Applicable for the Academic Year 2020-21 Batch: 2017

Applicable for the academicyear2018-19 Batch:2015

SCHEME & SYLLABUS

VII & VIIISEMESTERS

B.E. COMPUTER SCIENCE AND ENGINEERING

2020-21

Vision and Mission of theInstitution: Vision:

Dept. of CSE, SIT, Tumakuru

Applicable for the academic year 2020-21 Batch: 2017

Vision and Mission of the Institution:

Vision: “To develop young minds in a learning environment of high academic ambience by synergizing spiritual values and technological competence”. Mission: “To continuously strive for the total development of students by educating them in state-of-the-art technologies and helping them imbibe professional ethics and societal commitment, so that they emerge as competent professionals to meet the global challenges”.

Vision and Mission of the Department: Vision: “To work towards the vision of the institution by building a strong teaching and research environment that is capable of responding to the challenges of the 21st century”. Mission: “To prepare under graduate, graduate and research students for productive careers in industry and academia, through comprehensive educational programs, research in collaboration with industry & government, dissemination by scholarly publications and professional society & co- curricular activities”.

Program Educational Objectives (PEOs) Engineering graduates (CSE) will be able to: 1. Pursue successful careers in State/National/Multi-National companies as software developers by following sound professional and ethical practices in various cadres in key areas like networking, web design, cloud computing, big data processing, IoT, e-commerce, information security and so on. 2. Work effectively in multi-disciplinary and multi-cultural teams and demonstrate good soft skills. 3. Pursue higher education for a successful career in industry/academics/ research. 4. Pursue life-long learning, by anticipating trends in computer science and engineering, to excel in industry/academia or own a startup for a successful career as entrepreneur.

PROGRAM OUTCOMES Engineering Graduates will be able to:

Dept. of CSE, SIT, Tumakuru 1

Applicable for the academic year 2020-21 Batch: 2017 1. Engineering knowledge: Apply the knowledge of mathematics, science, engineering fundamentals, and an engineering specialization to the solution of complex engineering problems. 2. Problem analysis: Identify, formulate, review research literature, and analyze complex engineering problems reaching substantiated conclusions using first principles of mathematics, natural sciences, and engineering sciences. 3. Design/development of solutions: Design solutions for complex engineering problems and design system components or processes that meet the specified needs with appropriate consideration for the public health and safety, and the cultural, societal, and environmental considerations. 4. Conduct investigations of complex problems: Use research-based knowledge and research methods including design of experiments, analysis and interpretation of data, and synthesis of the information to provide valid conclusions. 5. Modern tool usage: Create, select, and apply appropriate techniques, resources, and modern engineering and IT tools including prediction and modeling to complex engineering activities with an understanding of the limitations. 6. The engineer and society: Apply reasoning informed by the contextual knowledge to assess societal, health, safety, legal and cultural issues and the consequent responsibilities relevant to the professional engineering practice. 7. Environment and sustainability: Understand the impact of the professional engineering solution in societal and environmental contexts, and demonstrate the knowledge of, and need for sustainable development. 8. Ethics: Apply ethical principles and commit to professional ethics and responsibilities and norms of the engineering practice. 9. Individual and team work: Function effectively as an individual, and as a member or leader in diverse teams, and in multidisciplinary settings. 10. Communication: Communicate effectively on complex engineering activities with the engineering community and with society at large, such as, being able to comprehend and write effective reports and design documentation, make effective presentations, and give and receive clear instructions.

11. Project management and finance: Demonstrate knowledge and understanding of the engineering and management principles and apply these to one’s own work, as a member and leader in a team, to manage projects and in multidisciplinary environments. 12. Life-long learning: Recognize the need for, and have the preparation and ability to engage in independent and life-long learning in the broadest context of technological change. Dept. of CSE, SIT, Tumakuru 2

Applicable for the academic year 2020-21 Batch: 2017

Program Specific Outcomes (PSOs) 1. Computer based systems development: Ability to apply the basic knowledge of database systems, computing, operating system, digital circuits, microcontroller, computer organization and architecture in the design of computer basedsystems.

2. Software development: Ability to specify, design and develop projects, application software and system software by using the knowledge of data structures, analysis and design of algorithm, programming languages, software engineering practices and open sourcetools.

3. Computer communications and Internet applications: Ability to design and develop network protocols and internet applications by incorporating the knowledge of computer networks, communication protocol engineering, cryptography and network security, distributed and cloud computing, data mining, big data analytics, ad hoc networks, storage area networks and wireless sensornetworks.

Dept. of CSE, SIT, Tumakuru 3

Applicable for the academic year 2020-21 Batch: 2017

3.0

1.5

4.0

26.0

Credits

BATCH2017 :

850

100

Total

Marks

400

S.E.E

Marks

21 21

450

Examination

C.I.E.

Marks

(Hrs)

Duration

Teaching

hours/week

VII Semester

Total

CSE

Dept.

Teaching

B.E. Computer Science Engineering Science & B.E. Computer

SCHEME OF TEACHING AND EXAMINATION: 2020 EXAMINATION: AND TEACHING OF SCHEME

SIDDAGANGA INSTITUTE OF TECHNOLOGY, TUMKUR TECHNOLOGY, OF INSTITUTE SIDDAGANGA

DEPARTMENT OF COMPUTER SCIENCE & ENGINEERING SCIENCE COMPUTER OF DEPARTMENT

Title

Sciences(HSS2)

Industrial Training

Major Project

Security Lab.

Cryptography & Network

Network Programming Lab

Design

Object Oriented Modeling and

Security

Cryptography & Network

CSIT

Sub.

Code

7CS02

Open Elective(OE3)

Humanity and Social

CSMP7

7CCI01

7CSL02

7CSL01

Professional Elective

Sl.

No.

Dept. of CSE, SIT, Tumakuru 4

Applicable for the academic year 2020-21 Batch: 2017

3.0

1.0 23.0

13.0

Credits

450

100

Total

Marks

200

S.E.E

Marks

250

C.I.E.

Marks

Examination

21 BATCH : 2017 BATCH : 21

(Hrs)

Duration

Teaching

hours/week

VIII Semester VIII

Total

CSE

Dept.

Computer Science & Engineering Science Computer

Teaching Teaching

B.E. B.E.

SIDDAGANGA INSTITUTE OF TECHNOLOGY, TUMKUR TECHNOLOGY, OF INSTITUTE SIDDAGANGA

DEPARTMENT OF COMPUTER SCIENCE & ENGINEERING SCIENCE COMPUTER OF DEPARTMENT

Title

–

SCHEME OF TEACHING AND EXAMINATION: 2020 EXAMINATION: AND TEACHING OF SCHEME

Technical Seminar Technical

Major Project Major

CSTS

Sub. Sub.

Code

CSMP8

Professional Elective Elective Professional

Sl.

No.

Dept. of CSE, SIT, Tumakuru 5

Applicable for the academic year 2020-21 Batch: 2017

List of Professional Electives Sl. No Sub. Code Course Title 1 CSPE01 Artificial Intelligence 2 CSPE02 Advanced DBMS 3 CSPE03 Data Compression 4 CSPE05 C# and .Net Technologies 5 CSPE06 Multimedia Computing 6 CSPE07 Data warehouse and Data Mining 7 CSPE08 Cloud Computing 8 CSPE09 Distributed Operating System 9 CSPE10 System Simulation & Modeling 10 CSPE11 Fuzzy Logic 11 CSPE12 Wireless Sensor Networks 12 CSPE13 Advanced Computer Architecture 13 CSPE14 Web 2.0 & rich internet application 14 CSPE15 Software Architecture 15 CSPE16 Computer Systems & Performance Analysis 16 CSPE17 Storage Area Networks 17 CSPE19 Communication Protocol Engineering 18 CSPE20 Ad hoc Wireless Networks 19 CSPE21 Multi-Core Architecture and Programming 20 CSPE22 Advanced Algorithms 21 CSPE23 Web Design Technique 22 CSPE24 Parallel Algorithms 23 CSPE25 Fundamentals of Digital Image Processing

24 CSPE26 Service Oriented Architecture 25 CSPE27 Mobile Computing 26 CSPE28 High Performance Computing 27 CSPE29 Network Management 28 CSPE30 Cyber Security 29 CSPE31 Software Testing

30 CSPE32 Advanced UNIX Programming 31 CSPE33 Foundations of Data Science 32 CSPE34 Big Data 33 CSPE35 Machine Learning Techniques 34 CSPE36 Project Management & Finance 35 CSPE37 Enterprise Content Management

36 CSPE38 Game Theory 37 CSPE39 Internet of Things 38 CSPE40 Web Technologies and its Applications 39 CSPE41 Foundations of Blockchain 40 CSPE42 Advanced Data Structures and Algorithms

Dept. of CSE, SIT, Tumakuru 6

Applicable for the academic year 2020-21 Batch: 2017

CRYPTOGRAPHY & NETWORK SECURITY

Contact Hours/ Week : 4+0+0 (L+T+P) Credits : 4 Total Lecture Hours : 52 CIE Marks : 50 Sub. Code : 7CCI01 SEE Marks : 50

COURSE OBJECTIVES: This Course will enable students to: 1. Define the security principles and explain the foundations of Cryptography and network security. {L1,L2} 2. Solve problems on classical encryption techniques and implement symmetric and asymmetric cryptographic algorithms. {L3} 3. Make use of advanced cryptographic tools to design secure networks. {L5} 4. Analyze different authentication protocols, integrity protocols and key agreement protocols. {L4}

UNIT-1 INTRODUCTION: Introduction: Computer Security concepts, The OSI Security Architecture, Security Services, Mechanisms and Attacks, A Model of Network Security. SYMMETRIC CIPHERS: Classical Encryption Techniques: Symmetric Cipher Model, Substitution Techniques, Transposition Techniques, Rotor machine, Steganography. Block Cipher and the Data Encryption Standard: Block Cipher Principles, The Data Encryption Standard, DES Example, Strength of DES, Differential and Linear Cryptanalysis. 10 Hrs

UNIT -2 SYMMETRIC CIPHERS (cont..) Block Cipher Operation: Multiple Encryption and triple DES, Electronic Code Book, Cipher Block Chaining Mode, Cipher Feedback Mode, Output feedback Mode, Counter Mode. Pseudorandom Number Generation and stream ciphers: Principles of Pseudorandom Number Generation, Pseudorandom Number Generators, Pseudorandom Number Generation using a block cipher, Streamcipher,RC4. 10 Hrs

UNIT -3 Number Theory: Prime Numbers, Fermat’s and Euler’s Theorems, Testing for Primality. PUBLIC-KEY CRYPTOGRAPHY AND RSA: Principles of Public-Key Cryptosystems, The RSA Algorithm. Diffie-Hellman Key Exchange. CRYPTOGRAPHIC DATA INTEGRITY ALGORITHMS: Cryptographic Hash Functions: Applications of Cryptographic hash functions, Two simple hash Functions, Secure Hash Algorithm. 10 Hrs

UNIT-4 MESSAGE AUTHENTICATION: Authentication Requirements, Authentication Functions, Message Authentication Codes, Security of MACs, MACs based on Hash Functions:HMAC. DIGITAL SIGNATURES: Digital Signatures, Digital Signature Standard.

Dept. of CSE, SIT, Tumakuru 7

Applicable for the academic year 2020-21 Batch: 2017

KEY MANAGEMENT AND DISTRIBUTION: Symmetric Key distribution using symmetric encryption, Symmetric Key distribution using Asymmetric encryption, Distribution of public keys, X.509certificates,Kerberos. 11 Hrs

UNIT-5 TRANSPORT-LEVEL SECURITY: Transport level security: Web Security considerations, Secure Sockets Layer and Transport Layer Security. Transport Layer Security. HTTPS, Secure Shell.

INTERNET SECURITY: Electronic Mail Security: Pretty Good Privacy, S/MIME.

IP Security: Overview, IP Security Policy. SYSTEM SECURITY: Intruders: Intruders, Intrusion detection. Malicious Software: Types of Malicious Software, Viruses. 10 Hrs Firewalls: The need for Firewalls, Firewall Characteristics, Types of Firewalls.

TEXT BOOK: William Stallings, Cryptography and Network Security, Fifth Edition, Prentice Hall of India, 2005 (Chapters 1.1-1.6, 2.1-2.5, 3.1-3.5, 6.1-6.6, 7.1-7.5, 8.1-8.3, 9.1-9.2, 10.1,11.1-11.2, 11.5,12.1-12.5,13.1,13.4,14.1-14.4,15.3,16.1-16.5,18.1-18.2,19.1,19.2,20.1-20.2,21.1- 21.2, 22.1-22.3)

REFERENCEBOOKS: 1. Charlie Kaufman, Radia Perlman, Mike Speciner, Network Security: Private Communication in a Public World, Second Edition, Pearson Education Asia,2002. 2. AtulKahate, Cryptography and Network Security, Tata McGrawHill,2003.

Course Outcomes: At the end of the course, students will be able to 1 Explain the principles and architecture of cryptography and network security and Interpret various security attacks 2 Apply the knowledge of mathematics to analyze and solve different classical encryption techniques 3 Illustrate symmetric cryptographic algorithms, Modes of operations, Pseudorandom Number Generations, Stream ciphers and analyze them for various types of attacks 4 Solve problems on number theory, develop solutions for problems on public key cryptosystems and analyze different integrity protocols 5 Explain and analyze different authentication and key management and distribution protocols. Apply the knowledge of engineering fundamentals to comprehend existing network security protocols

Dept. of CSE, SIT, Tumakuru 8

Applicable for the academic year 2020-21 Batch: 2017

OBJECT ORIENTED MODELING AND DESIGN

Contact Hours/ Week : 4 + 0+ 0 ( L+T+P) Credits : 4 Total Lecture Hours : 52 CIE Marks : 50 Sub. Code : 7CS02 SEE Marks : 50

Course Objectives: This Course will enable students to: 1. Acquire an ability to analyze, design and develop object oriented solutions to software systems of varying complexity. 2. Explain the object oriented concepts, system development life cycle, methodologies, UML language, and design patterns. 3. Apply & Analyze object oriented methodologies, unified approach and unified modeling language on a given case study . 4. Realize significance of design patterns; discuss the applicability of design patterns in modeling and design.

UNIT-1 INTRODUCTION: An Overview of Object Oriented Systems Development: Why an Object Orientation? Overview of the Unified Approach. Object Basics: Introduction, An Object-Oriented Philosophy, Objects, Classes, Attributes; Object Behavior and Methods, Encapsulation and Information Hiding, Class Hierarchy, Polymorphism, Object Relationships and Associations, Aggregations and Object Containment, Advanced topics. Object-Oriented Systems Development Life Cycle: Introduction, The Software development process, Building High- Quality software, Object-Oriented System Development: A Use-Case Driven Approach, Reusability. 08 Hrs

UNIT -2 METHODOLGY, MODELING AND UML: Object Oriented Methodologies: Introduction: Survey of Some of the Object-Oriented Methodologies, Patterns, Frameworks, The Unified Approach, Unified Modeling Language: Introduction, Static and Dynamic Models, Why Modeling, Introduction to the Unified Modeling Language, UML Diagrams, UML Class Diagram, Use-Case Diagram, UML Dynamic Modeling, Model Management: Packages and Model Organizations, UML Extensibility,UMLMeta-Model. 08 Hrs

UNIT -3 OBJECT ORIENTED ANALYSIS: Object Oriented Analysis Process – Identifying Use Case: Introduction, Business Object Analysis: Understanding the Business Layer, Use-Case Driven Object-Oriented Analysis: The Unified Approach, Business Process Modeling, Use-Case Model, Developing effective documentation, Case Study: ViaNet Bank ATM. Object Analysis-Classification: Introduction, Classification Theory, Approaches for Identifying Classes, Noun Phrase Approach, Common class patterns approach, Use-Case Driven Approach-Identifying classes and Their Behaviors

Dept. of CSE, SIT, Tumakuru 9

Applicable for the academic year 2020-21 Batch: 2017 through sequence / Collaboration Modeling, classes, Responsibilities, and Collaborators, Naming Classes. Identifying Object Relationships, A-Part-Of Relationships-Aggregation, Case Study. Class Responsibility: Identifying Attributes and Methods, Class Responsibility: Defining attributes by analyzing Use Cases and other UML Diagrams, Defining Attributes for ViaNet Bank Objects, Object Responsibility: Methods and Messages, Defining Methods for ViaNetBankObjects. 14 Hrs

UNIT - 4 OBJECT-ORIENTED DESIGN: The Object-Oriented Design Process and Design Axioms: Introduction, The Object- Oriented Design Process, Object-Oriented Design Axioms, Corollaries, Design Patterns. Designing Classes: Introduction, The Object-Oriented Design Philosophy, UML Object constraint Language, Designing Classes: The Process, Class Visibility: DesigningWell-Defined public, Private and Protected Protocols, Designing Classes: Refining Attributes, Refining Attributes for the ViaNet Bank Objects, Designing Methods and protocols, Designing Methods for the ViaNet Bank Objects, Packages and Managing classes. Access Layer-Object storage and object interoperability: Introduction, Object Store and Persistence: Database Management Systems, Organization and Access control, Distributed Databases and Client- Server Computing, Distributed Objects Computing, Object-Oriented Database Management Systems, Object-Relational systems, Multidatabase systems, Designing Access layer classes, Case Study: Designing the access layer for the ViaNet Bank ATM. View Layer-Designing Interface objects: Introduction, User Interface design as a creative process, Designing view layer classes. Macro-Level Process: Identifying View Classes by Analyzing Use Cases, Macro-Level Process, The Purpose of a view Layer Interface, Prototyping the User Interface. 14 Hrs UNIT 5 DESIGNING OBJECT WITH RESPONSIBILITIES: UML versus design principles, Object design: Example inputs, activities, and outputs. Responsibilities and responsibility-Driven Design. GRASP: A Methodical approach to basic OO Design. what’s the connection between re3sponsibilities, GRASP,and,UML Diagrams? What are patterns? Where are we now? A short example of object design with GRASP. Apply GRASP to object Design. Creator, Information Expert, Low coupling, Controller, High cohesion, Recommended Resources. GRASP: MORE OBJECTS WITH RESPONSIBILITIES: Polymorphism, Pure fabrication, Indirection, Protected variations. APLLYING GoF DESIGN PATTERNS: Adapter, Some GRASP Principles as a Generalizations of other Patterns,”Analysis” Discoveries during Design: Domain model, Factory, Singleton, Conclusion of the External services with varying interfaces problem, Strategy, Composite(GoF) and other Design Principles, Façade(GoF),Conclusion,RecommendedResources. 8 Hrs

TEXT BOOKS: 1 Ali Bahrami Object Oriented Systems Development, McGraw Hill, 1999 (Chapters 1 to 12). 2 Craig Larman Applying UML and Patterns, An Introduction to Object-Oriented Analysis and design, Addison-Wesley, 1998.

Dept. of CSE, SIT, Tumakuru 10

Applicable for the academic year 2020-21 Batch: 2017

REFERENCE BOOKS: 1 Rebecca wirfs – Designing Object-Oriented Software, Prentice-Hall India is our Brock et al country, 1990 2 Grady Booch et al Unified Modeling Language User Guide, Addison-Wesley, 1999 3 Gamma, E et al Design Patterns: Elements of Reusable Object-Oriented Software, Addison Wesley, 1995 4 Martin. J., and Odell, J Object-Oriented Methods, A Foundation, Prentice-Hall, 1995

Course Outcomes: After the completion of this course, students will be able to: 1. Apply the fundamental knowledge of object oriented software development, methodologies, UML language, and design patterns to the solution of complex engineering problems. 2. Analyze, formulate and review and justify a case study to identify classes, attributes, methods and relationships among them in the solutions. 3. Design UML models for a given case study using object oriented software development methodologies. 4. Design a good solution with the proper system components for a given case study by applying object oriented design axioms and corollaries and patterns. 5. Develop a good transparent and natural view layer for the solution of a given case study and Create a robust object oriented data base with better shareability and concurrency

Dept. of CSE, SIT, Tumakuru 11

Applicable for the academic year 2020-21 Batch: 2017

NETWORK PROGRAMMING LABORATORY

Lab Hours/ Week : 3.0 Credits : 1.5 Sub. Code : 7CSL01 CIE Marks : 50 SEE Marks: 50

Note: Student is required to solve one problem from PART-A and one problem from PART- B. The questions are allotted based on lots. Part-A questions carry 35 marks and Part-B questions carry 15marks.

PART A 1. For the given network graph, write a program to implement Link state routing algorithm to build a routing table for the given node. 2. Write a program to divide the message into variable length frames and sort them and display the message at the receiving side. 3. Using TCP/IP sockets, write a client – server program, the client sends the file name and the server sends back the requested text file ifpresent. 4. Implement the above program using FIFOs as IPCchannels. 5. Using UDP, write a client – server program, to exchange messages between client and the server. 6. Write a socket program to demonstrate IP multicasting which provides the capability for an application to send a single IP datagram that a group of hosts in a network canreceive. 7. Write a program to implement sliding window protocol between twohosts. 8. Write a program for error detecting code using CRC-CCITT (16-bits).

PART – B SIMULATION EXERCISES The following experiments should be conducted using NS2/any suggested simulator 1. Simulate a three nodes point – to – point network with duplex links between them. Set the queue size and vary the bandwidth and find the number of packetsdropped. 2. Simulate a four node point-to-point network with the link connectedasfollows:n0 – n2, n1– n2 and n2 – n3. Apply TCP agent between n0-n3 and UDP betweenn1 n3. Apply relevant applications over TCP and UDP agents changing the parameter and determine the number of packets sent by TCP / UDP. 3. Simulate the different types of Internet traffic such as FTP and TELNET over a network and analyze the throughput. 4. Simulate an Ethernet LAN using n nodes (6-10), change error rate and data rate and compare the throughput. 5. Simulate an Ethernet LAN using n nodes and set multiple traffic nodes and determine the collision across different nodes. 6. Simulate the transmission of ping messages over a network topology consisting of 6 nodes and find the number of packets dropped due to congestion (can useNS2). 7. Simulate simple ESS with transmitting nodes in wire-less LAN and determine the performance with respect to transmission of packets. 8. Simulate simple ad-hoc network with transmitting nodes and determine the performance with respect to transmission of packets.

Dept. of CSE, SIT, Tumakuru 12

Applicable for the academic year 2020-21 Batch: 2017

Additional programs: 1. Write a program to implement the following: a. For the given network graph with loops, implement Radia-Perlman algorithm to avoid loops. b. For the given network topology consisting of bridges and nodes, implement the learning bridge algorithm. 2. Write a program to compute Internet checksum (16bits). 3. Write a program for congestion control using Token bucket algorithm. 4. Write a program to implement Differentiated QoS using weighed fair queuing. 5. Write a program to implement MD5algorithm. 6. Write a program to implement RED congestion avoidance algorithm. 7. Write a program to implement distance vector routing algorithm.

Course Outcomes: After the completion of this course, students will be able to:

1. Develop and Implement network routing algorithms by applying network programming concepts. 2. Implement and analyse error detection and correction techniques in network applications. 3. Implement client server applications with TCP/UDP Socket Programming. 4. Simulate and analyse point to point network with duplex links, different types of internet traffic like FTP & Telnet, Ethernet LAN for error rates, data rates, throughput, collision detections and congestion control of ping messages over a topology using network simulator (NS2). 5. Analyze Network Simulator (NS2) output based on various network factors like packet loss, delay, error, node movements in wireless networks, etc.

Dept. of CSE, SIT, Tumakuru 13

Applicable for the academic year 2020-21 Batch: 2017

CRYPTOGRAPHY & NETWORK SECURITY LABORATORY

Lab Hours/ Week : 3.0 Credits : 1.5 Sub. Code : 7CSL02 CIE Marks : 50 SEE Marks : 50

1. Write a program to perform the following using Playfair cipher technique (i) Encrypt a given message M with different keys {k1,k2,…,kn}. Print key and cipher text pair (ii) Decrypt the cipher texts obtained in (i) to get back M 2. Write a program to perform the following using Hill cipher: (i) Encrypt a message M with a given key matrix of size 2X2 and3X3 (ii) Decrypt the cipher text obtained in (i) by computing inverse of the respective key matrix. 3. Perform encryption and decryption using mono-alphabetic cipher. The program should support the following: (i) Construct an input file named plaintext.txt (consisting of 1000 alphabets, without any space or special characters) (ii) Encrypt the characters of plaintext.txt and store the corresponding cipher text characters inciphertext.txt (iii) Compute the frequency of occurrence of each alphabet in both plaintext.txt and ciphertext.txt and tabulate the results as follows

Frequency Plaintext character Cipher text character 12.34 A X ...... 4. Write a program to perform encryption and decryption using transposition technique with column permutation given as key. 5. Generate and print 48-bit keys for all sixteen rounds of DES algorithm, given a 64-bit initial key. th th 6. Given 64-bit output of (i-1) round of DES, 48-bit i round key Ki and E table, find the 48- bit input for S-box. th 7. Given 48-bit input to S-box and permutation table P, find the 32-bit output Riof i round of DES algorithm. 8 Implement the following with respect to RC4: (i) Print first n key bytes generated by key generation process. (ii) Illustrate encryption/decryption by accepting one byte data as input on the above generated keys. 9 Write a program to generate large random number using BBS random number generator algorithm and check whether the generated number is prime or not using RABIN-MILLER primality testing algorithm.

Dept. of CSE, SIT, Tumakuru 14

Applicable for the academic year 2020-21 Batch: 2017

10 Implement RSA algorithm using client-server concept. The program should support the following : (i) Client generates {PU, PR} and distributes PU to Server. (ii) Sever p encrypts message M using client’s public key{PU}. (iii) Client decrypts the message sent by server using its private key{PR}.

11 Implement RSA algorithm to process blocks of plaintext (refer Figure 9.7 of the text book), where plaintext is a string of characters and let the block size be two characters. (Note: assign a unique code to each plain text character i.e., a=00, A=26). The program should support the following. (i) Accept string of characters as plaintext. (ii) Encryption takes plaintext and produces ciphertext characters (iii) Decryption takes ciphertext characters obtained in step ii and produces corresponding plaintext characters (iv) Display the result after each step

12 Implement RSA algorithm using client-server concept. Using this illustrate secret key distribution scenario with confidentiality and authentication. The program should support the following: (v) Both client and server generate {PU, PR} and distribute PU to each other. (vi) Establish a secret key K between client and server by exchanging the messages as shown in below figure.

13 Compute common secret key between client and server using Diffie-Hellman key exchange technique. Perform encryption and decryption of message using the shared secret key (Use simple XOR operation to encrypt and decrypt the message.)

14 Implement DSS algorithm for signing and verification of messages between two parties (obtain H(M) using simple XOR method of hash computation on M).

Dept. of CSE, SIT, Tumakuru 15 Applicable for the academic year 2020-21 Batch: 2017

Additional Assignments to be Solved in the lab:

1. Implementation of Merkel Tree.

2. Implementation of Hash Function other Application.

Course Outcomes: After the completion of this course, students will be able to:

1. Implement and execute Symmetric Algorithm, like Hill Cipher, Playfair and transposition technique. 2. Implement and execute Block Cipher Algorithm.(DES) 3. Implement and execute stream cipher Algorithms, (RC4) 4. Implement and execute Asymmetric Algorithm, like RSA and Diffie-Hellman key change. 5. Implement DSS algorithm for signing and verification of messages between two parties’ key agreement protocols.

Dept. of CSE, SIT, Tumakuru 16 Applicable for the academic year 2020-21 Batch: 2017

ARTIFICIAL INTELLIGENCE Contact Hours/ Week : 3 + 0 (Lecture + Tutorial) Credits : 3.0 Total Lecture Hours : 39 CIE Marks : 50 Sub. Code : CSPE01 SEE Marks : 50 UNIT -1 INTRODUCTION, INTELLIGENT AGENTS, SEARCHING: What is AI? Intelligent Agents: Agents and environment; Rationality; the nature of environments; the structure of agents. Problem-solving: Problem-solving agents; Searching for solution; Uninformed search strategies; Informed search strategies. 7 Hrs

UNIT - 2 CONSTRAINT SATISFACTION PROBLEMS, LOGICAL AGENTS, FIRST-ORDER LOGIC: Constraint satisfaction problems; Backtracking search for CSPs; Knowledge-based agents; The wumpus world as an example world; Logic; propositional logic; Reasoning patterns in propositional logic; Syntax and semantics of first-order logic; Using first-order logic; Knowledge engineering in first-order logic. 7 Hrs

UNIT - 3 INFERENCE IN FIRST-ORDER LOGIC: Propositional vs. First-order Inference; Unification and Lifting; Forward chaining; backward chaining; Resolution. KNOWLEDGE REPRESENTATION: Issues in Knowledge representation; Associationist Theories of Meaning; Semantic Nets; Frames; Conceptual graphs; Agent-based and distributed problem solving; Overview of expert system technology; Rule-based expert systems. 8 Hrs

UNIT - 4 PLANNING AND REASONING IN UNCERTAIN SITUATIONS: Planning; STRIPS; Reasoning in Uncertain situations; Logic-based abductive inference; Nonmonotonic reasoning; Truth Maintenance systems The Stochastic approach to Uncertainty: Directed Graphical Model, d-separation, inference algorithm, discrete Markov process, hidden Markov Model 9 Hrs UNIT - 5 MACHINE LEARNING: Introduction; A framework for symbol-based learning; Version Space search; The candidate elimination algorithm; The ID3 decision tress induction algorithm: Top-down decision tree induction, Information theoretic Test Selection; Inductive Bias and Learnability; Reinforcement Learning 8 Hrs

Dept. of CSE, SIT, Tumakuru 17 Applicable for the academic year 2020-21 Batch: 2017

TEXT BOOK: 1 Stuart Russel A Modern Approach, 3rd Edition, Pearson Education, 2009. Peter Norvig (For Unit I, II, and III Selected topics from Chapters 1, 2, 3, 4, 5, 7, 8 and 9).

2 George F Luger Structures and Strategies for Complex Problem Solving 5th Edition, Pearson Education, 2011. (For Unit III, IV, and V: Selected topics from Chapters 7, 8, 9 and 10).

REFERENCE BOOKS: 1 Elaine Rich Artificial Intelligence -2nd Edition, Tata McGraw Hill, 1991. Kevin Knight 2 Nils J. Nilsson Principles of Artificial Intelligence, 1980. Elsevier

Course Outcomes: After the completion of this course, students will be able to:

1 Apply the knowledge of Artificial Intelligence to write simple algorithm for agents. 2 Apply AI knowledge to solve problem on search algorithm 3 Develop knowledge base sentences propositional logic and first order logic. 4 Apply first order logic to solve knowledge engineering process. 5 Apply and analyze the knowledge of machine learning.

Dept. of CSE, SIT, Tumakuru 18 Applicable for the academic year 2020-21 Batch: 2017

ADVANCED DBMS Contact Hours/ Week : 3 + 0 (Lecture + Tutorial) Credits : 3.0 Total Lecture Hours : 39 CIE Marks : 50 Sub. Code : CSPE02 SEE Marks : 50 UNIT-1 Disk storage and basic file structures and hashing: Introduction, Secondary Storage Devices, Buffering of Blocks, Placing File Records on Disk, Operations on Files, Files of Unordered Records, Files of Ordered Records, Hashing Techniques, Other Primary File Organizations, Parallelizing Disk Access Using RAID Technology, New Storage Systems. 6 Hrs UNIT-2 Index structures for files: Types of Single-Level Ordered Indexes, Multilevel Indexes, Dynamic Multilevel Indexes Using B Trees and B+ Trees, Indexes on Multiple Keys, Other Types of Indexes. Concepts for object databases: Overview of Object-Oriented Concepts, Overview of the Object Model of ODMG, The Object Definition Language ODL, The Object Query Language OQL, Overview of the C++ Language Binding, Object Database Conceptual Design, Object Relational Features of Oracle 8. 9 Hrs UNIT-3 Query processing and optimization: Translating SQL Queries into Relational Algebra, Algorithms for External Sorting, Algorithms for SELECT and JOIN Operations, Algorithms for PROJECT and SET Operations, Implementing Aggregate Operations Using Pipelining, Using Heuristics in Query Optimization, Using Selectivity and Cost Estimates in Query Optimization, Overview of Query Optimization in ORACLE, Semantic Query Optimization. 8 Hrs UNIT-4 Practical database design and tuning: Physical Database Design in Relational Databases, An Overview of Database Tuning in Relational Systems. Distributed databases and client-server architecture: Distributed Database Concepts, Data Fragmentation, Replication, and Allocation Techniques for Distributed Database Design, Types of Distributed Database Systems, Query Processing in Distributed Databases, Overview of Concurrency Control and Recovery in Distributed Databases, An Overview of 3–Tier Client-Server Architecture, Distributed Databases in Oracle 8 Hrs

UNIT-5 Data mining concepts and data warehousing: Overview of Data Mining Technology, Applications of Data Mining, Commercial Data Mining Tools, Introduction to Data Warehousing, Definitions and Terminology, Characteristics of Data Warehouses, Data Modeling for Data Warehouses, Building a Data Warehouse, Typical Functionality of a Data Warehouse, Data Warehouse Versus Views, Problems and Open Issues in Data Warehouses. Emerging database technologies and applications: Mobile Databases, Multimedia Databases, Geographic Information Systems. 8 Hrs

TEXT BOOK: 1 Elmasri and Navathe. Fundamentals of Database Systems. Ed 5. Pearson Education. 2011. REFERENCE BOOKS: 1 Silberschatz, Korth and Sudharshan. Data base System Concepts. Ed 4. Mc- GrawHill. 2 Raghu Ramakrishnan and Johannes Database Management Systems. Ed 3. Gehrke. McGraw-Hill.

Dept. of CSE, SIT, Tumakuru 19 Applicable for the academic year 2020-21 Batch: 2017

DATA COMPRESSION Contact Hours/ Week : 3 + 0 (Lecture + Tutorial) Credits : 3.0 Total Lecture Hours : 39 CIE Marks : 50 Total Tutorial Hours : 00 SEE Marks : 50 Sub. Code : CSPE03 UNIT-1 Introduction, Lossless Compression: Compression techniques: Modeling and coding. Mathematical preliminaries for lossless compression: Overview; Basic concepts of Information Theory; Models; Coding; Algorithmic information theory: Minimum description length principle. Huffman coding: Overview; The Huffman coding algorithm, Minimum variance Huffman codes; Application of Huffman coding for text compression. 7 Hrs UNIT-2 Lossless Compression: Dictionary Techniques: Overview; Introduction; Static dictionary; Adaptive dictionary; Applications: UNIX compress, GIF, PNG, V.42. Lossless image compression: Overview; Introduction; Basics; CALIC; JPEG-LS; Multi resolution approaches; Facsimile encoding: Run-length coding, T.4 and T.6. Basics of Lossy Coding Some mathematical concepts: Overview; Introduction; Distortion criteria; Models. Scalar quantization: Overview; Introduction; The quantization problem; Uniform quantizer; Adaptive quantization. 10 Hrs UNIT-3 Vector Quantization, Differential Encoding Vector quantization: Overview; Introduction; Advantages of vector quantization over scalar quantization; The LBG algorithm. Differential Encoding: Overview; Introduction; The basic algorithm; Prediction in DPCM; Adaptive DPCM; Delta modulation; Speech coding; Image coding. 7 Hrs UNIT-4 Some Mathematical Concepts, Transform coding Some mathematical concepts: Linear systems; Sampling; Discrete Fourier transform; Z- transform. Transform coding: Overview; introduction; The transform; Transforms of interest; Quantization and coding for transform coefficients; Application to image compression – JPEG; Application to audio compression – MDCT. 8 Hrs UNIT-5 Subband Coding, Audio Coding Subband Coding: Overview; introduction; Filters; The basic subband coding algorithm; Bit allocation; Application to speech coding – G.722; Application to audio coding – MPEG audio; Application to image compression. Audio Coding: Overview; Introduction; MPEG audio coding; MPEG advanced audio coding; Dolby AC3; Other standards. 7 Hrs

TEXT BOOK: 1 Khalid Sayood Introduction to Data Compression, 3rd Edition, Elsevier, 2006.

REFERENCE BOOK: 1 D. Salomon Data Compression: The Complete Reference, Springer, 1998.

Dept. of CSE, SIT, Tumakuru 20 Applicable for the academic year 2020-21 Batch: 2017

C# AND .NET TECHNOLOGIES

Contact Hours/ Week : 3 Credits : 3.0 Total Lecture Hours : 39 CIE Marks : 50 Sub. Code : CSPE05 SEE Marks : 50 UNIT- 1 The Philosophy of .NET: Understanding the Previous State of Affairs, The .NET Solution, The Building Blocks of the .NET Platform, The Role of the .Net Base Class Libraries, What C# Brings to the Table, Additional .NET-Aware Programming Languages, An Overview of .NET Binaries. The Role of the Common Intermediate Language, The Role of .NET Type Metadata, The Role of the Assembly Manifest. Compiling CIL to Platform-Specific Instruction, Understanding the Common Type System, Understanding the Common Language Specification, Understanding the Common Language Runtime. A Tour of the .Net Namespaces- Accessing a Namespace Programmatically. Building C# Applications: The Role of the Command Line Compiler (csc.exe), Building C# Application Using csc.exe. Working with csc.exe Response Files, Generating Bug Reports, C# “Preprocessor” Directives- Specifying code regions, Conditional code compilation, Issuing warnings and errors. The System.Environment Class. 07 Hrs UNIT- 2 C# Language Fundamentals: The Anatomy of a Basic C# Class,Creating Objects: Constructor Basics. The Composition of a C# Application, Default Assignment and Variable Scope. The C# Member Variable Initialization Syntax, Basic Input and Output with the Console Class, Understanding Value Types and Reference Types, The Master Node: System. Object, The System Data Types (and C# Aliases). Converting Between Value Types and Reference Types: Boxing and Unboxing.Defining Custom Class Methods, understanding Static Methods, Method Parameter Modifiers. Array Manipulation in C#, String Manipulation in C#. C# Enumerations. Defining Structures in C#. Defining Custom Namespaces. 08 Hrs

UNIT- 3 Object-Oriented Programming with C#: Formal Definition of the C# Class, Definition the “Default Public Interface” of a Type, Recapping the Pillars of OOP. The First Pillars: C#’s Encapsulation Services. Pseudo- Encapsulation: Creating Read-Only Fields, The Second Pillar: C#’s Inheritance Supports, keeping Family Secrets: The “protected” Keyword. Nested Type Definitions, The Third Pillar: C#’s Polymorphic Support. Casting Between Types. Exceptions and Object Lifetime: Ode to Errors, Bugs, and Exceptions, The Role of .NET Exception Handling, The System.Exception Base Class, Throwing a Generic Exception. Catching Exception, CLR System-Level Exception (System.SystemException), Custom Application-Level Exception (System. Application Exception). Handling Multiple Exceptions, The Finally Block, Dynamically Identifying Application- and System-Level Exceptions. Understanding Object Lifetime, The CIL of “new”, The Basics of Garbage Collection, Finalizing a Type. The finalization Process, Building an Ad Hoc Destruction Method, Garbage Collection Optimizations, The System.GC Type . 08 Hrs

Dept. of CSE, SIT, Tumakuru 21 Applicable for the academic year 2020-21 Batch: 2017

UNIT- 4 Interfaces and Collections: Defining Interfaces Using C#, Invoking Interface Members at the Object Level, Exercising the Shapes Hierarchy.Understanding Explicit Interface Implementation, Interfaces As Polymorphic Agents, Building Interface Hierarchies. Building a Custom Enumerator. (IEnumerable and IEnumerator), Building Cloneable Objects (ICloneable), Building Comparable Objects (IComparable). Exploring the System.Collections Namespace.

Delegates: Understanding the .NET Delegate Type, Members of System.Multicast Delegate. The Simplest Possible Delegate Example. Understanding Asynchronous Delegates. 08 Hrs

UNIT- 5 Advanced C# Type Construction Techniques: The Advanced Keywords of C#, A Catalog of C# Keywords, Building a Custom Indexer, A Variation of the Cars Indexer. Overloading Operators. Understanding Custom Type Conversion, Creating Custom Conversion Routines. Defining Implicit Conversion Routines.

Understanding .NET Assembles: An Overview of .NET Assembly, Building a Single File Test Assembly, A C# Client Application. Building the Multifile Assembly, Using the Multifile Assembly, Understanding Private Assemblies, Understanding Shared Assembly, Understanding Strong Names, Building a Shared Assembly. 08 Hrs

TEXT BOOK: 1 Andrew Troelsen. C# and the .Net Platform, Second Edition

REFERENCE BOOK: 1 Herbert Schildt C#, The Complete Reference, Tata McGraw Hill, 2004.

Dept. of CSE, SIT, Tumakuru 22 Applicable for the academic year 2020-21 Batch: 2017

MULTIMEDIA COMPUTING

Contact Hours/ Week : 3 Credits : 3.0 Total Lecture Hours : 39 CIE Marks : 50 Sub. Code : CSPE06 SEE Marks : 50 UNIT-1 Multimedia communications: Introduction, multimedia information representation, multimedia networks, multimedia applications, media types, communication modes, network types, multipoint conferencing, network QOS application QOS. 8 Hrs

UNIT-2 Multimedia information representation: Introduction, digitization principles: analog signals, encoder design. Decoder design, text: unformatted text, formatted text, hypertext, images: graphics, digitized documents, digitized pictures. Audio: PCM speech, CD-quality audio, synthesized audio, Video: broadcast television, digital video, video content. 8 Hrs

UNIT-3 Text and image compression: Introduction, compression principles, Text compression: Huffman coding, Arithmetic coding, Lempel-Ziv coding, Lempel-ZIV-Welsh coding, Image compression: GIF, TIFF, JPEG. 8 Hrs

UNIT-4 Audio and video compression: introduction, audio compression, DPCM, ADPCM, APC, LPC, video compression, video compression principles, h.261, h.263, MPEG, MPEG-1, MPEG-2, MPEG-4 and MPEG-7. 8 Hrs

UNIT-5 Computer-Based Animation, Content Analysis: Basic Concepts; Specification of Animations; Methods of Controlling Animation; Display of Animation; Transmission of Animation; Virtual Reality Modeling Language.: Simple Vs. Complex Features; Analysis of Individual Images; Analysis of Image Sequences; Audio Analysis; Applications. 7 Hrs

TEXT BOOKS: Multimedia Communications: Applications, Networks, Protocols, and 1 Fred Halsall. Standards,Pearson Education, Asia, Second Indian reprint 2002. Ralf Steinmetz, “Multimedia Fundamentals: Vol 1-Media Coding and Content 2 Klara Narstedt Processing”, Pearson Education, 2004.

REFERENCE BOOKS: Prabhat K. Andleigh, 1 “Multimedia Systems Design”, PHI, 2004. Kiran Thakrar 2 Nalin K. Sharda Multimedia Information Networking

Dept. of CSE, SIT, Tumakuru 23 Applicable for the academic year 2020-21 Batch: 2017

DATA WAREHOUSE AND DATA MINING

Contact Hours/ Week : 3 Credits : 3.0 Total Lecture Hours : 39 CIE Marks : 50 Sub. Code : CSPE07 SEE Marks : 50 UNIT- 1 Introduction: What Motivated Data Mining? Why Is It Important? So, What Is Data Mining?, Data Mining—On What Kind of Data? Data Mining Functionalities—What Kinds of Patterns Can Be Mined? Are All of the Patterns Interesting? Classification of Data Mining Systems, Data Mining Task Primitives, Integration of a Data Mining System with a Database or Data Warehouse System, Major Issues in Data Mining Data Preprocessing: Why Preprocess the Data? Descriptive Data Summarization, Data Cleaning, Data Integration and Transformation, Data Reduction, Data Discretization and Concept Hierarchy Generation 8 Hrs UNIT- 2 Data Warehouse and OLAP Technology: An Overview What Is a Data Warehouse? Differences between Operational Database Systems and Data Warehouses, But, Why Have a Separate Data Warehouse? A Multidimensional Data Model From Tables and Spreadsheets to Data Cubes, Stars, Snowflakes, and Fact Constellations: Schemas for Multidimensional Databases, Examples for Defining Star, Snowflake and Fact Constellation Schemas, Measures: Their Categorization and Computation, Concept Hierarchies, LAP Operations in the Multidimensional Data Model, A Starnet Query Model for Querying Multidimensional Databases Data Warehouse Architecture Steps for the Design and Construction of Data Warehouses, A Three-Tier Data Warehouse Architecture, Data Warehouse Back-End Tools and Utilities, Metadata Repository, Types of OLAP Servers: ROLAP versus MOLAP versus HOLAP From DataWarehousing to Data Mining Data Warehouse Usage, From On-Line Analytical Processing to On-Line Analytical Mining 08 Hrs UNIT- 3 Data Cube Computation and Data Generalization Efficient Methods for Data Cube Computation A Road Map for the Materialization of Different Kinds of Cubes, Multiway Array Aggregation for Full Cube Computation, BUC: Computing Iceberg Cubes from the Apex Cuboid Downward, Star-cubing: Computing Iceberg Cubes Using a Dynamic Star-tree Structure, Precomputing Shell Fragments for Fast High-Dimensional OLAP, Computing Cubes with Complex Iceberg Conditions Further Development of Data Cube and OLAP Technology

Dept. of CSE, SIT, Tumakuru 24 Applicable for the academic year 2020-21 Batch: 2017

Discovery-Driven Exploration of Data Cubes, Complex Aggregation at Multiple Granularity: Multifeature Cubes, Constrained Gradient Analysis in Data Cubes Mining Frequent Patterns, Associations, and Correlations: Basic Concepts and a Road Map Market Basket Analysis: A Motivating Example, Frequent Item sets, Closed Item sets, and Association Rules, Frequent Pattern Mining: A Road Map Efficient and Scalable Frequent Item set Mining Methods The Apriori Algorithm: Finding Frequent Item sets Using Candidate Generation, Generating Association Rules from Frequent Item sets, Improving the Efficiency of Apriori, Mining Frequent Item sets without Candidate Generation, Mining Frequent Item sets Using Vertical Data Format, Mining Closed Frequent Itemsets. 08 Hrs

UNIT- 4 Mining Various Kinds of Association Rules Mining Multilevel Association Rules, Mining Multidimensional Association Rules from Relational Databases and Data Warehouses Classification and Prediction What Is Classification? What Is Prediction? Issues Regarding Classification and Prediction Preparing the Data for Classification and Prediction, Comparing Classification and Prediction Methods 08 Hrs UNIT- 5 Classification by Decision Tree Induction Decision Tree Induction, Attribute Selection Measures, Tree Pruning, Scalability and Decision Tree Induction Bayesian Classification Bayes’ Theorem, Naïve Bayesian Classification, Bayesian Belief Networks, Training Bayesian Belief Networks Rule-Based Classification Using IF-THEN Rules for Classification, Rule Extraction from a Decision Tree, Rule Induction Using a Sequential Covering Algorithm Prediction Linear Regression, Nonlinear Regression, Other Regression-Based Methods 7 Hrs TEXT BOOKS: 1 Jiawei I-lan, & Micheline Data Mining: Concepts and Techniques, 2nd Edition, Kamber Elsevier. 2 Arun K. Pujari Data Mining Techniques”, University Press (India) Limited, First Edition,2001.

REFERENCE BOOKS: 1 Margaret H.Dunham. Data Mining: Introductory and Advanced Topics”.Pearson Education,First Indian Reprint,2003 2 David Hand, Heikki Mannila Principles of Data Mining MIT press-2001 and Padhraic Smyth

Dept. of CSE, SIT, Tumakuru 25 Applicable for the academic year 2020-21 Batch: 2017

CLOUD COMPUTING

Contact Hours/ Week : 3 Credits : 3.0 Total Lecture Hours : 39 CIE Marks : 50 Total Tutorial Hours : 0 SEE Marks : 50 Sub. Code : CSPE08

UNIT- 1 Defining Cloud Computing: Cloud Types, The NIST model, The Cloud Cube Model, Deployment models, Service models, Examining the Characteristics of Cloud Computing, Paradigm shift, Benefits of cloud computing, Disadvantages of cloud computing; Assessing the value proposition: Early adopters and new applications, the laws of cloudonomics, cloud computing obstacles, behavioral factors relating to cloud adoption, measuring cloud computing costs, specifying SLAs 07 Hrs

UNIT- 2 Understanding Cloud Architecture: Exploring the Cloud Computing Stack, Composability, Infrastructure, Platforms, Virtual Appliances, Communication Protocols; Understanding Services and Applications by Type: Defining IaaS, Defining PaaS, Defining SaaS, Defining IDaaS. 09 Hrs

UNIT- 3 Understanding Abstraction and Virtualization: Using Virtualization Technologies, Load balancing and Virtualization, Understanding Hypervisors; Capacity Planning: Defining Baseline and Metrics, Baseline measurements, System metrics, Load testing, Resource ceilings, Server and instance types, Network Capacity, Scaling 08 Hrs

UNIT-4 Understanding Service Oriented Architecture: Introducing Service Oriented Architecture, Event-driven SOA or SOA 2.0, The Enterprise Service Bus, Service catalogs, Defining SOA Communications, Business Process Execution Language, Business process modeling, Managing and Monitoring SOA, SOA management tools, SOA security, The Open Cloud Consortium, Relating SOA and Cloud Computing 08 Hrs

UNIT-5 Understanding Cloud Security: Securing the Cloud, the security boundary, Security service boundary, Security mapping, Securing Data, Brokered cloud storage access, Storage location and tenancy, Encryption, Auditing and compliance, Establishing Identity and Presence, Identity protocol standards, Windows Azure identity standards 07 Hrs

Dept. of CSE, SIT, Tumakuru 26 Applicable for the academic year 2020-21 Batch: 2017

TEXT BOOK: “Cloud Computing Bible”, Wiley Publishing Inc. 2011 (free 1 Barrie Sosinsky e-book available).

REFERENCES: David S Cloud Computing and SOA Convergence in Your 1 Linthicum Enterprise: A Step-by-Step Guide (free e-book available)

Kai Hwang “Distributed and Cloud Computing – From Parallel Processing to Geoffrey C. Fox 2 the Internet of Things”, Morgan Kaufman Publishers, 2012. Jack J. Dongarra, Enterprise Cloud Computing Technology Architecture 3 Gautam Shroff Applications (free e-book available) Toby Velte Cloud Computing, A Practical Approach (free e-book available) 4 Anthony Velte Robert Elsenpeter

Course Outcomes: After the completion of this course, students will be able to:

1 Apply the key dimensions of Cloud Computing and characteristics. 2 Analyze and infer the benefits and drawbacks of Cloud computing. 3 Analyze and Apply the various types of virtualization and capacity planning metrics to Clouds. 4 Identify the uses of different Cloud Service. 5 Apply the SOA, Cloud Security and Identity Management knowledge to various challenges of Cloud Computing.

Dept. of CSE, SIT, Tumakuru 27 Applicable for the academic year 2020-21 Batch: 2017

DISTRIBUTED OPERATING SYSTEM Contact Hours/ Week : 3 (Lecture) Credits : 3 Total Lecture Hours :39 CIE Marks : 50 Sub. Code : CSPE09 SEE Marks : 50 UNIT-1 Fundamentals: What is Distributed Computing Systems?, Distributed Computing System Models, What is Distributed Operating System?, Issues in Designing a Distributed Operating System, Introduction to Distributed Computing Environment(DCE). 07 Hrs

UNIT- 2 Message Passing: Desirable Issues of s Good Message Passing, Issues in IPC by Message Passing, Synchronization, Buffering, Multidatagram Messages, Encoding and Decoding of Message Data, Process Addressing, Failure Handling, Group Communication. 08 Hrs

UNIT-3 Remote Procedure Calls: The RPC Model, Transparency of RPC, Implementing RPC Mechanism, Stub Generation, RPC Messages, Marshaling Arguments and Results. Server Management, Parameter - Passing Semantics, Call semantics, Communication Protocols for RPCs, Complicated RPCs, Client-Server Binding. 07 Hrs

UNIT-4 Synchronization: Clock Synchronization, Centralized and Distributed clock synchronization algorithms. Event Ordering, Mutual Exclusion, Dead Lock, Election Algorithms. 09 Hrs

UNIT-5 Distributed Shared Memory: General Architecture of DSM Systems, Design and Implementation Issues of DSM. Granularity, Structure of Shared Memory Space, Consistency Models, Replacement Strategy, Thrashing

Resource Management: Desirable Features of a Good Global Scheduling Algorithm, Task Assignment Approach. Distributed File Systems: Desirable Features of a Good Distributed File System, File models. 08 Hrs TEXT BOOK: Distributed Operating System: Concepts and Design, , 1997, PHI. programming, A Simple Assembly Scheme and Pass Structure of 1 Pradeep. K. Sinha Assemblers.[Chapter 1: 1.1, 1.3, 1.5-1.7, Chapter 3: 3.2-3.10, Chapter 4: 4.2-4.13, Chapter 5: 5.2 -5.8,Chapter 6: 6.2-6.6, Chapter 7: 7.2- 7.3, Chapter 9: 9.2- 9.3].

REFERENCE BOOK: 1 Andrew S. Tanenbaum ‘Distributed Operating System’, Pearson Education, 2002

Dept. of CSE, SIT, Tumakuru 28 Applicable for the academic year 2020-21 Batch: 2017

SYSTEM SIMULATION AND MODELING

Contact Hours/ Week : 3 + 0 (Lecture + Tutorial) Credits : 3.0 Total Lecture Hours : 39 CIE Marks : 50 Sub. Code : CSPE10 SEE Marks : 100 UNIT- 1 Introduction to simulation: When simulation is the appropriate tool and when it is not appropriate; Advantages and disadvantages of Simulation; Areas of application; Systems and system environment; Components of a system; Discrete and continuous systems; Model of a system; Types of Models; Discrete-Event System Simulation; Steps in a Simulation Study. Simulation examples: Simulation of queuing systems. 08 Hrs UNIT- 2 General Principles and Queuing Models : Concepts in Discrete-Event Simulation: The Event-Scheduling / Time-Advance Algorithm. Characteristics of queuing systems: The Calling Population, System Capacity, The Arrival Process, Queue Behavior and Discipline, Service Times and Mechanism; Queuing notation. 08 Hrs UNIT- 3 Simulation Software and Random-Number Generation : History of simulation software; selection of simulation software; An example simulation, ,roperties of random numbers; Generation of pseudo-random numbers; Techniques for ,generating random numbers, Linear Congruential Method, Combined Linear Congruential generators ; Tests for Random Numbers, Frequency tests: Kolmogrov-Smirnov test and Chi- Square test. 08 Hrs UNIT- 4 Verification and Validation, Output Analysis for a single model : Model building, Verification and Validation; Verification of Simulation Models, Calibration and Validation of Models, Validation of Model Assumptions.Types of simulation with respect to output analysis,Output analysis for steady-state simulations.

UNIT- 5 Simulation of Computer Systems Introduction, Simulation Tools: Process Orientation, Event Orientation; CPU Simulation, Memory Simulation. 07 Hrs

TEXT BOOK: Jerry Banks, John S. Carson Discrete-Event System Simulation, 4th Edition, Pearson 1 II, Barry L. Nelson, David Education, 2007. M. Nicol

REFERENCE BOOKS: Lawrence M. Leemis, Discrete – Event Simulation: A First Course, Pearson / 1 Stephen K. Park Prentice-Hall, 2006. 2 Averill M. Law Simulation Modeling and Analysis,4th Edition, TMH, 2007

Dept. of CSE, SIT, Tumakuru 29 Applicable for the academic year 2020-21 Batch: 2017

FUZZY LOGIC

Contact Hours/ Week : 3 + 0 (Lecture + Tutorial) Credits : 3.0 Total Lecture Hours : 39 CIE Marks : 50 Sub. Code : CSPE11 SEE Marks : 100 UNIT- 1 INTRODUCTION, CLASSICAL SETS AND FUZZY SETS: Background, Uncertainty and Imprecision, Statistics and Random Processes, Uncertainty in Information, Fuzzy Sets and Membership, Chance versus Ambiguity. Classical Sets - Operations on Classical Sets, Properties of Classical (Crisp) Sets, Mapping of Classical Sets to Functions. Fuzzy Sets - Fuzzy Set operations, Properties of Fuzzy Sets. Sets as Points in Hypercubes. 8 Hrs

UNIT-2 CLASSICAL RELATIONS AND FUZZY RELATIONS: Cartesian Product, Crisp Relations - Cardinality of Crisp Relations, Operations on Crisp Relations, Properties of Crisp Relations, Composition. Fuzzy Relations - Cardinality of Fuzzy Relations, Operations on Fuzzy Relations, Properties of Fuzzy Relations, Fuzzy Cartesian Product and Composition, Non-interactive Fuzzy Sets. Tolerance and Equivalence Relations - Crisp Equivalence Relation, Crisp Tolerance Relation, Fuzzy Tolerance and Equivalence Relations. Value Assignments - Cosine Amplitude, Max-min Method, Other Similarity methods. 7 Hrs

UNIT- 3 MEMBERSHIP FUNCTIONS: Features of the Membership Function, Standard Forms and Boundaries, Fuzzification, Membership Value Assignments – Intuition, Inference, Rank Ordering, Angular Fuzzy Sets, Neural Networks, Genetic Algorithms, Inductive Reasoning. 7 Hrs UNIT-4 FUZZY-TO-CRISP CONVERSIONS, FUZZY ARITHMETIC: Lambda-Cuts for Fuzzy Sets, Lambda-Cuts for Fuzzy Relations, Defuzzification Methods. Extension Principle - Crisp Functions, Mapping and Relations, Functions of fuzzy Sets – Extension Principle, Fuzzy Transform (Mapping), Practical Considerations. Fuzzy Numbers Interval Analysis in Arithmetic, Approximate Methods of Extension - Vertex method, DSW Algorithm, Restricted DSW Algorithm, Comparisons. Fuzzy Vectors. 8 Hrs

UNIT-5 CLASSICAL LOGIC AND FUZZY LOGIC: Classical Predicate Logic – Tautologies, Contradictions, Equivalence, Exclusive Or and Exclusive Nor, Logical Proofs, Deductive Inferences. Fuzzy Logic, Approximate Reasoning, Fuzzy Tautologies, Contradictions, Equivalence and Logical Proofs, Other forms of the Implication Operation, Other forms of the Composition Operation. FUZZY RULE- BASED SYSTEMS: Natural Language, Linguistic Hedges, Rule-Based Systems - Canonical Rule Forms, Decomposition of Compound Rules, Likelihood and Truth Qualification, Aggregation of FR. Graphical Techniques of Inference. 9 Hrs

TEXT BOOK: Fuzzy Logic with Engineering Applications, 1 Timothy J. Ross, McGraw- HHill 1997. REFERENCE BOOK: Neural Networks and Fuzzy systems: A 1 B Kosko, Prentice Hall Dynamical System Approach, 1991. Dept. of CSE, SIT, Tumakuru 30 Applicable for the academic year 2020-21 Batch: 2017

WIRELESS SENSOR NETWORKS

Contact Hours/ Week : 3 + 0 (Lecture + Tutorial) Credits : 3.0 Total Lecture Hours : 39 CIE Marks : 50 Sub. Code : CSPE12 SEE Marks : 100

UNIT- 1 Introduction: The vision of Ambient Intelligence, Application examples, Types of applications, Challenges for WSNs, Why are sensor networks different?, Enabling technologies Single node architecture, Hardware components 7 Hrs. Sections: 1.1 to 1.6, 2.1.1, 2.1.2, 2.1.3, 2.1.4 (except some examples of radio transceivers), 2.1.5, 2.1.6.

UNIT- 2 FUNDAMENTALS OF WSN ARCHITECTURE: Operating systems and execution environments, Network architecture, Sensor network scenarios, Optimization goals & figures of merit, Gateway concepts. 7 Hrs. Sections: 2.3.1, 2.3.2 , 2.3.3, 2.3.4, 2.3.5, 3.1, 3.2 ,3,5

UNIT- 3 LOCALISATION AND POSITIONING: Properties of localization and positioning procedures, Possible approaches, Mathematical basics for the lateration problem, Single- hop localization, Positioning in multihop environments, Impact of anchor placement Sections: 9.1 to 9.6 8 Hrs.

UNIT- 4 ROUTING PROTOCOLS: Routing Protocols: Faces of forwarding and routing, Gossiping and agent-based unicast forwarding, Energy-efficient unicast, Broadcast and multicast, Geographic Routing 8 Hrs. Sections:1 1.1, 1 1.2 , 1 1.3.1, 11.3.4, 11.4.1 to 11.4.4, 11.5

UNIT- 5 TRANSPORT LAYER AND QUALITY OF SERVICE: The transport layer and QoS in wireless sensor networks, Reliable data transport, Block delivery, Congestion control and rate control. 9 Hrs. Sections: 13.1 , 13.3, 13.5, 13.6

TEXT BOOKS: 1. Holger Karl “Protocols and Architectures for Wireless Sensor Andreas Willig Networks” John Wiley & Sons, Ltd

REFERENCE BOOKS: 1. Feng Zhao Wireless Sensor Networks – An Information Processing Leonidas Guibas Approach, Elsevier, 2004 2. Edgar H. Callaway Wireless Sensor Networks Architectures and Protocols Auerbach Publications 2004

Dept. of CSE, SIT, Tumakuru 31 Applicable for the academic year 2020-21 Batch: 2017

Course Outcomes: After the completion of this course, students will be able to:

Apply the knowledge of the basic Computer Network operational 1 methodologies onto the WSN paradigm. Adequately learn and demonstrate how the architecture of the WSNs differ 2 from the Computer Network Analyse the various methods of Localization and Positioning with respect to 3 nodes in the WSN application 4 Apply the knowledge of Routing protocols to fit the WSNs paradigm. Correlate the QoS and Transport layer protocols of Computer Network with 5 the requirements of WSNs paradigm.

Dept. of CSE, SIT, Tumakuru 32 Applicable for the academic year 2020-21 Batch: 2017

ADVANCED COMPUTER ARCHITECTURE

Contact Hours/ Week : 3 Credits : 3.0 Total Lecture Hours : 39 CIE Marks : 50 Sub. Code : CSPE13 SEE Marks : 50 UNIT - 1 Parallel Computer Models The State of Computing, Computer Development Milestones, Elements of Modern Computers, Evolution of Computer Architecture, System Attributes to Performance Multiprocessors and Multicomputer Shared –Memory Multiprocessors, Distributed Memory Multiprocessors, A Taxonomy of MIMD Computers, Multi vector and SIMD computers, Vector Supercomputers, SIMD Supercomputers 6 Hrs UNIT -2 Program and Network Properties: Conditions of Parallelism, Data and Resource Dependences, Hardware and Software Parallelism, the Role of Compilers, Program Partitioning and Scheduling, Grain Sizes and Latency, Grain Packing and Scheduling. Program flow Mechanisms, Control Flow Versus Data Flow, Demand-Driven Mechanisms Comparisons of Flow Mechanisms, System Interconnect Architectures. 12 Hrs UNIT-3 Pipelining and Superscalar Techniques Processor: Superscalar and Vector Processors. Linear Pipeline Processors, Asynchronous and Synchronous Models, Clocking and Timing control, Speed up, Efficiency and Throughput, Non-linear Pipeline Processors, Reservation and Latency Analysis, Collision-Free Scheduling, 8 Hrs UNIT-4 Instruction Pipeline Design. Mechanism for Instruction Pipelining, Arithmetic Pipeline Design, Computer Arithmetic Principles, Static Arithmetic Pipeline, Cache Coherence and Synchronization Mechanisms, The Cache Coherence, Problem, Snoopy Bus Protocol. 7 Hrs

UNIT–V Multiprocessors and Multi-computers Directory-based protocols, Hardware Synchronization Mechanisms, Message Passing Schemes, Message Routing Schemes, Deadlock and Virtual Channels, Flow Control Strategies, Parallel Models. 6 Hrs

TEXT BOOK:

1 Kai Advanced Computer Architecture Parallelism, Scalability: Hwang Programmability, Tata Mc Grawhill, 2003. Ch 1.1 to 1.3, Ch 2.1 to 2.4, : Ch 4.2, Ch 6.1 to 6.4, 6.4.1,6.4.2, Ch 7.2, 7.4 REFERENCE BOOKS:

1 John P Hayes Computer Architecture and Organization, 3rd Edition, McGrawHill, 1998 2 V Rajaraman, C Siva Parallel Computers – Architecture and Programming, Ram Murthy PHI,2000 3 Dezso Sima, Terence Advanced Computer Architectures – A design space Fountain, Peter Kacsuk approach, Pearson Education 1997

Dept. of CSE, SIT, Tumakuru 33 Applicable for the academic year 2020-21 Batch: 2017

WEB 2.0 & RICH INTERNET APPLICATION

Contact Hours/ Week : 3 Credits : 3.0 Total Lecture Hours : 39 CIE Marks : 50 Sub. Code : CSPE14 SEE Marks : 50 UNIT – 1 WEB SERVICES: What is Web 2.0?, Folksonomies and Web 2.0, Software as a Service (SaaS), Data and Web 2.0, Convergence, Iterative development, Rich User experience, Multiple Delivery Channels, Social Networking. WEB SERVICES AND BUILDING RICH INTERNET APPLICATIONS WITH AJAX-1: SOAP, RPC Style SOAP, Document style SOAP, WSDL, REST services, JSON format, What is JSON? Array literals, Object literals, Mixing literals, JSON Syntax, JSON Encoding and Decoding, JSON versus XML. 09 Hrs UNIT - 2 BUILDING RICH INTERNET APPLICATIONS WITH AJAX-1: Building Rich Internet Applications with AJAX: Limitations of Classic Web application model, AJAX principles, Technologies behind AJAX, Examples of usage of AJAX, Dynamic web applications through Hidden frames for both GET and POST methods. BUILDING RICH INTERNET APPLICATIONS WITH AJAX-2: Frames, Asynchronous communication and AJAX application model, XMLHTTP Object – properties and methods, handling different browser implementations of XMLHTTP 08 Hrs UNIT -3 AJAX-2: The same origin policy, Cache control, AJAX Patterns (Only algorithms – examples not required): Predictive fetch pattern, Submission throttling pattern, Periodic refresh, Multi stage download, Fall back patterns. BUILDING RICH INTERNET APPLICATIONS WITH FLEX - 1: Flash player, Flex framework, MXML and Action script, Working with Data services, Understanding differences between HTML and Flex applications, Understanding how Flex applications work, Understanding Flex and Flash authoring, MXML language, a simple example. 08 Hrs

UNIT - 4 BUILDING RICH INTERNET APPLICATIONS WITH FLEX - 2: Using Actionscript, MXML and Actionscript correlations. Understanding Actionscript 3.0 language syntax: Language overview, Objects and Classes, Packages and namespaces, Variables & scope of variables, case sensitivity and general syntax rules, Operators, Conditional, Looping, Functions, Nested functions, Functions as Objects, Function scope, OO Programming in Actionscript: Classes, Interfaces, Inheritance, Working with String objects, Working with Arrays, Error handling in Actionscript: Try/Catch, Working with XML. 07 Hrs

Dept. of CSE, SIT, Tumakuru 34 Applicable for the academic year 2020-21 Batch: 2017

UNIT - 5 BUILDING RICH INTERNET APPLICATIONS WITH FLEX - 3: Framework fundamentals, Understanding application life cycle, Differentiating between Flash player and Framework, Bootstrapping Flex applications, Loading one flex application in to another, Understanding application domains, Understanding the preloader. Managing layout, Flex layout overview, Working with children, Container types, Layout rules, Padding, Borders and gaps, Nesting containers, Making fluid interfaces. 07 Hrs

TEXT BOOKS: 1. Professional AJAX – Nicholas C Zakas et al,Wrox publications, 2006. 2. Programming Flex 2 – Chafic Kazoun, O’Reilly publications, 2007. 3. Mashups – Francis Shanahan, Wrox, 2007.

REFERENCE BOOKS: 1. Ajax: The Complete Reference – Thomas A. Powel, McGraw Hill, 2008. 2. Unleashing Web 2.0: From Concepts to Creativity – Gottfried Vossen, Stephan Hagemann, Elsevier, 2007. 3. Essential Actionscript 3.0 – Colin Moock, O’Reilly Publications, 2007. 4. Ajax Bible - Steven Holzner, Wiley India, 2007. 5. A Web 2.0 Primer Pragmatic Ajax – Justin Gehtland et al, SPD Publications, 2006. 6. Professional Web 2.0 Programming – Eric Van derVlist et al, Wiley India, 2007.

Dept. of CSE, SIT, Tumakuru 35 Applicable for the academic year 2020-21 Batch: 2017

SOFTWARE ARCHITECTURE

Contact Hours/ Week : 3 Credits : 3.0 Total Lecture Hours : 39 CIE Marks : 50 Sub. Code : CSPE15 SEE Marks : 50 UNIT 1 Introduction: The Architecture Business Cycle: Where do architectures come from? Software processes and the architecture business cycle; What makes a “good” architecture? What software architecture is and what it is not; Other points of view; Architectural patterns, reference models and reference architectures; Importance of software architecture; Architectural structures and views. 6 Hrs UNIT 2 Quality: Functionality and architecture; Architecture and quality attributes; System quality attributes; Quality attribute scenarios in practice; Other system quality attributes; Business qualities; Architecture qualities. Achieving Quality: Introducing tactics; Availability tactics; Modifiability tactics; Performance tactics; Security tactics; Testability tactics; Usability tactics; Relationship of tactics to architectural patterns; Architectural patterns and styles. 9 Hrs UNIT – 3 Architectural patterns-1: Introduction; from mud to structure: Layers, Pipes and Filters, Distributed Systems: Broker; Interactive Systems: MVC, Presentation-Abstraction-Control. 8 Hrs UNIT - 4 Architectural patterns-2: Adaptable Systems: Microkernel. Some design patterns: Structural decomposition: Whole – Part; Organization of work: Master – Slave; Access Control: Proxy. 8 Hrs UNIT - 5 Designing and documenting software architecture: Architecture in the life cycle; designing the architecture; Forming the team structure; Creating a skeletal system. Uses of architectural documentation; Views; choosing the relevant views; Documenting a view; Documentation across views. 8 Hrs

TEXT BOOKS: 1. Software Architecture in Practice – Len Bass, Paul Clements, Rick Kazman, 2nd Edition, Pearson Education, 2003. 2. Pattern-Oriented Software Architecture, A System of Patterns - Volume 1 – Frank Buschmann, Regine Meunier, Hans Rohnert, Peter Sommerlad, Michael Stal,, John Wiley and Sons, 2006. 3. Mary Shaw and David Garlan: Software Architecture- Perspectives on an Emerging Discipline, Prentice-Hall of India, 2007.

REFERENCE BOOK: Design Patterns- Elements of Reusable Object-Oriented Software – E. Gamma, R. Helm, R. Johnson, J. Vlissides:, Addison-Wesley, 1995. Web site for Patterns: http://www.hillside.net/patterns/

Dept. of CSE, SIT, Tumakuru 36 Applicable for the academic year 2020-21 Batch: 2017

COMPUTER SYSTEMS & PERFORMANCE ANALYSIS

Contact Hours/ Week : 3 Credits : 3.0 Total Lecture Hours : 39 CIE Marks : 50 Sub. Code : CSPE16 SEE Marks : 50

UNIT -1 1. Introduction: The art of Performance Evaluation; Common Mistakes in Performance Evaluation, A Systematic Approach to Performance Evaluation, Selecting an Evaluation Technique, Selecting Performance Metrics, Commonly used Performance Metrics, Utility Classification of Performance Metrics, Setting Performance Requirements. 8 Hrs

UNIT 2 2. Workloads: Workload Selection and Characterization: Types of Work loads, addition instructions, Instruction mixes, Kernels; Synthetic programs, Application benchmarks, Popular benchmarks. Work load Selection: Services exercised, level of detail; Representativeness; Timeliness, Other considerations in workload selection. Work load characterization Techniques: Terminology; Averaging, Specifying dispersion, Single Parameter Histograms, Multi Parameter Histograms, Principle Component Analysis, Markov Models, Clustering. 8 Hrs UNIT 3 3. Monitors: Program Execution Monitors and Accounting Logs: Monitors: Terminology and classification; Software and hardware monitors, Software versus hardware monitors, Firmware and hybrid monitors, Distributed System Monitors, Program Execution Monitors and Accounting Logs, Program Execution Monitors, Techniques for Improving Program Performance, Accounting Logs, Analysis and Interpretation of Accounting log data, Using accounting logs to answer commonly asked questions. 8 Hrs

UNIT 4 4. Capacity Planning and Benchmarking: Steps in capacity planning and management; Problems in Capacity Planning; Common Mistakes in Benchmarking; Benchmarking Games; Load Drivers; Remote-Terminal Emulation; Components of an RTE; Limitations of RTEs. 8 Hrs UNIT 5 5. Experimental Design and Analysis: Introduction: Terminology, Common mistakes in experiments, Types of experimental designs, 2k Factorial Designs, Concepts, Computation of effects, Sign table method for computing effects; Allocation of variance; General 2k Factorial Designs, General full factorial designs with k factors: Model, Analysis of a General Design, Informal Methods. 7 Hrs

TEXT BOOK: Raj Jain: The Art of Computer Systems Analysis, John Wiley and Sons, 2007.

REFERENCE BOOK: Paul J Fortier, Howard E Michel: computer Systems Performance Evaluation and prediction, Elsevier, 2003

Dept. of CSE, SIT, Tumakuru 37 Applicable for the academic year 2020-21 Batch: 2017

STORAGE AREA NETWORKS

Contact Hours/ Week : 3 Credits : 3.0 Total Lecture Hours : 39 CIE Marks : 50 Sub. Code : CSPE17 SEE Marks : 50

UNIT-1 Introduction: Server Centric IT Architecture and its Limitations; Storage – Centric IT Architecture and its advantages; Case study: Replacing a server with Storage Networks;.

Intelligent disk subsystems - 1: Architecture of Intelligent Disk Subsystems; Hard disks and Internal I/O Channels, JBOD, Storage virtualization using RAID and different RAID levels. 9 Hrs UNIT-2 Caching: Acceleration of Hard Disk Access I/O Techniques: Intelligent disk subsystems; Availability of disk subsystems. The Physical I/O path from the CPU to the Storage System; SCSI. Fibre Channel Protocol Stack; Fibre Channel SAN; 7 Hrs UNIT -3 IP Storage: IP storage standarads, TCP/IP and ethernet as an I/P technology, Migration from SCSI and FC to IP strorage Network attached storage: The NAS Architecture, The NAS hardware Architecture, The NAS Software Architecture, Network connectivity, NAS as a storage system. File system: Local File Systems; Network file Systems and file servers; Shared Disk file systems; Comparison of fibre Channel and NAS. 8 Hrs

UNIT-4 Storage virtualization: Definition of Storage virtualization; Implementation Considerations; Storage virtualization on Block or file level; Storage virtualization on various levels of the storage Network; Symmetric and Asymmetric storage virtualization in the Network Application of Storage Networks: Definition of the term ‘storage networks’, storage sharing. 7 Hrs UNIT-5 Application of Storage Networks (continued): availability of Data, adaptability and scalability of IT systems Network Back-up: General conditions for Back-up, Network Back-up Services, Server components, Backup clients, performance gains and bottlenecks of network back-up, Limited opportunities for increased performance, Next generation Back-up, Back-up of file systems and databases. 8 Hrs.

Dept. of CSE, SIT, Tumakuru 38 Applicable for the academic year 2020-21 Batch: 2017

TEXT BOOK: Storage Networks Explained – Ulf Troppens, Rainer Erkens and Wolfgang Muller, John Wiley & Sons, 2009.

REFERENCE BOOKS: 1. Storage Networks: The Complete Reference – Robert Spalding, Tata McGraw Hill, 2003. 2. Storage Area Network Essentials: A Complete Guide to understanding and Implementing SANs – Richard Barker and Paul Massiglia, John Wiley India, 2002. 3. 2.Storage Networking Fundamentals Marc Farley, Cisco Press, 2005.

Course Outcomes: After the completion of the course, students will be able to:

1 Analyze the tradeoffs between Server Centric IT architecture and Storage Centric architecture, SAN and NAS architectures. 2 Understand the knowledge of IT Architectures, Disk Subsystems and apply the different RAID levels to address performance issues of SAN. 3 Analyze the different I/O techniques to realize the data exchange between computer and storage devices. 4 Identify the different protocols for the transmission of storage data traffic, Recognize the working methodologies of SAN and NAS and their comparisons. 5 Analyze the impact of Storage virtualization on various levels and Identify the different network back up services of the storage Network.

Dept. of CSE, SIT, Tumakuru 39 Applicable for the academic year 2020-21 Batch: 2017

COMMUNICATION PROTOCOL ENGINEERING

Contact Hours/ Week : 3 + 0 (Lecture + Tutorial) Credits : 3.0 Total Lecture Hours : 39 CIE Marks : 50 Sub. Code : CSPE19 SEE Marks : 100 UNIT-1 Introduction: Communication model, Communication Software, Communication Subsystems, Communication Protocol Definition/Representation, Formal and Informal Protocol Development Methods, Protocol Engineering Phases Protocol Specification: Components of specification, Service specification, Communication Service Specification Protocol entity specification: Sender, Receiver and Channel specification, Interface specifications. 08 Hrs. UNIT-2 Protocol Specification Language (SDL): Salient Features. Communication System Description using SDL, Structure of SDL. Data types and communication paths, Examples of SDL based Protocol Specifications: Question and answer protocol, X-on-X-off protocol, Alternating bit protocol, Sliding window protocol specification, TCP protocol specification. 08 Hrs. UNIT -3 Protocol Verification / Validation: Protocol Verification using FSM, ABP Verification, Protocol Design Errors, Deadlocks, Unspecified Reception, Non-executable Interactions, State Ambiguities, Protocol Validation Approaches: Perturbation Technique, Reachability Analysis, Fair Reachability Graphs, Process Algebra based Validation. 8 Hrs.

UNIT -4 Protocol Conformance Testing: Conformance Testing Methodology and Framework, Local and Distributed Conformance Test Architectures, Test Sequence Generation Methods: T, U, D and W methods, Distributed Architecture by Local Methods, Synchronizable Test Sequence, Conformance testing with Tree and Tabular Combined Notation (TTCN). 8 Hrs.

UNIT-5 Protocol Performance Testing: Testing Multimedia Systems, quality of service test architecture(QOS), Performance Test methods, SDL Based Performance Testing of TCP, OSPF. 7 Hrs.

TEXT BOOK: Pallapa Venkataram and Sunilkumar S. Manvi: Communication Protocol Engineering, PHI, 2004. REFERENCE BOOK: Mohammed G. Gouda: Elements of Protocol Design, Wiley Student Edition, 2004.

Dept. of CSE, SIT, Tumakuru 40 Applicable for the academic year 2020-21 Batch: 2017

AD HOC WIRELESS NETWORKS

Contact Hours/ Week : 3 + 0 (Lecture + Tutorial) Credits : 3.0 Total Lecture Hours : 39 CIE Marks : 50 Total Tutorial Hours : 00 SEE Marks : 50 Sub. Code : CSPE20 UNIT–1 Introduction to Wireless Communication Technology: Fundamentals, The Electromagnetic Spectrum, Radio Propagation Mechanisms, Characteristics of the Wireless Channel. Wireless LANs: Fundamentals of WLANs, IEEE 802.11 standard. Wireless WANs: The Cellular Concept, Cellular Architecture, The First-Generation cellular Systems, The Second-Generation cellular Systems, The Third-Generation cellular Systems. Wireless Internet: What is Wireless Internet? Mobile IP. 08 Hrs

UNIT-2 Ad hoc Networks: Introduction, Issues in Ad hoc wireless networks, Ad hoc wireless internet. MAC – 1: MAC Protocols for Ad hoc wireless Networks: Introduction, Issues in designing a MAC protocol for Ad hoc wireless Networks, Design goals of a MAC protocol for Ad hoc wireless Networks, Classification of MAC protocols, Contention based protocols, Contention based protocols with reservation mechanisms. 09 Hrs

UNIT-3 Routing protocols for Ad hoc wireless Networks: Introduction, Issues in designing a routing protocol for Ad hoc wireless Networks, Classification of routing protocols, Table driven routing protocols, On-demand routing protocols, Hybrid routing protocols. 08 Hrs

UNIT–4 Transport layer protocols for Ad hoc wireless Networks: Introduction, Issues in designing a transport layer protocol for Ad hoc wireless Networks, Design goals of a transport layer protocol for Ad hoc wireless Networks, Classification of transport layer solutions, TCP over Ad hoc wireless Networks. Security: Security in wireless Ad hoc wireless Networks, Network security requirements, Issues & challenges in security provisioning, Network security attacks, Key management 07 Hrs UNIT–5 QoS: Quality of service in Ad hoc wireless Networks: Introduction, Issues and challenges in providing QoS in Ad hoc wireless Networks, Classification of QoS solutions, MAC layer solutions, network layer solutions. 07 Hrs

TEXT BOOK: C. Siva Ram Murthy & B. S. Manoj: Ad hoc Wireless Networks, 2nd Edition, Pearson Education, 2005 [ Chapter 1: 1.1, 1.2, 1.3, 1.4. Chapter 2: 2.1, 2.2, 2.3. Chapter 3: 3.1, 3.2, 3.3, 3.4, 3.5, 3.6. Chapter 4: 4.1, 4.2, 4.3. Chapter 5, Chapter 6: 6.1-6.6, Chapter 7: 7.1 – 7.6, Chapter 9: 9.1, 9.2, 9.3, 9.4, 9.5, 9.7, 9.8, 9.9, 9.10, 9.11, Chapter 10: 10.1, 10.2, 10.3, 10.4, 10.5]

REFERENCE BOOKS: 1. Ozan K. Tonguz and Gianguigi Ferrari: Ad hoc Wireless Networks, John Wiley, 2007. 2. Xiuzhen Cheng, Xiao Hung, Ding-Zhu Du: Ad hoc Wireless Networking, Kluwer Academic Publishers, 2004. 3. C.K. Toh: Adhoc Mobile Wireless Networks- Protocols and Systems, Pearson Education, 2002.

Dept. of CSE, SIT, Tumakuru 41 Applicable for the academic year 2020-21 Batch: 2017

MULTI-CORE ARCHITECTURE AND PROGRAMMING Contact Hours/ Week : 3 + 0 (Lecture + Tutorial) Credits : 3.0 Total Lecture Hours : 39 CIE Marks : 50 Sub. Code : CSPE21 SEE Marks : 50 UNIT–1 Introduction The power and potential of parallelism, Examining sequential and parallel programs, Parallelism using multiple instruction streams, The Goals: Scalability and performance portability, Balancing machine specifics with portability, A look at six parallel computers: Chip multiprocessors, Symmetric multiprocessor architectures, Heterogeneous chip designs, Clusters, Supercomputers, Observations from the six parallel computers. 10 Hrs UNIT–2 Examples of Multi-Core Architectures Introduction to Intel Architecture, How an Intel Architecture System works, Basic Components of the Intel Core 2 Duo Processor: The CPU, Memory Controller, I/O Controller; Intel Core i7: Architecture, The Intel Core i7 Processor, Intel Quick Path Interconnect, The SCH; Intel Atom Architecture. 125 Introduction to Texas Instruments’ Multi-Core Multilayer SoC architecture for communications, infrastructure equipment. 08 Hrs UNIT–3 Parallel Algorithm Design Introduction, The Task / Channel model, Foster’s design methodology, Examples: Boundary value problem, Finding the maximum, The n-Body problem, Adding data input 08 Hrs UNIT–4 Parallel Programming – 1 (Using OpenMP) Designing for threads: Task decomposition, Data decomposition, Data flow decomposition, Implications of different decompositions; Challenges in decomposition, Parallel programming patters, A motivating problem: Error diffusion. Threading and Parallel Programming Constructs 07 Hrs UNIT–5 Solutions to Common Parallel Programming Problems Too many threads, Data races, deadlocks, and live locks, Heavily contended locks, Non- blocking algorithms, Thread-safe functions and libraries, Memory issues, Cache-related issues, Avoiding pipeline stalls, Data organization for high performance 06 Hrs.

TEXT BOOKS: 1. Calvin Lin, Lawrence Snyder: Principles of Parallel Programming, Pearson Education, 2009. (Listed topics only from Chapters 1, 2, 3) 2. Michael J. Quinn: Parallel Programming in C with MPI and OpenMP, Tata McGraw Hill, 2004. (Listed topics only from Chapters 3, 17) 3. Shameem Akhter, Jason Roberts: Multi-Core Programming, Increasing Performance through Software Multithreading, Intel Press, 2006. (Listed topics only from Chapters 3, 4, 7, 9, 10) 4. Web resources for Example Architectures of INTEL and Texas Instruments: http://download.intel.com/design/intarch/papers/321087.pdf ; http://focus.ti.com/lit/wp/spry133/spry133.pdf

REFERENCE BOOKS: 1. Introduction to Parallel Computing – Ananth Grama et. al., Pearson Education, 2009. 2. Reinders : Intel Threading Building Blocks, O’reilly – 2005 3. David Culler et. al.: Parallel Computer Architecture: A Hardware/Software Approach, Elsevier, 2006. 4. Richard Gerber, Aart J.C. Bik, Kevin B. Smith, Xinmin Tian: Software Optimization Cookbook, High-Performance Recipes for IA-32 Platforms, 2nd Edition, Intel Press, 2006

Dept. of CSE, SIT, Tumakuru 42 Applicable for the academic year 2020-21 Batch: 2017

ADVANCED ALGORITHMS Contact Hours/ Week : 3 + 0 (Lecture + Tutorial) Credits : 3.0 Total Lecture Hours : 39 CIE Marks : 50 Total Tutorial Hours : 00 SEE Marks : 50 Sub. Code : CSPE22 UNIT–1 Review of Analysis Techniques: Growth of Functions: Asymptotic notations; Standard notations and common functions; Recurrences and Solution of Recurrence equations- The substitution method, The recursion – tree method, The master method; Amortized Analysis: Aggregate analysis, Accounting and Potential Methods. 08 Hrs UNIT–2 Red-Black Trees: Properties of red-black trees, Rotations, Insertion, Deletion. B- Trees: Definition of B-trees, Basic operations on B-trees, deleting a key from a B-tree. 08 Hrs UNIT–3 Binomial Heaps : Binomial trees and binomial heaps, Operations on binomial heaps. Fibonacci Heaps : Structure of Fibonacci heaps, Mergeable-heap operations, Decreasing a key and deleting a node. 08 Hrs UNIT–IV Graph Algorithms: Bellman - Ford Algorithm; Single source shortest paths in a directed acyclic graphs; Johnson’s Algorithm for sparse graphs; Flow networks and Ford-Fulkerson method; Maximum bipartite matching. 07 Hrs UNIT–V Matrix Operations: Properties of Matrices, Strassen’s algorithm for matrix multiplication, Solving systems of Linear Equations. Polynomials and the FFT: Representation of polynomials; The DFT and FFT; Efficient implementation of FFT. String-Matching Algorithms: Naive string Matching; Rabin - Karp algorithm; String matching with finite automata. 08 Hrs

TEXT BOOK: T. H Cormen, C E Leiserson, R L Rivest and C Stein: Introduction to Algorithms, 2nd Edition, Prentice-Hall of India, 2010. UNIT I :Chapter 3; Chapter 4: 4.1, 4.2, 4.3; Chapter 17: 17.1, 17.2, 17.3; UNIT II :Chapter 13: 13.1, 13.2, 13.3, 13.4; Chapter 18; UNIT III :Chapter 19; Chapter 20 : 20.1, 20.1, 20.3; UNIT IV : Chapter 24: 24.1, 24.2; Chapter 25:25.3; Chapter 26: 26.1, 26.2, 26.3; UNIT V : Chapter 28: 28.1, 28.2, 28.3; Chapter 30; Chapter 3.1, 32.2, 32.3; ]

REFERENCE BOOK: Ellis Horowitz, Sartaj Sahni, S.Rajasekharan: Fundamentals of Computer Algorithms, 2nd Edition, Universities press, 2007.

Dept. of CSE, SIT, Tumakuru 43 Applicable for the academic year 2020-21 Batch: 2017

WEB DESIGN TECHNIQUES Contact Hours/ Week : 3 + 0 (Lecture + Tutorial) Credits : 3.0 Total Lecture Hours : 39 CIE Marks : 50 Total Tutorial Hours : 00 SEE Marks : 50 Sub. Code : CSPE23 UNIT - 1 Fundamentals of Web, XHTML – 1: Internet, WWW, Web Browsers, and Web Servers; URLs; MIME; HTTP; Security; The Web Programmers Toolbox. XHTML: Origins and evolution of HTML and XHTML; Basic syntax; Standard XHTML document structure; Basic text markup. XHTML – 2: Images; Hypertext Links; Lists; Tables; Forms; Frames; Syntactic differences between HTML and XHTML. 09 Hrs UNIT – 2 CSS: Introduction; Levels of style sheets; Style specification formats; Selector forms; Property value forms; Font properties; List properties; Color; Alignment of text; The Box model; Background images; The and tags; Conflict resolution. JAVASCRIPT: Overview of Javascript; Object orientation and Javascript; General syntactic characteristics; Primitives, operations, and expressions; Screen output and keyboard input. 08 Hrs UNIT - 3 JAVASCRIPT: Control statements; Object creation and modification; Arrays; Functions; Constructor; Pattern matching using regular expressions; Errors in scripts; Examples. JAVASCRIPT AND HTML DOCUMENTS: The Javascript execution environment; The Document Object Model; Element access in Javascript; Events and event handling; Handling events from the Body elements, Button elements, Text box and Password elements. 08 Hrs

UNIT - 4 XML:Introduction; Syntax; Document structure; Document Type definitions; Namespaces; XML schemas; Displaying raw XML documents; Displaying XML documents with CSS; XSLT style sheets; XML processors; Web services.

JSON: JSON format, What is JSON? Array literals, Object literals, Mixing literals, JSON Syntax, JSON Encoding and Decoding, JSON versus XML. 07 Hrs UNIT - 5 RESTful Web Services– Introduction, Environment Setup, First Application, Resources, Messages, Addressing, Statelessness, caching, security.

CGI PROGRAMMING: The Common Gateway Interface; CGI linkage; Query string format; CGI.pm module; A survey example; Cookies. 07 Hrs

TEXT BOOKS: 1. Programming the World Wide Web – Robert W. Sebesta, 4th Edition, Pearson Education, 2008. 2. Professional AJAX – Nicholas C Zakas et al, Wrox publications, 2006. 3. https://www.tutorialspoint.com/restful/index.htm (REST Web Services topics are referred to this link)

REFERENCE BOOKS: 1. Internet & World Wide Web How to H program – M. Deitel, P.J. Deitel, A. B. Goldberg, 3rd Edition, Pearson Education / PHI, 2004. 2. Web Programming Building Internet Applications – Chris Bates, 3rd Edition, Wiley India, 2006. 3. The Web Warrior Guide to Web Programming – Xue Bai et al, Thomson, 2003.

Dept. of CSE, SIT, Tumakuru 44 Applicable for the academic year 2020-21 Batch: 2017

PARALLEL ALGORITHMS Contact Hours/ Week : 3 + 0 (Lecture + Tutorial) Credits : 3.0 Total Lecture Hours : 39 CIE Marks : 50 Total Tutorial Hours : 00 SEE Marks : 50 Sub. Code : CSPE24

UNIT–1 Introduction: Need for parallel computers, Models of computation, Analyzing parallel algorithms, expressing parallel algorithms. Principles of Parallel Algorithm design: Preliminaries, Decomposition techniques, Characteristics of Tasks and Interactions, Mapping Techniques for Load Balancing, Methods for containing Interaction overheads, Parallel Algorithm models. Dense Matrix algorithms: Matrix vector Multiplication, Matrix multiplication 8 Hrs UNIT–2 Sorting Algorithms: Issues in sorting and searching on Parallel Computers, Bubble Sort and its variants, Quick sort, Bucket and Sample sort, Other Sorting algorithms. Searching Algorithms: Issues in searching, Sequential Search Algorithms, Search overhead factor, Parallel DFS, parallel BFS, Speedup anomalies in Parallel search algorithms. 8 Hrs

UNIT-3 Graph Algorithms: Definitions and Representations, Minimum Spanning Tree: Prim's algorithm, Single Source shortest path algorithms, all pairs shortest path algorithm, Transitive closure, Connected Components in Graph: DFS method,Algorithms for Sparse Graphs, Graph Coloring Algorithm. 8 Hrs UNIT-4 Dynamic Programming: Overview of Dynamic Programming, Serial Monadic DP Formulations, Non-Serial Monadic DP Formulations, Serial Polyadic DP Formulation. 7 Hrs UNIT-5 Open MP: A standard for Directive Based Programming: Programming Model in Open MP, Specifying Concurrent Tasks in OpenMP, Synchronization in OpenMP, Data Handling in OpenMP, OpenMP library functions, Environmental Variables of Open MP, Explicit Thread Versus OpenMP based Programming. 8 Hrs

TEXT BOOKS: 1. Ananth Grama, Anshul Gupta, George Karypis, Vipin Kumar "Introduction to Parallel Computing", Second Edition, Addison Wesley, 2003. 2. S.G.Akl, "The Design and Analysis of Parallel Algorithms", PHI, 1989.

REFERENCE BOOK: 1. F.T.Leighton, "Introduction to Parallel Algorithms and Architectures: Arrays, Trees, Hypercubes", MK Publishers, San Mateo California, 1992.

Dept. of CSE, SIT, Tumakuru 45 Applicable for the academic year 2020-21 Batch: 2017

FUNDAMENTALS OF DIGITAL IMAGE PROCESSING

Contact Hours/ Week : 3 + 0 (Lecture + Tutorial) Credits : 3.0 Total Lecture Hours : 39 CIE Marks : 50 Sub. Code : CSPE25 SEE Marks : 50 UNIT - 1 Introduction: What is digital image processing? Examples of fields that use digital image processing, Fundamental steps in digital image processing, Components of an image processing system, Digital Image Fundamentals: Image sensing and acquisition: Image acquisition using a single sensor, Image acquisition using a sensor strips, Image acquisition using sensor arrays. A simple image formation model. 7 Hrs UNIT - 2 Digital Image Fundamentals: Image sampling and quantization, Basic concepts in sampling and quantization, representing digital images, Spatial and Intensity resolutions. Some basic relationships between pixels: Neighbors of a pixel, Adjacency, Connectivity, Regions and Boundaries, Distance measures. An introduction to the Mathematical tools used in digital image processing: Array versus matrix operations, Linear versus nonlinear operations, Arithmetic operations, Set and Logical operations, Spatial operations, Vector and matrix operations, Image transforms, Probabilistic methods. 9 Hrs

UNIT - 3 Intensity Transformations and spatial filtering: The basics of intensity transformations and spatial filtering. Basic intensity transformation functions: Image negatives, Log transformations, Power-Law (Gamma) transformations, Piecewise-Linear transformation functions. Fundamentals of spatial filtering: The mechanics of spatial filtering, Spatial correlation and convolution, Vector representation of Linear filtering. Image RESTORATION: A model of the image restoration/degradation process. Restoration in the presence of Noise only—Spatial Filtering: Mean Filters. 8 Hrs

UNIT – 4 Color Image Processing: Pseudo color image processing: Intensity Slicing, Intensity to color transformation. Basics of full-color image processing. Image Compression: Fundamentals: Coding redundancy, Spatial and Temporal redundancy, irrelevant information, Measuring image information. Some basic compression methods: Arithmetic coding, LZW coding, symbol-based coding.

MORPHOLOGICAL IMAGE processing: Preliminaries. Erosion and dilation: Erosion, Dilation, Duality. Opening and closing. The Hit-or-Miss Transformation. Some basic morphological algorithms: Boundary Extraction, Hole Filling. 8 Hrs

Dept. of CSE, SIT, Tumakuru 46 Applicable for the academic year 2020-21 Batch: 2017

UNIT–5 IMAGE SEGMENTATION: Fundamentals. Point, Line and Edge detection: Background, Detection of isolated Points, Line detection, Edge Models, Basic Edge detection. Region-Based segmentation: Region growing, Region Splitting and Merging. Segmentation using Morphological Watersheds: Background, Dam construction, Watershed segmentation algorithm.

OBJECT RECOGNITION: Patterns and pattern classes. Recognition based on Decision- Theoretic methods: Matching, Optimum statistical classifiers, Neural networks. 7 Hrs

TEXT BOOK: Rafael C. Gonzales, Richard E. Woods, Digital Image Processing, 3rd Edition, Pearson publications, 2005.

REFERENCE BOOKS: 1. A.K. Jain, Fundamentals of Digital Image Processing, Pearson, 2004. 2. S.Jayaraman, S.Esakkiranjan, T. Veerakumar, Digital Image Processing, Tata McGraw Hill, 2004.

Dept. of CSE, SIT, Tumakuru 47 Applicable for the academic year 2020-21 Batch: 2017

SERVICE ORIENTED ARCHITECTURE

Contact Hours/ Week : 3 + 0 (Lecture + Tutorial) Credits : 3.0 Total Lecture Hours : 39 CIE Marks : 50 Sub. Code : CSPE26 SEE Marks : 50 UNIT-1 INTRODUCTION TO SOA WITH WEB SERVICES: SOA and Business Process Management - Overview of Service-Oriented Architecture - SOA concepts - Service, Governance - Processes - Guidelines - Principles - Methods and Tools - SOA: Business Benefits. 8 Hrs UNIT-2 SOA AND WEB SERVICES: Web services Platform - Service contracts - Service-level data model - Service -level security - Service-Level Communication - SOA and Web services for Integration: Overview - Integration and Interoperability Using XML and Web Services 8 Hrs UNIT–3 SOA AND MULTI-CHANNEL ACCESS: Business Benefits of SOA- SOA for Multi- channel Access Client/Presentation Tier - Channel Access Tier - SOA and Business Process Management: Concepts - Combining BPM, SOA and Web Services - Orchestration and Choreography Specifications - Example of Web Services Composition 8 Hrs UNIT–4 METADATA MANAGEMENT: Simple Approach to Metadata Management - Metadata specifications - Policy - WS-MetadataExchange - Web services security: Core concepts - Summary of challenges, Threats and Remedies - Securing the Communications Layer - Message-Level Security. 8 Hrs UNIT–5 ADVANCED MESSAGING: Advanced Messaging: Concept and technologies - Benefits of Reliable Messaging - Web services reliable Messaging Specifications. Transaction Processing: Impact of Web services on Transactions - Transactions specifications. 7 Hrs

TEXT BOOK: Understanding SOA with Web Services, Eric Newcomer, Greg Lomow, Pearson Education, New Delhi, 2005.

REFERENCE BOOKS: 1. "Understanding Enterprise SOA", Eric Pulier, Hugh Taylor, Dreamtech press, New Delhi, 2005 2. “Enterprise SOA: Designing it for Business Innovation", Dan Woods, Thomas Mattern, Shroff publishers, 2006

Dept. of CSE, SIT, Tumakuru 48 Applicable for the academic year 2020-21 Batch: 2017

MOBILE COMPUTING

Contact Hours/ Week : 3 + 0 (Lecture + Tutorial) Credits : 3.0 Total Lecture Hours : 39 CIE Marks : 50 Sub. Code : CSPE27 SEE Marks : 50

UNIT-1 Introduction: Mobility of Bits and Bytes, Wireless- The Beginning, Mobile Computing, Dialogue Control, Networks, Middleware and Gateways, Application and Services (Contents), Developing Mobile Computing Applications, Security in Mobile Computing. Mobile Computing Architecture: History of Computers, History of Internet, Internet-The Ubiquitous Network, Architecture for Mobile Computing, Three-Tier Architecture, Design Considerations for Mobile Computing, Mobile Computing through Internet. 08 Hrs UNIT - 2 Global System for Mobile Communications (GSM): Global System for Mobile Communications, GSM Architecture, GSM Entities, Call Routing in GSM, PLMN Interfaces, GSM Addresses and Identifiers General Packet Radio Service (GPRS): Introduction, GPRS and Packet Data Network, GPRS Network Architecture, GPRS Network Operations, Data Services in GPRS, Applications for GPRS. 08 Hrs

UNIT -3 Wireless Application Protocol (WAP), CDMA AND 3G: Introduction, WAP, MMS, GPRS Applications, Spread-Spectrum Technology, Is-95, CDMA versus GSM, Wireless Data. 08 Hrs

UNIT - 4 Mobile IP Network Layer: IP and Mobile IP Network Layers Packet Delivery and Handover Management, Registration, Tunneling and Encapsulation Mobile Transport Layer: Indirect TCP, Snooping TCP, Mobile TCP, Other Methods of TCP – layer Transmission for Mobile Networks. 07 Hrs UNIT - 5 Security Issues in Mobile Computing: Introduction, Information Security, Security Techniques and Algorithms, Security Protocols, Public Key Infrastructure, Trust Mobile Application languages: Introduction, XML, JAVA, Java 2 Micro Edition (J2ME), JavaCard. Mobile Operating Systems:

Dept. of CSE, SIT, Tumakuru 49 Applicable for the academic year 2020-21 Batch: 2017

Operating System, PalmOS, Windows CE, Symbian OS, Linux for Mobile Devices. 08 Hrs

TEXT BOOKS: 1. Asoke Talkukder, Roopa R Yavagal, “Mobile Computing –Technology, Applications and Service Creation”, Tata McGraw Hill, 2008 (Chapters 1, 2, 5, 7, 8, 9, 18) 2. Raj Kamal, “Mobile Computing”, Oxford University Press, 2007. (Chapters 5, 6, 13, 14)

REFERENCES BOOKS: 1. Reza Behravanfar, “Mobile Computing Principles: Designing and Developing Mobile Applications with UML and XML”, ISBN: 0521817331, Cambridge University Press, October 2004, 2. Jochen Schiller, “Mobile Communications”, Addison-Wesley. Second edition, 2004. 3. Stojmenovic and Cacute, “Handbook of Wireless Networks and Mobile Computing”, Wiley, 2002, ISBN 0471419028. 4. M. Richharia, "Mobile Satellite Communication: Principles and Trends”, Pearson Education.

Dept. of CSE, SIT, Tumakuru 50 Applicable for the academic year 2020-21 Batch: 2017

HIGH PERFORMANCE COMPUTING

Contact Hours/ Week : 3 + 0 (Lecture + Tutorial) Credits : 3.0 Total Lecture Hours : 39 CIE Marks : 50 Sub. Code : CSPE28 SEE Marks : 50 Course objectives: This Course will enable students to: 1. Discuss Physical Organization of Parallel Platforms. 2. Differentiate One-to-All broadcast and All-to-one Reduction. 3. List the principles that need to be considered while designing parallel algorithms using CUDA and OpenMP. 4. Describe the metrics used to evaluate the performance of parallel programs. 5. Illustrate send and receive operations in a MPI paradigm. 6. Designing asynchronous programming using OpenMP

UNIT I Introduction to Parallel Computing: Motivating Parallelism, Scope of Parallel Computing Introduction to HPC: Parallel Programming Platforms: Implicit Parallelism: Trends in Microprocessor Architectures, Limitations of Memory System Performance, Dichotomy of Parallel Computing Platforms, Physical Organization of Parallel Platforms, Communication Costs in Parallel Machines. 07 Hrs UNIT II Principles of Parallel Algorithm Design: Preliminaries, Decomposition Techniques, Characteristics of Tasks and Interactions, Mapping Techniques for Load Balancing, Methods for Containing Interaction Overheads, Parallel Algorithm Models. Basic communication operations: One-to-All broadcast and All-to-one Reduction. Analytical Modeling of Parallel Programs: Sources of Overhead in Parallel Programs, Performance Metrics for Parallel Systems, the Effect of Granularity on Performance. 08 Hrs UNIT III Programming using the Message-Passing Paradigm: Principles of Message-Passing Programming, The Building Blocks: Send and Receive Operations, MPI: the Message Passing Interface, Topologies and Embedding, Overlapping Communication with Computation, Collective Communication and Computation Operations, Groups and Communicators. 08 Hrs UNIT IV Why CUDA? Why NoW?: The Age of Parallel Processing, Central Processing Units, The Rise of GPU Computing, A brief history of GPUs, Early GPU computing, CUDA, What is CUDA architecture, using the CUDA architecture, Applications of CUDA, Medical Imaging, Computational Fluid Dynamics, Environmental Science, Introduction to CUDA C: A First Program, Hello world, A kernel call, Passing parameters, Querying devices, using device properties, Prallel Programming in CUDA C:CUDA parallel programming, Summing vectors, A fun example. 08 Hrs

Dept. of CSE, SIT, Tumakuru 51 Applicable for the academic year 2020-21 Batch: 2017

UNIT V Programming Shared Address Space Platforms: Thread Basics, Why Threads? The POSIX Thread API,Thread Creation and Termination, Synchronization Primitives in Pthreads,Controlling Thread and Synchronization Attributes, Thread Cancellation, Composite Synchronization Constructs, Tips for Designing Asynchronous Programs,OpenMP: A Standard for Directive Based Parallel Programming. 08 Hrs

TEXTBOOKS 1 Ananth Grama,Anshul Introduction to parallel computing, second edition, Pearson Gupta,Vipin education publishers. kumar,George Karypis (chapters 01,2.1-2.5,3,4.1.1-4.1.3, 5.1, 5.2, 5.3, 6,7) 2 Jason Sanders CUDA by example, NVIDIA Corporation-2011(Chapters 1 ,3, Edward Kandrot and 4)

REFERENCE BOOKS: 1 Thomas Rauber and Parallel Programming for Multicore and cluster systems, Gudula Runger Springer International Edition,2009 2 Hennessey and Patterson Computer Architecture: A quantitative Approach, Morgan Kaufman Publishers 3 Michael J.Quin “Parallel Programming in C with MPI and Open MP”, McGraw Hill. (For MPI and Open MP) 4 D. E. Culler and J. P. Parallel Computer Architecture. Morgan- Kaufmann publishers Singh with A. Gupta.

Course Outcomes: After the completion of the course, students will be able to 1. Select and analyze the characteristics of various parallel computing platforms. 2. Choose a suitable platform for parallel computing. 3. Analyze simple parallel algorithm models. 4. Apply the principles of message-passing programming construct to solve engineering problems. 5. Design and develop parallel programs using CUDA and OpenMp programming interface

Dept. of CSE, SIT, Tumakuru 52 Applicable for the academic year 2020-21 Batch: 2017

NETWORK MANAGEMENT

Contact Hours/ Week : 3 + 0 (Lecture + Tutorial) Credits : 3.0 Total Lecture Hours : 39 CIE Marks : 50 Sub. Code : CSPE29 SEE Marks : 50

UNIT - 1 Introduction: Analogy of Telephone Network Management, Data and Telecommunication Network Distributed computing Environments, TCP/IP-Based Networks: The Internet and Intranets, Communications Protocols and Standards- Communication Architectures, Protocol Layers and Services; Case Histories of Networking and Management – The Importance of topology, Filtering Does Not Reduce Load on Node, Some Common Network Problems; Challenges of Information Technology Managers, Network Management: Goals, Organization, and Functions- Goal of Network Management, Network Provisioning, Network Operations and the NOC. 08 Hrs UNIT - 2 Basic Foundations: Standards, Models, and Language: Network Management Standards, Network Management Model, Organization Model, Information Model – Management Information Trees, Managed Object Perspectives, Communication Model; ASN.1- Terminology, Symbols, and Conventions, Objects and Data Types, Object Names 08 Hrs

UNIT -3 SNMPv1 Network Management: Managed Network: The History of SNMP Management, Internet Organizations and standards, Internet Documents, The SNMP Model, The Organization Model, System Overview. The Information Model – Introduction, The Structure of Management Information, Managed Objects, Management Information Base 08 Hrs

UNIT -4 SNMP Management–RMON: Remote Monitoring, RMON SMI and MIB, RMONI1- RMON1 Textual Conventions, RMON1 Groups and Functions, Relationship Between Control and Data Tables, RMON1 Common and Ethernet Groups, RMON Token Ring Extension Groups. 07 Hrs UNIT -5 Network Management Applications: Configuration Management- Network Provisioning, Inventory Management, Network Topology, Fault Management- Fault Detection, Fault Location and Isolation Techniques, Performance Management – Performance Metrics, Data Monitoring, Problem Isolation, Performance Statistics; Security Management – Policies and Procedures, Security Breaches and the Resources Needed to Prevent Them, Firewalls, Cryptography, Authentication and Authorization, Client/Server Authentication Systems, Messages Transfer Security, Protection of Networks from Virus Attacks. 08 Hrs

TEXT BOOKS: Mani Subramanian: Network Management- Principles and Practice, 2nd Pearson Education, 2010.

REFERENCE BOOKS: J. Richard Burke: Network management Concepts and Practices: a Hands-On Approach, PHI, 2008..

Dept. of CSE, SIT, Tumakuru 53 Applicable for the academic year 2020-21 Batch: 2017

CYBER SECURITY

Contact Hours/ Week : 3 + 0 (Lecture + Tutorial) Credits : 3.0 Total Lecture Hours : 39 CIE Marks : 50 Total Tutorial Hours : 00 SEE Marks : 50 Sub. Code : CSPE30

UNIT -1 Cyber Security Fundamentals: Network and Security Concepts, Information Assurance Fundamentals, Basic Cryptography, Symmetric Encryption, Public Key Encryption, The Domain Name System (DNS), Firewalls, Virtualization, Radio-Frequency Identification, Microsoft Windows Security Principles, Windows Tokens, Window Messaging, Windows Program Execution, The Windows Firewall 07 Hrs

UNIT -2 Attacker Techniques and Motivations: How Hackers Cover Their Tracks (Anti-forensics), How and Why Attackers Use Proxies, Tunneling Techniques, Fraud Techniques, Phishing, Smishing, Vishing and Mobile Malicious Code, Rogue Anti-Virus, Click Fraud, Threat Infrastructure, Botnets, Fast-Flux, Advanced Fast-Flux 08 Hrs

UNIT -3 Exploitation: Techniques to Gain a Foothold, Shellcode, Integer Overflow, Vulnerabilities, Stack-Based Buffer Overflows, Format-String Vulnerabilities, SQL Injection, Malicious PDF Files, Race Conditions, Web Exploit Tools, DoS Conditions, Brute-Force and Dictionary Attacks, Misdirection, Reconnaissance and Disruption Methods, Cross-Site Scripting (XSS), Social Engineering, WarXing, DNS Amplification Attacks. 08 Hrs

UNIT - 4 Malicious Code: Self-Replicating Malicious Code, Worms, Viruses, Evading Detection and Elevating Privileges, Obfuscation, Virtual Machine Obfuscation, Persistent Software Techniques, Rootkits, Spyware, Attacks against Privileged User Accounts and Escalation of Privileges, Token Kidnapping, Virtual Machine Detection, Stealing Information and Exploitation, Form Grabbing, Man-in-the-Middle Attacks, DLL Injection, Browser Helper Objects. 08 Hrs

UNIT - 5 Defense and Analysis Techniques: Memory Forensics, Why Memory Forensics Is Important, Capabilities of Memory Forensics, Memory Analysis Frameworks, Dumping Physical Memory, Installing and Using Volatility, Finding Hidden Processes, Volatility Analyst Pack, Honeypots, Malicious Code Naming, Automated Malicious Code Analysis Systems, Passive Analysis, Active Analysis, Physical or Virtual Machines, Intrusion Detection Systems, Cyber Security Essentials.

Dept. of CSE, SIT, Tumakuru 54 Applicable for the academic year 2020-21 Batch: 2017

Open Source Security Tools: Port Scanners: Installing Nmap on Linux and windows. Intrusion Detection Systems: Unique Features of Snort, Configuring Snort for Maximum performance. Analysis and Management Tools: Using Databases and Web Servers to Manage Your Security Data. Forensic Tools: Preparing for Good Forensic, Forensic Analysis Tools, Making Copies of Forensic and Creating and Logging into a Case. 08 Hrs TEXT BOOK: 1. James Graham, Richard Howard, Ryan Olson- Cyber Security Essentials CRC Press 2. Open Source Security Tools Practical Applications for Security by Tony Howlett. Web link: http://ptgmedia.pearsoncmg.com/images/0321194438/downloads/0321194438_book.pdf UNIT-5 Open Source Security tools: Chapter: 4, 7, 8 and 11 section from these chapters. REFERENCE BOOKS:

1 James A. Lewis, Cyber security: turning national solutions into international cooperation 2 Dan Shoemaker, Ph.D., William Arthur Conklin, Wm Arthur Conklin, Cyber security: The Essential Body of Knowledge. 3 John Rittinghouse, PhD, William M. Hancock, PhD, Cyber security Operations Handbook

Course Outcomes: After the completion of the course, students will be able to 1. Apply the cryptographic concepts underlying Cyber Security. 2. Analyze the techniques used by hackers to create frauds 3. Analyze the vulnerabilities in a network or in an application that will help hackers to build the attack. 4. Compare and analyze various types of malicious code 5. Demonstrate Memory Forensics as a defense technique for Cyber Security 6. Compare and analyze various types of Tools

Dept. of CSE, SIT, Tumakuru 55 Applicable for the academic year 2020-21 Batch: 2017

SOFTWARE TESTING

Contact Hours/ Week : 3 + 0 (Lecture + Tutorial) Credits : 3.0 Total Lecture Hours : 39 CIE Marks : 50 Sub. Code : CSPE31 SEE Marks : 50 UNIT - 1 A Perspective on Testing, Examples: Basic definitions, Test cases, Insights from a Venn diagram, Identifying test cases, Error and fault taxonomies, Levels of testing. Examples: Generalized pseudocode, The triangle problem, The Next Date function, The commission problem, The SATM (Simple Automatic Teller Machine) problem, The currency converter, Saturn windshield wiper. 07 Hrs UNIT - 2 Boundary Value Testing, Equivalence Class Testing, Decision Table Based Testing: Boundary value analysis, Robustness testing, Worst-case testing, Special value testing, Examples, Random testing, Equivalence classes, Equivalence test cases for the triangle problem, Next Date function, and the commission problem, Guidelines and observations. Decision tables, Test cases for the triangle problem, Next Date function, and the commission problem, Guidelines and observations 08 Hrs UNIT -3 Path Testing, Data Flow Testing: DD paths, Test coverage metrics, Basis path testing, guidelines and observations. Definition-Use testing, Slice-based testing, Guidelines and observations. 07 Hrs UNIT -4 Levels of Testing, Integration Testing: Traditional view of testing levels, Alternative life-cycle models, The SATM system, Separating integration and system testing. A closer look at the SATM system, Decomposition-based, call graph-based, Path-based integrations. System Testing, Interaction Testing: Threads, Basic concepts for requirements specification, Finding threads, Structural strategies and functional strategies for thread testing. 08 Hrs UNIT -5 SATM test threads, System testing guidelines, ASF (Atomic System Functions) testing example. Context of interaction, A taxonomy of interactions, Interaction, composition, and determinism, Client/Server Testing. Process Framework: Validation and verification, Degrees of freedom, Varieties of software. Basic principles: Sensitivity, redundancy, restriction, partition, visibility, Feedback. The quality process, Planning and monitoring, Quality goals, Dependability properties, Analysis, Testing, Improving the process, Organizational factors 09 Hrs

TEXT BOOKS:

1 Software Testing, A Craftsman’s Paul C. Jorgensen . 3 Edition, Auerbach Approach Publications, 2008. 2 Software Testing and Analysis – Mauro Pezze, Michal Young:, Wiley India, 2009 Process, Principles and Techniques

REFERENCE BOOKS:

1 Foundations of Software Aditya P Mathur, Pearson Education, 2008. Testing 2 Software Testing Srinivasan Desikan, Gopalaswamy Ramesh:, 2nd Principles and Practices Edition, Pearson Education, 2007 3 The Craft of Software Testing Brian Marrick:, Pearson Education, 1995

Dept. of CSE, SIT, Tumakuru 56 Applicable for the academic year 2020-21 Batch: 2017

ADVANCED UNIX PROGRAMMING

Contact Hours/ Week : 3 + 0 (Lecture + Tutorial) Credits : 3.0 Total Lecture Hours : 39 CIE Marks : 50 Total Tutorial Hours : 00 SEE Marks : 50 Sub. Code : CSPE32

UNIT - 1 UNIX Standardization and Implementations: Introduction, UNIX Standardization, UNIX System Implementations, Relationship of Standards and Implementations, Limits, Options, Feature Test Macros. 2 Hrs UNIX Processes: The Environment of a UNIX Process: Introduction, main function, Process Termination, Command-Line Arguments, Environment List, Memory Layout of a C Program, Shared Libraries, Memory Allocation, Environment Variables, setjmp and longjmp Functions, getrlimit, setrlimit Functions, UNIX Kernel Support for Processes. 5 Hrs

UNIT -2 Process Control: Introduction, Process Identifiers, fork, vfork, exit, wait, waitpid, wait3, wait4 Functions, Race Conditions, exec Functions, system Function, Process Accounting, User Identification, Process Times 3 Hrs Process Relationships: Process Groups, Sessions, Controlling Terminal, tcgetpgrp and tcsetpgrp Functions, Job Control, Shell Execution of Programs, Orphaned Process Groups. 3 Hrs Daemon Processes: Introduction, Daemon Characteristics, Coding Rules, Error Logging. 2 Hrs UNIT -3 Signals: Introduction, Signal Concepts, signal Function, kill and raise Functions, alarm and pause Functions, Signal Sets, sigprocmask Function, sigpending Function, sigaction Function, sigsetjmp and siglongjmp Functions, sigsuspend Function, abort Function, system Function, sleep Function, Job-Control Signals 8 Hrs UNIT - 4 Threads: Introduction, Thread Concepts, Thread Identification, Thread Creation, Thread Termination, Thread Synchronization. 2 Hrs

Advanced I/O: Introduction, Nonblocking I/O, Record Locking, STREAMS, I/O Multiplexing, Asynchronous I/O, readv and writev Functions, readn and writen Functions, Memory-Mapped I/O. 5 Hrs UNIT - 5 Inter-process Communication Overview of IPC Methods, Pipes, popen, pclose Functions, Coprocesses, FIFOs, System V IPC, Message Queues, Semaphores. Shared Memory. Network IPC: Sockets 9 Hrs

TEXT BOOK: 1 W. Richard Stevens, Advanced Programming in the UNIX Environment, Second Stephen A. Rago Edition, Addison-Wesley, 2005. [Chapters: 2,7, 8, 9,10,11,13,14,15,16] REFERENCE BOOKS:

1. Terrence Chan Unix System Programming Using C++, Prentice Hall India, 1999. 2. Maurice J Bach The Design of the UNIX Operating System , Prentice-Hall, 2007

Dept. of CSE, SIT, Tumakuru 57 Applicable for the academic year 2020-21 Batch: 2017

FOUNDATIONS OF DATA SCIENCE Contact Hours/ Week : 3 + 0 (Lecture + Tutorial) Credits : 3.0 Total Lecture Hours : 39 CIE Marks : 50 Total Tutorial Hours : 00 SEE Marks : 50 Sub. Code : CSPE33

COURSE OBJECTIVES: This Course will enable students to: 1 Describe the concept of data science, its scope in business and explain the available techniques. (L1, L2) 2 Understand Predictive modeling, explain supervised segmentation and given data set should be able to select (through solving) the attribute for segmentation using the available techniques. (L2, L3) 3 Explain the concept of Classification and classify (solve) a given data set. (L3) 4 Understand and describe the concept of similarity, neighbors and clustering and apply it for any real world data. (L3, L4) 5 Explain the concepts of mining text and other data science tasks and techniques. (L2, L4)

UNIT-1 Introduction: Data-Analytic Thinking: The Ubiquity of Data Opportunities, Example: Hurricane Frances, Example: Predicting Customer Churn. Data Science, Engineering, and Data-Driven Decision Making, Data Processing and “Big Data”, Data and Data Science Capability as a Strategic Asset, Data-Analytic Thinking. Business Problems and Data Science Solutions: From Business Problems to Data Mining Tasks, Supervised Versus Unsupervised Methods, Data Mining and Its Results, The Data Mining Process, Business Understanding, Data Understanding, Data Preparation, Modeling, Evaluation, Deployment, Other Analytics Techniques and Technologies: Statistics, Database Querying, Data Warehousing, Regression Analysis, Machine Learning and Data Mining 07 Hrs UNIT -2 Introduction to Predictive Modeling: From Correlation to Supervised Segmentation Models, Induction, and Prediction, Supervised Segmentation, Selecting Informative Attributes Example: Attribute Selection with Information Gain, Supervised Segmentation with Tree- Structured Models, Visualizing Segmentations, Trees as Sets of Rules, Probability Estimation, Example: Addressing the Churn Problem with Tree Induction. 08 Hrs

UNIT -3 Fitting a Model to Data: Classification via Mathematical Functions: Linear Discriminant Functions, Optimizing an Objective Function, An Example of Mining a Linear Discriminant from Data, Linear Discriminant Functions for Scoring and Ranking Instances, Support Vector Machines briefly, Regression via Mathematical Functions, Class Probability Estimation and Logistic “Regression”. Logistic Regression: Some Technical Details. Example: Logistic Regression versus Tree Induction, Non Linear Functions, Support vector machines and Neural Networks Over fitting and Its Avoidance: Fundamental Concepts, Exemplary Techniques, Regularization,

Dept. of CSE, SIT, Tumakuru 58 Applicable for the academic year 2020-21 Batch: 2017

Genaralization, Over fitting, Over fitting Examined. 08 Hrs UNIT - 4 Similarity, Neighbors, and Clusters: Similarity and Distance, Nearest-Neighbor Reasoning, Example: Whiskey Analytics, Nearest Neighbors for Predictive Modeling, How Many Neighbors and How Much Influence? Geometric Interpretation, Overfitting, and Complexity Control. Issues with Nearest-Neighbor Methods. Some important Technical Details Relating to Similarities and neighbors. Clustering, Example: Whiskey Analytics Revisited, Hierarchical Clustering, Nearest Neighbors Revisited: Clustering Around Centroids. Understanding the Results of Clustering 08 Hrs UNIT – 5 Decision Analytic Thinking I: What is a Good Model?: Evaluating Classifiers Plain Accuracy and its Problems, The confusion matrix, Problems with unbalanced Classes, Problems with Unequal Costs and Benefits. Representing and Mining Text: Why Text Is Important? Why Text Is Difficult? Representation, Bag of Words, Term Frequency, Measuring Sparseness: Inverse Document Frequency, Combining Them: TFIDF, Example: Jazz Musicians Other Data Science Tasks and Techniques: Co-occurrences and Associations: Finding Items That Go Together, Measuring Surprise: Lift and Leverage, Example: Beer and Lottery Tickets, Associations Among Facebook Likes, Profiling: Finding Typical Behavior, Link Prediction and Social Recommendation 08 Hrs

TEXT BOOK:

1 Foster Provost and Tom Fawcett Data Science for Business, Published by O’Reilly Media, Inc. July 2013: First Edition REFERENCE BOOKS:

1 Doing Data Science Rachel Schutt & Cathy O’Neil, O’Reilly Media, October 2013: First Edition 2 Practical Data Analysis Hector Cuesta,PACKT Publishing, First published: October 2013 3. Guide to Intelligent Data Michael R. Berthold,Christian Borgelt, Frank Hijppner Analysis Frank Klawonn, Springer-Verlag London Limited 2010

Course Outcomes: After the completion of the course, students will be able to

1. Apply the knowledge of mathematics to explain the concept of data science, the available techniques in data science and its scope in business. 2. Develop a Decision tree based on supervised segmentation and predict the class for a given data set by selecting (through solving) the attribute for segmentation using the available techniques. 3. Analyze the given data set, and solve a problem by performing Classification using the basics of mathematics and data science. 4. Develop solutions to group entities in data set and apply it for the given real world data using the basic knowledge of similarity, neighbors and clustering 5. Analyze the importance of mining text (social data) and formulate the association rules based on market basket analysis. Dept. of CSE, SIT, Tumakuru 59

Applicable for the academic year 2020-21 Batch: 2017 BIG DATA ContactHours/Week :3+0(Lecture+Tutorial) Credits : 3.0 Total Lecture Hours : 39 CIE Marks : 50 Total Tutorial Hours : 00 SEE Marks : 50 Sub. Code : CSPE34 COURSE OBJECTIVES: This Course will enable students to: 1. Describe the basic concepts , technology , evolution and applications of Big Data (L2) 2. Explain the architecture , components and technology of Big Data Ecosystem that can manage , process and analyze Big Data (L2) 3. Study how the data is stored in databases and data warehouses (L2) 4. Identify the importance of big data stack architecture in effective analysis of big data (L2) 5. Describe the basic MapReduce Programming Model and Apply it to solve real world application problems (L2,L3) 6. Describe the requirement of Hive & Oozie tools for Big Data access and monitoring (L2)

UNIT I Getting an Overview of Big Data: What is Big Data? History of Data, Management – Evolution of Big Data, Structuring Big Data, Types of Data, Elements of Big Data, Volume, Velocity, Variety, Veracity, Big Data Analytics, Careers in Big data, Advantages of Big Data Analytics, Future of Big Data. Exploring the Use of Big Data in Business Context: Use of Big Data in Social Networking, Business Intelligence, Marketing, Product Design and Development, Use of Big Data in Preventing Fraudulent Activities, Preventing Fraud Using Big Data Analytics, Use of Big Data in Retail Industry, Use of RFID Data in Retail Introducing Technologies for Handling Big Data: Distributed and Parallel Computing for Big Data,How data models and computing models are different, Introducing Hadoop, HDFS and MapReduce, How does Hadoop Function? Cloud Computing and Big Data, Cloud Services for Big Data, In-Memory Computing Technology for Big Data 07 Hrs UNIT II Understanding Hadoop Ecosystem: Hadoop Ecosystem,Hadoop Distributed File System, HDFS Architecture, Concepts of Blocks in HDFS Architecture, NameNodes and DataNodes, The command line interface, Using HDFS Files , Hadoop specific File System Files, HDFS commands,The org.apache.hadoop.io.package,HDFS High Availability , Features of HDFS, MapReduce, Hadoop Yarn, Introducing HBase, HBase Architecture, Regions, Storing Bigdata with HBase, Interacting with the Hadoop Ecosystem, HBase in Operation –Programming with HBase, Combining HBase and HDFS, REST and Thrift, Data Integrity in HDFS, Features of HBase ,hive, Pig and Pig Latin, Sqoop, Zookeeper, Flume, Oozie. Understanding Big Data Technology Foundations: Exploring the Big Data Stack, Data Sources Layer, Ingestion Layer, Storage Layer, Physical Infrastructure Layer, Platform Management Layer, Security Layer, Monitoring Layer, Analytics Engine, Visualization Layer, Big Data Applications, Virtualization and Big Data, Virtualization Approaches, Server virtualization, Application Virtualization, Network Virtualization, Processor and Memory Virtualization, Data and Storage Virtualization, Managing Virtualization with Hypervisor. Implementing Virtualization to work with Big data. 08 Hrs

Dept. of CSE, SIT, Tumakuru 60

Applicable for the academic year 2020-21 Batch: 2017 UNIT III Understanding MapReduce Fundamentals and HBase: The MapReduce Framework. Exploring the Features of MapReduce. Working of MapReduce. Exploring Map and Reduce Functions. Techniques to Optimize MapReduce Jobs. Hardware/Network Topology, Synchronization, File System. Uses of MapReduce. Role of HBase in Big Data Processing. Characteristics of HBase . Storing Data in Databases and Data Warehouses: RDBMS and Big Data, CAP Theorem, Issues with the Relational Model, Non-Relational Database, Issues with the Non-Relational Model, Polyglot Persistence, Integrating Big Data with Traditional Data Warehouses, Big Data Analysis and Data Warehouse, Changing Deployment Models in Big Data Era 08 Hrs UNIT – IV Processing Your Data with MapReduce: Recollecting the Concept of MapReduce Framework, Developing Simple MapReduce Application, Building the Application, Executing the Application, Points to Consider while Designing MapReduce. Customizing MapReduce Execution: Controlling MapReduce Execution with InputFormat, InputSplit, RecordReader, FileInputFormat, Implementing InputFormat for Compute-Intensive Applications, Implementing InputFormat to control the Number of Maps, Implementing InputFormat for Multiple HBase Tables, Reading Data with Custom RecordReader, Organizing Output Data with OutputFormats, Customizing Data with RecordWriter, Optimizing MapReduce Execution with Combiner, Controlling Reducer Execution with Partitioners 08 Hrs UNIT - V Exploring Hive: Introducing Hive, Getting Started with Hive,Hive services, Hive Variables, Hive Properties, Hive Queries, Data Types in Hive, Built-In Functions in Hive, Hive DDL, Creating Databases, Viewing a Database, Dropping a Database, Altering Databases, Creating Tables, Creating a Table Using the Existing Schema, Dropping Tables, Altering Tables, Using Hive DDL Statements, Data Manipulation in Hive, Loading Files into Tables, Inserting Data into Tables, Update in Hive, Delete in Hive, Using Hive DML Statements, Data Retrieval Queries, Using the SELECT Command, Using the WHERE Clause, Using the GROUP BY Clause, Using the HAVING Clause, Using the LIMIT Clause, Executing HiveQL Queries, Using JOINS in Hive, Inner Joins, Outer Joins, Cartesian Product Joins, Map-Side Joins, Joining Tables

Using Oozie: Introducing Oozie, Main Functional Components of Oozie, Benefit of Oozie, Installing and Configuring Oozie, Understanding the Oozie Workflow, Execution of Asynchronous Actions in Oozie, Implementing the Oozie Workflow, Oozie Recovery Capabilities, Oozie Workflow Life Cycle, Oozie Coordinator, Types of Oozie Coordinator, Oozie Coordinator Lifecycle Operations, Oozie Bundle, Oozie Parameterization with EL, Workflow Functions, Coordinator Functions, Bundle Functions, EL Functions, Oozie Job Execution Model, Accessing Oozie, Oozie SLA, Event Status, SLA Status ,Oozie Activity, The Oozie SLA Subsystem, SLA Language Schema

8 Hrs

Dept. of CSE, SIT, Tumakuru 61

Applicable for the academic year 2020-21 Batch: 2017 TEXT BOOK: 1 BIG DATA D T Editorial Services, Dreamtech press 2016 Edition Black Book

REFERENCE BOOKS: 1 Big Data Glossary Pete Warden, O’Reilly, 2011

2 Hadoop: The Definitive Tom White Third Edition, O’reilly Media, Fourth Guide Edition,2015 3. Big Data and Analytics Seema Acharya,Subhashini Chellappan, Wiley India Publications, May 2015

COURSE OUTCOMES (COS): After the completion of this course, students will be able to:

1. Apply the basic knowledge related to Big Data to explain its elements, its analytics, its usage in business context and computing in big data 2. Select and apply appropriate modern tools of Hadoop ecosystem to the solution of various problems in storage , processing , accessing , managing and analyzing the Bigdata 3. Design and Develop MapReduce programs to the solution of various real world application problems 4. Identify the importance of the different layers of Bigdata Stack architecture in effective analysis of Bigdata 5. Analyze the merits of using modern data warehouses against the limitations of Traditional Databases 6. Identify the requirement of Hive and Oozie tools for Bigdata access and monitoring

Dept. of CSE, SIT, Tumakuru 62

Applicable for the academic year 2020-21 Batch: 2017 MACHINE LEARNING TECHNIQUES

Contact Hours/Week :3+0 (Lecture + Tutorial) Credits : 3.0 Total Lecture Hours : 39 CIE Marks : 50 Total Tutorial Hours : 00 SEE Marks : 50 Sub. Code : CSPE35

Course Objectives: This Course will enable students to: 1. Define machine learning and understand the basic theory underlying machine learning. 2. Differentiate supervised, unsupervised and reinforcement learning. 3. Understand the basic concepts of learning and decission trees. 4. Understand neural networks and genetic algorithms for problems appear in machine learning. 5. Understand the instant based learning and analyitical learning. 6. Understand the reinforced learning. 7. Perform the statistical analysis of machine learning techniques.

UNIT – I INTRODUCTION, CONCEPT LEARNING: Well Posed Learning problem, Designing Learning systems, Perspectives and Issues in machine learning, Concept Learning: Introduction, A Concept Learning Task, Concepts Learning Search, Version Spaces and Candidate Elimination Algorithm, Remarks on version space and Candidate Elimination. 8 Hrs.

UNIT - II BAYESIAN LEARNING: Introduction, Bayes Theorem, Bayes Theorem and Concept Learning, Maximum Likelihood and least squared error hypotheses, Minimum Description Length Principle, Bayes Optimal Classifier, and Naive Bayes Classifier, An Example: Learning to Classify Text, Bayesian Belief network, EM Algorithm- General Statements of EM Algorithm. 8 Hrs.

UNIT III NEURAL NETWORKS: Introduction, Neural Network Representations, Appropriate problems for Neural Networks, Perceptrons, Multilayer Networks and Back Propagation Algorithms. GENETIC ALGORITHMS: Motivation, Genetic Algorithms, Hypothesis Space Search, Genetic Programming. 8 Hrs.

Unit IV INSTANT BASED LEARNING: Introduction K- Nearest Neighbor Learning, Locally Weighted Regression, Radial Basis Functions. ANALYTICAL LEARNING: Introduction, learning with Perfect Domain Theories, Remarks on Explanation Based Learning, Explanation Based Learning of Searching Control Knowledge. 8 Hrs.

Dept. of CSE, SIT, Tumakuru 63

Applicable for the academic year 2020-21 Batch: 2017 Unit V REINFORCEMENT LEARNING: Introduction, Learning Task, Q-Learning, Nondeterministic Rewards and actions, Temporal Difference Learning, Generalizing from Examples, Relationship to Dynamic Programming. 7 Hrs.

TEXT BOOKS: 1. Tom M. Mitchell “Machine Learning”, McGraw-Hill Education (INDIAN EDITION), 2013. (Chapters 1.1-1.3, 2.1-2.3,2.5,2.6, 4.1- 4.5,6.1-6.4,6.6-6.7,6.9,6.10,6.11(6.11.1-6.11.4) ,6.12, 8.1- 8.5,9.1-9.5, 11.1-11.4,13.1-13.7)

REFERENCE BOOKS: 1. Ethem Alpaydin “Introduction to Machine Learning”, 2nd Ed., PHI Learning Pvt. Ltd., 2013. 2. T. Hastie, R. Tibshirani, “The Elements of Statistical Learning”, Springer; 1st J. H. Friedman edition, 2001.

Course Outcomes: After the completion of the course, students will be able to 1. Choose the learning techniques and investigate concept learning. 2. Apply Bayesian techniques and derive effectively learning rules. 3. Apply effectively neural networks and genetic algorithm for appropriate applications. 4. Apply instant based learning and analytical learning to solve the given machine learning applications. 5. Evaluate hypothesis and investigate instant based learning and reinforced learning.

Dept. of CSE, SIT, Tumakuru 64

Applicable for the academic year 2020-21 Batch: 2017 Project Management & Finance Contact Hours/Week : 3 (L) Credits : 3 Total Lecture Hours : 39 CIE Marks : 50 Course Code : CSPE36 SEE Marks : 50

Course objectives: This course will enable students to: 1) Acquiring an ability to analyze, the process of Product and Project Life Cycle .(L1) 2) Analyzing Project Integration Management, Project Scope Management & Project Schedule Management. (L2) 3) Defining and Analyzing the concepts, purpose and significance of Project Cost Quality & Resource Management. (L2) 4) Analyzing the concepts of Project management and the methods of procurement, stakeholders and communication management. (L2)

Unit I Introduction: Project, Program, and portfolio, Operations management, Product life cycle, Project life cycle, Project management life cycle, Ten Knowledge areas, Role of project manager and PMO, Ten Project Knowledge areas with their associated processes. Project Integration Management: Develop project charter, Develop project management plan, Direct & manage project work, Monitor control project, Perform integrated change control, Close project / phase. (Section 4.1, 4.2, 4.3, 4.4, 4.5, 4.6, 4.7) 7 Hrs. UNIT - II Project scope management: Plan scope management, Collect requirements, Define scope, Create WBS, Validate Scope, Control scope. (Section 5.1, 5.2, 5.3, 5.4, 5.4.1, 5.5, 5.6)

Project Schedule management: Plan schedule management, Define activities, Sequence activities, Estimate activity durations, Develop schedule, and Control schedule and Problems. (Section 6.1, 6.2, 6.3, 6.4, 6.4.1, 6.5, 6.5.2.2, 6.6) 8 Hrs. Unit III Project cost management: Plan cost management, Estimate cost, Determine budget, and Control costs. (Section 7.1, 7.2, 7.2.1, 7.3, 7.4) and Problems. Project quality management: Plan quality management, Manage quality and Control quality (Section 8.1, 8.2, 8.3) Project resource management: Plan resource management, Estimate activity resources, Acquire resources, Develop team, Manage team and Control resources (Section 9.1, 9.2, 9.3, 9.4, 9.5, 9.6) 8 Hrs. Unit IV Project communication management: Plan communication management plan, Manage communications and Monitor communications (Section 10.1, 10.2, 10.3)

Project risk management: Plan risk management, Identify risks, Perform qualitative risk analysis, Perform quantitative risk analysis, Plan risk responses, Implement risk responses and Monitor risks. (Section 11.1, 11.2, 11.3, 11.4, 11.5, Dept. of CSE, SIT, Tumakuru 65

Applicable for the academic year 2020-21 Batch: 2017 11.6, 11.7) Project Procurement management: Plan procurement management, Conduct procurement, Control procurements. (Section 12.1, 12.2, 12.3) 8 Hrs. Unit V Project stake holder management: Identify stake holders, Plan stake holder management, Manage stake holder engagement, and Monitor stake holder engagement. A case study relevant to the domain knowledge of the department is taken up to explain the principles of the project management as brought out above. 8 Hrs.

TEXT BOOKS: 1. Project Management Book of Knowledge (PMBOK), 6th Edition, PMI, USA

REFERENCE BOOKS: 1 Prasanna Chandra, Project Planning: Analysis, Selection, Implementation and Review, MC- Graw Hill Education, 8th Edition, 2017.

Course Outcomes: After the completion of the course, students will be able to

1. Explain and analyze the basic concepts of project management, roles of project managers and identify different stages involved in project planning 2. Explain, analyze and Develop Scope management Plan and Project Schedule based on approved project deliverables and milestones 3. Describe, analyze and Design the procedures for overall financial analysis of the project alongside the resource requirement and ideal quality 4. Analyze, Identify and explain the sources and processes for communication, risk management and procurement 5. Describe stakeholder management processes and perform stakeholder analysis using appropriate tools and techniques in order to align expectations and gain support for the project

Dept. of CSE, SIT, Tumakuru 66

Applicable for the academic year 2020-21 Batch: 2017 ENTERPRISE CONTENT MANAGEMENT Contact Hours/ Week : 2 + 2 (Lecture + Practical) Credits : 3.0 Total Lecture Hours : 26 CIE Marks : 50 Total Lab Hours : 26 SEE Marks : 50 Sub. Code : CSPE37

UNIT -1 WCM & AEM Introduction: AEM Terminology, Basic concepts AEM Setup & Overview: Install and deploy AEM, Work with various Web Consoles, Work with User interfaces (UIs) Web Framework: Understand REpresentational State Transfer (REST) architectural style, Apache Sling. OSGi Framework: Understand the concepts of OSGi and Apache Sling, Describe the AEM functional building blocks, Describe the Granite platform, Understand OSGi framework, Understand about OSGi bundles 5+5 Hrs. UNIT -2 Content Repository: Basic Concepts – JCR, Learn about the Java Content Repository (JCR), Understand the concepts of Apache Jackrabbit, Explore Adobe CRX, Understand the underlying repository structure AEM – Developer UI: Content Authoring Overview, CRX Interface, CRXDE Lite Interface. AEM – Templates & Components: Creating Project Structure, Introduction to Sightly, Creating Template & Page Component (JSP and Sightly), Creating Pages & Website Structure. 5+5 Hrs. UNIT -3 Sightly: Features of Sightly in AEM Development, Sightly Vs JSP, Building Blocks, Expressions & Statements. AEM Authoring Framework – Components & Design: Modularize the template, Extend the component hierarchy, Assign a design, Create and include components in scripts. AEM Authoring Framework – Dialog Boxes: Create dialog boxes for components, Create Design dialog boxes for global content, Use the Edit_Config property to enhance components 5+5 Hrs. UNIT -4 Authoring Responsive and Mobile Pages: Define Responsive Design Work with Responsive page layout, Create a Mobile page, Add content to the Mobile page DAM: Finding & Viewing Assets, Create a folder and upload assets to it, Edit an asset and it's properties, Add a content fragment and an asset to a page. Adding New Content: Create a page, Insert a new paragraph, Edit the text paragraph, Add new components, Work with the Content Finder Handling Page Properties: Describe Page Properties, Provide Multiple titles for a Page, Bulk Editing. 6+6 Hrs.

Dept. of CSE, SIT, Tumakuru 67

Applicable for the academic year 2020-21 Batch: 2017 UNIT -5 Workflows: Creating and Managing Workflows, Creating and Managing Launches. Admin Basics: Roles, Users, Groups and Permissions(ACLs), Apache Felix Console Interface, Package Manager. Agile Basics: Agile Basics for AEM Projects. 5+5 Hrs.

Course Outcomes: After the completion of the course, students will be able to 1. Describe the evolution and explosion of digital touchpoints and social media across all channels making the content relevant, engaging and unified experience. 2. Develop solutions to attract new audiences, deliver targeted content through actionable data and social interactions. 3. Explain and apply AEM Content Repository, UI, Templates and components. 4. Construct user experience modules using AEM Authoring Framework 5. Utilize rich media assets and optimize multichannel outreach for increased click-throughs impacting conversions. 6. Develop responsive and mobile pages using layouts and designs and Understand the basics of Workflows and Administration in AEM.

Dept. of CSE, SIT, Tumakuru 68

Applicable for the academic year 2020-21 Batch: 2017 GAME THEORY Contact Hours/Week : 03 Credits : 03 Total Lecture Hours : 39 CIE Marks : 50 Total Tutorial Hours : 00 SEE Marks : 50 Course Code : CSPE38

Course objectives: This course will enable students to: 1. Emphasize on the applications of game theory in various decision making scenarios. 2. Use key concepts such as equilibrium, rationality, and cooperation in game theory 3. Apply game-theoretic analysis, by computing Core and Shapley Value for interactions among coalitions of players. 4. Analyse the key models and solutions for non-cooperative and cooperative game theory. 5. Compare various Game Theoretic based bargaining procedures

UNIT - I Introduction, uses of Game Theory, some application and examples, Games in Normal Form : Example: The TCP User’s Game , Definition of Games in Normal Form, More Examples of Normal-Form Games - Prisoner’s Dilemma , Common- payoff Games , Zero-sum Games , Battle of the Sexes ; Strategies in Normal-form Games. Analyzing Games: From Optimality To Equilibrium: Pareto optimality, Defining Best Response and Nash Equilibrium; Finding Nash Equilibria . 8 Hrs.

UNIT - II Further Solution Concepts for Normal-Form Games: Maxmin and Minmax Strategies, Minimax Regret ; Removal of Dominated Strategies; Rationalizability; Correlated Equilibrium, Trembling-Hand Perfect Equilibrium, Nash Equilibrium, Evolutionarily Stable Strategies. Games With Sequential Actions: The Perfect-information Extensive Form: Definition, Strategies and Equilibria, Subgame-Perfect Equilibrium, Backward Induction. 8 Hrs.

UNIT - III Generalizing the Extensive Form: Imperfect-Information Games: Definition, Strategies and Equilibria , Sequential Equilibrium . Repeated Games : Finitely Repeated Games , Infinitely Repeated Games . Uncertainty About Payoffs: Bayesian Games : Definition, Information Sets , Extensive Form with Chance Moves, Epistemic Types , Strategies and Equilibria . 8 Hrs.

UNIT - IV Coalitional Game Theory: Coalitional Games with Transferable Utility , Classes of Coalitional Games , Analyzing Coalitional Games , The Shapley Value , The Core . 7 Hrs.

UNIT - V Bargaining Procedures and the problem of honesty: Introduction, The Honesty Problem, The Bonus Procedure, The Bonus Appraisal Procedure, The Penalty Procedure, The Penalty Appraisal Procedure. 8 Hrs.

Dept. of CSE, SIT, Tumakuru 69

Applicable for the academic year 2020-21 Batch: 2017

TEXT BOOKS: 1. Kevin Leyton-Brown Essentials of Game Theory Morgan and Claypool Publishers. Yoav Shoham 2. Steven J Brams Applying Game Theory to Bargaining and Arbitration, Routledge Taylor & Francis Group

REFERENCE BOOKS: 1. Osborne, M. J A Course in Game Theory. Cambridge, MA: MIT Press Rubinstein, A.. 2. Nisan, N. Algorithmic Game Theory. Cambridge University Press T. Roughgarden E. Tardos V. Vazirani

Course outcomes: After the completion of this course, students will be able to: 1. Analyze games based on complete and incomplete information about the players 2. Analyze games where players cooperate 3. Compute Nash equilibrium with suitable procedures 4. Compute Core and Shapley Value to study the interactions among coalitions of layers. 5. Analyse Game Theoretic based bargaining procedures 6. Model Engineering problems with Game Theoretic Approaches.

Dept. of CSE, SIT, Tumakuru 70

Applicable for the academic year 2020-21 Batch: 2017 INTERNET OF THINGS Contact Hours/Week : 3 + 0 (L+T) Credits : 03 Total Lecture Hours : 39 CIE Marks : 50 Total Tutorial Hours : 00 SEE Marks : 50 Course Code : CSPE39 Course objectives: This course will enable students to: 1. Realize the evolution of IOT in Mobile Devices, Cloud & Sensor Networks. 2. Study the building blocks of IOT, its characteristics and application areas of IOT. 3. Explore and learn about Internet of Things with the help of preparing projects designed for Raspberry Pi. 4. Explore the architecture, its components and working of IOT components. Unit - I Introduction & Concepts: Introduction to Internet of Things, Definitions and Characteristics of IoT, Physical Design of IoT, Things in IoT, IoT Protocols, Logical Design of IoT, IoT Functional Blocks, IoT Communication Models, IoT Communication APIs, IoT Enabling Technologies, Wireless Sensor Networks, Cloud Computing, Big Data Analytics, Communication Protocols, Embedded Systems, IoT levels and Development Templates, IoT Level-1, IoT Level-2, IoT Level-3, IoT Level-4, IoT Level-5, IoT Level-6. 09 Hrs.

Unit - II IoT Platform Design Methodology: Introduction, IoT Design Methodology: Step1: Purpose and requirement specification, Step2: Process Specification, Step 3: Domain Model Specification, Step 4: Information Model Specification, Step 5: Service Specification, Step 6: IoT Level Specification, Step 7: Function View Specification Step 9: Device and Component Integration, Step 10: Application Development. Case Study: Weather Monitoring. 08 Hrs.

Unit - III Python Programming: Introduction, Installing Python, Python Data Types and Data Structures, Control Flow, Functions, Modules, Packages, File Handling, Date Time applications, Classes, Python Packages of Interest for IoT.

Python web application frame work-django, designing a RESTful web API, amazon web services for IoT, SkyNetIoT messaging platforms. 08 Hrs. Unit - IV Raspberry Pi : Basic Building Blocks - The Board, Linux on Raspberry Pi, Raspberry pi interfaces, programming Raspberry Pi with python

Cloud : IoT physical servers and cloud offerings: introduction to cloud storage models and communication Networks 07 Hrs.

Unit - V Data Analytics for IoT; Introduction AppacheHadoop, using HadoopMapReduce for Batch Data Analysis, Apache oozie, Apache Spark, Apache Storm, using Apache Storm for Real-time Data Analysis. 07 Hrs.

Dept. of CSE, SIT, Tumakuru 71

Applicable for the academic year 2020-21 Batch: 2017

TEXT BOOKS: 1.Arshdeep Bahga, VijayInternet Of Things-A Hands on Approach, University of Penn, Madisetti http://www.internet-of-things-book.com/ 2.Adrian McEwen &Designing the Internet of Things, ISBN 978-81-265-5686-1 Wiley Hakim Cassimally Publication.

REFERENCE BOOK: 1. Ovidiu Vermesan, Internet of Things : Converging Technologies for Smart PeterFriess Environmentsand Integrated Ecosystems. River Publishers Series in Communication.

Course outcomes: After the completion of this course, students will be able to: 1. Apply the knowledge of the internet and computer network onto IoT paradigm. 2. Adequately learn and demonstrate the IoT communication. 3. Apply the knowledge of python in Raspberry PI programming. 4. Analyze different configuration setups for connecting different types of sensors and upload the code on the board and communicate to the cloud. 5. Apply the knowledge of data analytics in different analytics platforms.

Dept. of CSE, SIT, Tumakuru 72

Applicable for the academic year 2020-21 Batch: 2017 WEB TECHNOLOGIES AND ITS APPLICATIONS Contact Hours/Week : 3 L Credits : 3 Total Lecture Hours : 39 CIE Marks : 50 Total Tutorial Hours : - SEE Marks : 50 Course Code : CSPE40

Course objectives: This course will enable students to: 1. Illustrate the Semantic Structure of HTML and CSS 2. Compose forms and tables using HTML and CSS 3. Design Client-Side programs using JavaScript and Server-Side programs using PHP 4. Infer Object Oriented Programming capabilities of PHP 5. Examine JavaScript frameworks such as jQuery and Backbone

UNIT - I Introduction to HTML, What is HTML and Where did it come from?, HTML Syntax, Semantic Markup, Structure of HTML Documents, Quick Tour of HTML Elements, HTML5 Semantic Structure Elements, Introduction to CSS, What is CSS, CSS Syntax, Location of Styles, Selectors, The Cascade: How Styles Interact, The Box Model, CSS Text Styling. Chapters: 2.1 to 2.6, 3.1 to 3.7 8 Hrs. UNIT - II HTML Tables and Forms, Introducing Tables, Styling Tables, Introducing Forms, Form Control Elements, Table and Form Accessibility, Microformats, Advanced CSS: Layout, Normal Flow, Positioning Elements, Floating Elements, Constructing Multicolumn Layouts, Approaches to CSS Layout, Responsive Design, CSS Frameworks. Chapters: 4.1 to 4.6, 5.1 to 5.7 8 Hrs. UNIT - III JavaScript: Client-Side Scripting, What is JavaScript and What can it do?, JavaScript Design Principles, Where does JavaScript Go?, Syntax, JavaScript Objects, The Document Object Model (DOM), JavaScript Events, Forms, Introduction to Server-Side Development with PHP, What is Server-Side Development, A Web Server’s Responsibilities, Quick Tour of PHP, Program Control, Functions Chapters: 6.1 to 6.8, 8.1 to 8.5 8 Hrs. UNIT - IV PHP Arrays and Superglobals, Arrays, $_GET and $_POST Superglobal Arrays, $_SERVER Array, $_Files Array, Reading/Writing Files, PHP Classes and Objects, Object-Oriented Overview, Classes and Objects in PHP, Object Oriented Design, Managing State, The Problem of State in Web Applications, Passing Information via Query Strings, Passing Information via the URL Path. Chapters: 9.1 to 9.5, 10.1 to 10.3, 13.1 to 13.3 8 Hrs.

UNIT - V Cookies, Serialization, Session State, HTML5 Web Storage, Advanced JavaScript and jQuery, JavaScript Pseudo-Classes, jQuery Foundations, AJAX, Asynchronous File

Dept. of CSE, SIT, Tumakuru 73

Applicable for the academic year 2020-21 Batch: 2017 Transmission, Animation, Backbone MVC Frameworks, Getting Started with Backbone.js, Backbone Models, Collections, Views. Chapters: 13.4 to 13.7, 15.1 to 15.6 8 Hrs.

TEXT BOOK: 1. Randy Connolly, "Fundamentals of Web Development”, Pearson Education Ricardo Hoar India, 1st Edition, ISBN:978-9332575271

REFERENCE BOOKS: 1. Alexis Goldstein, “HTML5 & CSS3 for the Real World”, SitePoint Pty. Ltd., Louis Lazaris, 2nd Edition, 2015, ISBN: 978-0987467485 Estelle Weyl 2. Adrian W. West “Practical Web Design for Absolute Beginners”, Apress, Edition, 2016, ISBN: 978-1484219928 3. Patrick Carey “New Perspectives on HTML5 and CSS3”, Cengage Learning, 7th Edition, 2017, ISBN: 978-1305503939

Course outcomes: After the completion of this course, students will be able to: 1. Apply the knowledge of HTML and CSS syntax and semantics to build web pages. 2. Construct and visually format tables and forms using HTML and CSS. 3. Develop Client-Side Scripts using JavaScript and Server-Side Scripts using PHP to generate and display the contents dynamically. 4. Appraise the principles of object oriented development using PHP 5. Illustrate JavaScript frameworks like Query and Backbone which facilitates developer to focus on core features.

Dept. of CSE, SIT, Tumakuru 74

Applicable for the academic year 2020-21 Batch: 2017 FOUNDATIONS OF BLOCKCHAIN Contact Hours/Week : 3 (L) Credits : 3 Total Lecture Hours : 39 CIE Marks : 50 Total Tutorial Hours : 00 SEE Marks : 50 Course Code : CSPE41 Course objectives: This course will enable students to: 1. Comprehend the fundamentals of Blockchain and its organization. 2. Describe the underlying concepts of working of a Blockchain. 3. Infer the working principle of Bitcoin. 4. Interpret the working of Blockchain using Ethereum. 5. Examine possible business applications of Blockchain.

UNIT - I Introduction to Blockchain, Backstory of Blockchain, What is Blockchain?, Centralized vs. Decentralized Systems, Centralized Systems, Decentralized Systems, Layers of Blockchain, Application Layer, Execution Layer, Semantic Layer, Propagation Layer, Consensus Layer, Why is Blockchain Important?, Limitations of Centralized Systems, Blockchain Adoption So Far, Blockchain Uses and Use Cases T1 – Chapter 1 8 Hrs. UNIT - II Laying the Blockchain Foundation, Game Theory, Nash Equilibrium, Prisoner’s Dilemma, Byzantine Generals’ Problem, Zero-Sum Games, Why to Study Game Theory, Computer Science Engineering, The Blockchain, Merkle Trees, Putting It All Together, Properties of Blockchain Solutions, Blockchain Transactions, Distributed Consensus Mechanisms, Blockchain Applications, Scaling Blockchain, Off-Chain Computation, Sharding Blockchain State T1 – Chapter 2 8 Hrs. UNIT - III The History of Money, Dawn of Bitcoin, What Is Bitcoin?, Working with Bitcoins, The Bitcoin Blockchain, Block Structure, The Genesis Block, The Bitcoin Network, Network Discovery for a New Node, Bitcoin Transactions, Consensus and Block Mining, Block Propagation, Putting It all Together, Bitcoin Scripts, Bitcoin Transactions Revisited, Scripts, Full Nodes vs. SPVs, Full Nodes, SPVs T1 – Chapter 3 8 Hrs. UNIT - IV From Bitcoin to Ethereum, Ethereum as a Next-Gen Blockchain, Design Philosophy of Ethereum, Enter the Ethereum Blockchain, Ethereum Blockchain, Ethereum Accounts, Trie Usage, Merkle Patricia Tree, RLP Encoding, Ethereum Transaction and Message Structure, Ethereum State Transaction Function, Gas and Transaction Cost, Ethereum Smart Contracts, Contract Creation, Ethereum Virtual Machine and Code Execution, Ethereum Ecosystem, Swarm, Whisper, DApp, Development Components T1 – Chapter 4 8 Hrs.

Dept. of CSE, SIT, Tumakuru 75

Applicable for the academic year 2020-21 Batch: 2017 UNIT - V Propelling Business with Blockchains , Recognizing Types of Market Friction, Information frictions, Interaction frictions, Innovation frictions, Moving Closer to Friction-Free Business Networks, Reducing information friction, Easing interaction friction, Easing innovation friction, Transforming Ecosystems through Increased Visibility, Blockchain in Action: Use Cases Financial Services, Trade finance, Post-trade clearing and settlement, Cross-border transactions, Trusted digital identity, Multinational Policy Management, Government, Supply Chain Management, Food safety, Global trade, Healthcare, Electronic medical records, Healthcare payment preauthorization T2 – Chapter 3 & 4 8 Hrs.

TEXT BOOKS: 1. Bikramaditya Singhal, Beginning Blockchain, Apress Media, 2018, ISBN Gautam Dhameja, 9781484234433 Priyansu Sekhar Panda 2. Manav Gupta Blockchain For Dummies, John Wiley & Sons, 2nd IBM Limited Edition, ISBN 9781119545934

REFERENCE BOOKS: 1. Peter Lypovonyav Blockchain for Business 2019, Packt Publishing Limited, 2019, ISBN 9781789956023 2. Debajani Mohanty Ethereum for Architects and Developers, Apress Media, 2018, ISBN 9781484240748

Course outcomes: After the completion of this course, students will be able to: 1. Explain the fundamentals of Blockchain and its structure. 2. Outline the prerequisite concepts of Blockchain. 3. Illustrate the working of Bitcoin cryptocurrency. 4. Demonstrate the use of Ethereum in implementing Blockchain. 5. Examine potential business use cases of Blockchain

Dept. of CSE, SIT, Tumakuru 76

Applicable for the academic year 2020-21 Batch: 2017 ADVANCED DATA STRUCTURES AND ALGORITHMS

Contact Hours/ Week : 3 + 0 (Lecture + Tutorial) Credits : 3.0 Total Lecture Hours : 39 CIE Marks : 50 Total Tutorial Hours : 00 SEE Marks : 50 Course Code :CSPE42 Course objectives: This course will enable students to: 1. Knowledge: List, define and identify the different data structures and its uses. 2. Comprehension: Explain the relationship between data and operations on data structures. 3. Analysis: Compare and contrast the design and implementation of various operations on data structures. 4. Synthesis: Design efficient algorithms for data structures. 5. Evaluation: Evaluate the efficiency of the algorithms used to operate on various data structures. UNIT I Abstract Data Types and Trees: Abstract Data Types (ADTs), List ADT, Vector and List in the STL, implementation of vector, implementation of list. B-trees 7 Hrs UNIT II Hashing: General idea, Hash function, Separate chaining, Hash tables without linked list, Rehashing, Extensible hashing. 8 Hrs UNIT -III Priority Queues: Heaps revisited – Model, simple implementations, Binary Heap. d-Heaps, Leftist Heaps, Skew Heaps, Binomial Queues 8 Hrs UNIT – IV Sorting: Shell sort, Quick sort, Indirect sorting, External sorting. 8 Hrs

UNIT –V Miscellaneous Data Structures: Bottom-up and Top-down Splay trees, Red-Black Trees 8 Hrs

TEXTBOOK:

1. Mark Allen Weiss Data Structures and Algorithm Analysis in C++, 3rd Edition, Pearson Education.

REFERENCE BOOKS:

1. Thomas H. Cormen, Charles E. Introduction to Algorithms. Ed 2. PHI. 2006. Leiserson, Ronal L. Rivest, Clifford Stein. 2. Alfred V. Aho, John E. Hopcroft, Data Structures and Algorithms. Jeffrey D. Ullman

Dept. of CSE, SIT, Tumakuru 77

Applicable for the academic year 2020-21 Batch: 2017

Course Outcomes: After the completion of this course, students will be able to: 1. Explain various data structures and its application in computer science. 2. Demonstrate how data structures are implemented using C++ Standard Template Library. 3. Analyze and Compare algorithms and techniques of implementing data structures using STL. 4. Design and Implement the complex data structures with algorithms.

Dept. of CSE, SIT, Tumakuru 78