Flow and Congestion Control for High Speed Networks
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Scalable Network Scheduling in Software A
SCALABLE NETWORK SCHEDULING IN SOFTWARE A Dissertation Presented to The Academic Faculty By Ahmed Mohamed Said Mohamed Tawfik Issa In Partial Fulfillment of the Requirements for the Degree Doctor of Philosophy in the School of Computer Science Georgia Institute of Technology August 2019 Copyright c Ahmed Mohamed Said Mohamed Tawfik Issa 2019 SCALABLE NETWORK SCHEDULING IN SOFTWARE Approved by: Dr. Mostafa H. Ammar, Co-advisor Dr. Amin Vahdat School of Computer Science Google Georgia Institute of Technology Dr. Ellen W. Zegura, Co-advisor Dr. Jun Xu School of Computer Science School of Computer Science Georgia Institute of Technology Georgia Institute of Technology Dr. Ada Gavrilovska School of Computer Science Georgia Institute of Technology Date Approved: June 17th, 2019 To my wife, Heba Kamal. ACKNOWLEDGEMENTS This work is a culmination of work done throughout my PhD which wouldn’t have been possible without the encouragement, support, and guidance of many. I am grateful to everyone who was there for me. First and foremost, I would like to express my sincere gratitude to my advisors Prof. Ellen W. Zegura and Prof. Mostafa Ammar for their dedica- tion, availability, guidance, patience, and support. From my first day at Geogria Tech, they were accommodating of my inclination to exploration and my many side projects. Their guidance helped me to grow and develop academically and professionally. Their compli- mentary views and advice enriched my experience and allowed me to make more educated choices throughout my PhD. I am also extremely grateful to Prof. Khaled Harras whom without I wouldn’t have applied to earn a PhD degree. -
Chapter 7 Packet-Switching Networks
Chapter 7 Packet-Switching Networks Network Services and Internal Network Operation Packet Network Topology Datagrams and Virtual Circuits Routing in Packet Networks Shortest Path Routing ATM Networks Traffic Management Network Layer Network Layer: the most complex layer Requires the coordinated actions of multiple, geographically distributed network elements (switches & routers) Must be able to deal with very large scales Billions of users (people & communicating devices) Biggest Challeng es Addressing: where should information be directed to? Routing: what path should be used to get information there? 1 Packet Switching t1 t0 Network Transfer of information as payload in data packets Packets undergo random delays & possible loss Different applications impose differing requirements on the transfer of information Network Service Messages Messages Transport Segments Transport layer layer Network Network service service Network Network Network Network layer layer layer layer Data link Data link Data link Data link End End layer layer layer layer system system Physical Physical β α Physical Physical layer layer layer layer Network layer can offer a variety of services to transport layer Connection-oriented service or connectionless service Best-effort or delay/loss guarantees 2 Network Service vs. Operation Network Service Internal Network Connectionless Operation Datagram Transfer Connectionless Connection-Oriented IP Reliable and possibly Connection-Oriented constant bit rate transfer Telephone connection ATM Various -
Performance Analysis of a Token Bucket Shaper for Different Communication Streams
Performance Analysis of a Token Bucket Shaper for Different Communication Streams By: Faheem, Fahd Humayun and Asif Mehmood A thesis submitted to Department of Electrical and Electronics Engineering, University of Engineering and Technology, Peshawar for the Final Year Project on “Performance Analysis of Token Bucket Shaper for Different Communication Streams.” APPROVAL CERTIFICATE This is to certify that the thesis submitted by Faheem, Fahd Humayun and Asif Mehmood is of sufficient standard to justify its acceptance by Department of Electrical and Electronics Engineering, University of Engineering and Technology Peshawar. ___________________________ Dr. Muhammad Inayatullah Khan Babar Supervisor i Abbreviations TB Token Bucket HTB Hierarchal Token Bucket DCF Distributed Coordination Function CSMA/CA Channel Sensing Multiple Access/ Collision Avoidance AP Access Point ISP Internet Service Provider QoS Quality of Source CBR Constant Bit rate VBR Variable Bit rate MPEG4 Motion Picture Experts Group Layer-4 Video UDP User Datagram Protocol TCP Transmission Control Protocol IMS IP Multimedia Subsystem TNTC Token bucket based Notification Traffic Control MBTS Measurement-Based traffic specification VOIP Voice over IP NAM Network Animator ii ABSTRACT The motive behind this thesis is to present the performance analysis of a Token Bucket Shaper for various communication streams. The study will provide a thorough insight into the Token Bucket Shaper and how its performance can be improved by adjusting its certain parameters. This study will provide an insight into how a node with Token Bucket Shaper will shape the real time traffic of MPEG4 video and real audio. This thesis will also show the effect of varying the parameters of the Token Bucket Shaper for improving its overall performance and making some trade-offs as per requirements. -
Analytical Models for the Multiplexing of Worst Case Traffic Sources and Their Application to ATM Traffic Control
Analytical Models for the Multiplexing of Worst Case Traffic Sources and their Application to ATM Traffic Control. José M. Barceló Ordinas March 5, 1998 r 9 f2 r Analytical Models for the Multiplexing of Worst Case Traffic Sources and their Application to ATM Traffic Control. José M. Barceló Ordinas This thesis has been written at Polytechnic University of Catalonia, Computer Architec- ture Department, c/ Gran Capitán, Modulo C6-E105, Barcelona E-08071, Spain, tel : + 34 3 4016798, fax : + 34 3 4017055, e-mail : josebac.upc.es This thesis has been promoted by: PhD advisor: Dr. Jorge García Vidal Universidad Politécnica de Cataluña. Spai: PhD Tutor: Prof. Dr. Olga Casals Torres Universidad Politécnica de Cataluña. Spai: Members of the PhD thesis tribunal: Prof. Dr. Chris Blondia University of Antwerp, Belgium Prof. Dr. Jorma Virtamo Telekniikan Laboratorio, Finland Prof. Dr. Vicente Casares Giner Universidad Politécnica de Valencia, Spain Dr. Josep Paradells Aspas Universidad Politécnica de Cataluña, Spain Prof. Dr. Ramon Puigjaner Trepat Universidad de les Illes Balears, Spain Contents List of Figures. List of Tables. Preface. 1 Introduction. 11 1.1 Moving towards B-ISDN 11 1.2 Controlling the ATM traffic 12 1.3 Outline 13 2 Traffic Contract and Cell Delay Variation in ATM networks. 18 2.1 Traffic Contract and ATM Transfer Capabilities 18 2.2 ATM Traffic Control and Traffic Congestion Functions 22 2.3 Ruled based traffic parameters 23 2.4 Models to quantify the CDV in ATM networks 25 2.4.1 Single queues 25 2.4.2 Tandem queues 26 2.4.3 Impact of CDV on resource allocation 27 3 Cell Delay Variation introduced in a real network. -
Chapter 7 Packet-Switching Networks
Chapter 7 Packet-Switching Networks Network Services and Internal Network Operation Packet Network Topology Datagrams and Virtual Circuits Routing in Packet Networks Shortest Path Routing ATM Networks Traffic Management Network Layer Network Layer: the most complex layer Requires the coordinated actions of multiple, geographically distributed network elements (switches & routers) Must be able to deal with very large scales Billions of users (people & communicating devices) Biggest Challenges Addressing: where should information be directed to? Routing: what path should be used to get information there? 1 Packet Switching t1 t0 Network Transfer of information as payload in data packets Packets undergo random delays & possible loss Different applications impose differing requirements on the transfer of information Network Service Messages Messages Transport Segments Transport layer layer Network Network service service Network Network Network Network layer layer layer layer Data link Data link Data link Data link End End layer layer layer layer system system Physical Physical β α Physical Physical layer layer layer layer Network layer can offer a variety of services to transport layer Connection-oriented service or connectionless service Best-effort or delay/loss guarantees 2 Network Service vs. Operation Network Service Internal Network Connectionless Operation Datagram Transfer Connectionless Connection-Oriented IP Reliable and possibly Connection-Oriented constant bit rate transfer Telephone connection ATM Various -
Flow and Congestion Control for High Speed Networks
Flow and Congestion Control For High Speed Networks Wide Area Network Prof. Taieb Znati Department Computer Science Telecommunication Program Congestion Control in High Speed Networks . The congestion control problem is more acute in high speed networks supporting QoS, than in “best-effort” networks . Faster link speeds mean that congestion can happen faster than before e.g., 64 kilobyte buffer @ 64 kbps: 8 seconds @ 10 Mbps: 52 milliseconds @ 1 Gbps: 0.52 milliseconds Buffering: A Solution? . Buffering in switches can help alleviate short term or transient congestion problems, but... Under sustained overload, buffers will still fill up, and packets will be lost Only defers the congestion problem . More buffers means more queuing delay Beyond a certain point, more buffering makes the congestion problem worse, because of increased delay and retransmission Buffering Impact on Delay . To achieve a worst-case delay of 1 second, buffer requirements increases with link speeds @ 64 kbps 8 kilobytes buffer @ 10 Mbps 1.25 Mbytes buffer @ 1 Gbps 125 Mbytes buffer Traffic Characteristics . Traffic is bursty High peak-to-mean ratio, peak rates ♦ Data traffic 10-to-1, for a peak rate of 1-10 Mbps ♦ Video traffic 20-to-1, for a peak rate 5-100 Mbps . Traffic Aggregation, through statistically multiplexing several channels Average behavior is achievable If the aggregate rate of the active traffic flows exceeds the capacity of the channels over a certain period of time, congestion is inevitable High Speed Network Traffic Control DESIGN ISSUES Traffic Control Approaches (I) . Two fundamental approaches to congestion control, reactive and preventive, are possible . Reactive feedback-based Attempt to detect congestion, or the onset of congestion, and take action to resolve the problem before things get worse .