Structures Non-Elementary Data Type • Also Known As Aggregates • Allow the Collection of Different Types of Variables Into O
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Application of TRIE Data Structure and Corresponding Associative Algorithms for Process Optimization in GRID Environment
Application of TRIE data structure and corresponding associative algorithms for process optimization in GRID environment V. V. Kashanskya, I. L. Kaftannikovb South Ural State University (National Research University), 76, Lenin prospekt, Chelyabinsk, 454080, Russia E-mail: a [email protected], b [email protected] Growing interest around different BOINC powered projects made volunteer GRID model widely used last years, arranging lots of computational resources in different environments. There are many revealed problems of Big Data and horizontally scalable multiuser systems. This paper provides an analysis of TRIE data structure and possibilities of its application in contemporary volunteer GRID networks, including routing (L3 OSI) and spe- cialized key-value storage engine (L7 OSI). The main goal is to show how TRIE mechanisms can influence de- livery process of the corresponding GRID environment resources and services at different layers of networking abstraction. The relevance of the optimization topic is ensured by the fact that with increasing data flow intensi- ty, the latency of the various linear algorithm based subsystems as well increases. This leads to the general ef- fects, such as unacceptably high transmission time and processing instability. Logically paper can be divided into three parts with summary. The first part provides definition of TRIE and asymptotic estimates of corresponding algorithms (searching, deletion, insertion). The second part is devoted to the problem of routing time reduction by applying TRIE data structure. In particular, we analyze Cisco IOS switching services based on Bitwise TRIE and 256 way TRIE data structures. The third part contains general BOINC architecture review and recommenda- tions for highly-loaded projects. -
Mod Perl 2.0 Source Code Explained 1 Mod Perl 2.0 Source Code Explained
mod_perl 2.0 Source Code Explained 1 mod_perl 2.0 Source Code Explained 1 mod_perl 2.0 Source Code Explained 15 Feb 2014 1 1.1 Description 1.1 Description This document explains how to navigate the mod_perl source code, modify and rebuild the existing code and most important: how to add new functionality. 1.2 Project’s Filesystem Layout In its pristine state the project is comprised of the following directories and files residing at the root direc- tory of the project: Apache-Test/ - test kit for mod_perl and Apache2::* modules ModPerl-Registry/ - ModPerl::Registry sub-project build/ - utilities used during project build docs/ - documentation lib/ - Perl modules src/ - C code that builds libmodperl.so t/ - mod_perl tests todo/ - things to be done util/ - useful utilities for developers xs/ - source xs code and maps Changes - Changes file LICENSE - ASF LICENSE document Makefile.PL - generates all the needed Makefiles After building the project, the following root directories and files get generated: Makefile - Makefile WrapXS/ - autogenerated XS code blib/ - ready to install version of the package 1.3 Directory src 1.3.1 Directory src/modules/perl/ The directory src/modules/perl includes the C source files needed to build the libmodperl library. Notice that several files in this directory are autogenerated during the perl Makefile stage. When adding new source files to this directory you should add their names to the @c_src_names vari- able in lib/ModPerl/Code.pm, so they will be picked up by the autogenerated Makefile. 1.4 Directory xs/ Apache2/ - Apache specific XS code APR/ - APR specific XS code ModPerl/ - ModPerl specific XS code maps/ - tables/ - Makefile.PL - 2 15 Feb 2014 mod_perl 2.0 Source Code Explained 1.4.1 xs/Apache2, xs/APR and xs/ModPerl modperl_xs_sv_convert.h - modperl_xs_typedefs.h - modperl_xs_util.h - typemap - 1.4.1 xs/Apache2, xs/APR and xs/ModPerl The xs/Apache2, xs/APR and xs/ModPerl directories include .h files which have C and XS code in them. -
Customizing and Extending Powerdesigner SAP Powerdesigner Documentation Collection Content
User Guide PUBLIC SAP PowerDesigner Document Version: 16.6.2 – 2017-01-05 Customizing and Extending PowerDesigner SAP PowerDesigner Documentation Collection Content 1 PowerDesigner Resource Files.................................................... 9 1.1 Opening Resource Files in the Editor.................................................10 1.2 Navigating and Searching in Resource Files............................................ 11 1.3 Editing Resource Files........................................................... 13 1.4 Saving Changes................................................................13 1.5 Sharing and Embedding Resource Files...............................................13 1.6 Creating and Copying Resource Files.................................................14 1.7 Specifying Directories to Search for Resource Files.......................................15 1.8 Comparing Resource Files........................................................ 15 1.9 Merging Resource Files.......................................................... 16 2 Extension Files................................................................18 2.1 Creating an Extension File.........................................................19 2.2 Attaching Extensions to a Model....................................................20 2.3 Exporting an Embedded Extension File for Sharing.......................................21 2.4 Extension File Properties......................................................... 21 2.5 Example: Adding a New Attribute from a Property -
C Programming: Data Structures and Algorithms
C Programming: Data Structures and Algorithms An introduction to elementary programming concepts in C Jack Straub, Instructor Version 2.07 DRAFT C Programming: Data Structures and Algorithms, Version 2.07 DRAFT C Programming: Data Structures and Algorithms Version 2.07 DRAFT Copyright © 1996 through 2006 by Jack Straub ii 08/12/08 C Programming: Data Structures and Algorithms, Version 2.07 DRAFT Table of Contents COURSE OVERVIEW ........................................................................................ IX 1. BASICS.................................................................................................... 13 1.1 Objectives ...................................................................................................................................... 13 1.2 Typedef .......................................................................................................................................... 13 1.2.1 Typedef and Portability ............................................................................................................. 13 1.2.2 Typedef and Structures .............................................................................................................. 14 1.2.3 Typedef and Functions .............................................................................................................. 14 1.3 Pointers and Arrays ..................................................................................................................... 16 1.4 Dynamic Memory Allocation ..................................................................................................... -
Typedef in C
CC -- TTYYPPEEDDEEFF http://www.tutorialspoint.com/cprogramming/c_typedef.htm Copyright © tutorialspoint.com The C programming language provides a keyword called typedef, which you can use to give a type a new name. Following is an example to define a term BYTE for one-byte numbers: typedef unsigned char BYTE; After this type definitions, the identifier BYTE can be used as an abbreviation for the type unsigned char, for example:. BYTE b1, b2; By convention, uppercase letters are used for these definitions to remind the user that the type name is really a symbolic abbreviation, but you can use lowercase, as follows: typedef unsigned char byte; You can use typedef to give a name to user defined data type as well. For example you can use typedef with structure to define a new data type and then use that data type to define structure variables directly as follows: #include <stdio.h> #include <string.h> typedef struct Books { char title[50]; char author[50]; char subject[100]; int book_id; } Book; int main( ) { Book book; strcpy( book.title, "C Programming"); strcpy( book.author, "Nuha Ali"); strcpy( book.subject, "C Programming Tutorial"); book.book_id = 6495407; printf( "Book title : %s\n", book.title); printf( "Book author : %s\n", book.author); printf( "Book subject : %s\n", book.subject); printf( "Book book_id : %d\n", book.book_id); return 0; } When the above code is compiled and executed, it produces the following result: Book title : C Programming Book author : Nuha Ali Book subject : C Programming Tutorial Book book_id : 6495407 typedef vs #define The #define is a C-directive which is also used to define the aliases for various data types similar to typedef but with following differences: The typedef is limited to giving symbolic names to types only where as #define can be used to define alias for values as well, like you can define 1 as ONE etc. -
Abstract Data Types
Chapter 2 Abstract Data Types The second idea at the core of computer science, along with algorithms, is data. In a modern computer, data consists fundamentally of binary bits, but meaningful data is organized into primitive data types such as integer, real, and boolean and into more complex data structures such as arrays and binary trees. These data types and data structures always come along with associated operations that can be done on the data. For example, the 32-bit int data type is defined both by the fact that a value of type int consists of 32 binary bits but also by the fact that two int values can be added, subtracted, multiplied, compared, and so on. An array is defined both by the fact that it is a sequence of data items of the same basic type, but also by the fact that it is possible to directly access each of the positions in the list based on its numerical index. So the idea of a data type includes a specification of the possible values of that type together with the operations that can be performed on those values. An algorithm is an abstract idea, and a program is an implementation of an algorithm. Similarly, it is useful to be able to work with the abstract idea behind a data type or data structure, without getting bogged down in the implementation details. The abstraction in this case is called an \abstract data type." An abstract data type specifies the values of the type, but not how those values are represented as collections of bits, and it specifies operations on those values in terms of their inputs, outputs, and effects rather than as particular algorithms or program code. -
PL/SQL Data Types
PPLL//SSQQLL -- DDAATTAA TTYYPPEESS http://www.tutorialspoint.com/plsql/plsql_data_types.htm Copyright © tutorialspoint.com PL/SQL variables, constants and parameters must have a valid data type, which specifies a storage format, constraints, and valid range of values. This tutorial will take you through SCALAR and LOB data types available in PL/SQL and other two data types will be covered in other chapters. Category Description Scalar Single values with no internal components, such as a NUMBER, DATE, or BOOLEAN. Large Object LOB Pointers to large objects that are stored separately from other data items, such as text, graphic images, video clips, and sound waveforms. Composite Data items that have internal components that can be accessed individually. For example, collections and records. Reference Pointers to other data items. PL/SQL Scalar Data Types and Subtypes PL/SQL Scalar Data Types and Subtypes come under the following categories: Date Type Description Numeric Numeric values on which arithmetic operations are performed. Character Alphanumeric values that represent single characters or strings of characters. Boolean Logical values on which logical operations are performed. Datetime Dates and times. PL/SQL provides subtypes of data types. For example, the data type NUMBER has a subtype called INTEGER. You can use subtypes in your PL/SQL program to make the data types compatible with data types in other programs while embedding PL/SQL code in another program, such as a Java program. PL/SQL Numeric Data Types and Subtypes Following -
5. Data Types
IEEE FOR THE FUNCTIONAL VERIFICATION LANGUAGE e Std 1647-2011 5. Data types The e language has a number of predefined data types, including the integer and Boolean scalar types common to most programming languages. In addition, new scalar data types (enumerated types) that are appropriate for programming, modeling hardware, and interfacing with hardware simulators can be created. The e language also provides a powerful mechanism for defining OO hierarchical data structures (structs) and ordered collections of elements of the same type (lists). The following subclauses provide a basic explanation of e data types. 5.1 e data types Most e expressions have an explicit data type, as follows: — Scalar types — Scalar subtypes — Enumerated scalar types — Casting of enumerated types in comparisons — Struct types — Struct subtypes — Referencing fields in when constructs — List types — The set type — The string type — The real type — The external_pointer type — The “untyped” pseudo type Certain expressions, such as HDL objects, have no explicit data type. See 5.2 for information on how these expressions are handled. 5.1.1 Scalar types Scalar types in e are one of the following: numeric, Boolean, or enumerated. Table 17 shows the predefined numeric and Boolean types. Both signed and unsigned integers can be of any size and, thus, of any range. See 5.1.2 for information on how to specify the size and range of a scalar field or variable explicitly. See also Clause 4. 5.1.2 Scalar subtypes A scalar subtype can be named and created by using a scalar modifier to specify the range or bit width of a scalar type. -
Enum, Typedef, Structures and Unions CS 2022: Introduction to C
Enum, Typedef, Structures and Unions CS 2022: Introduction to C Instructor: Hussam Abu-Libdeh Cornell University (based on slides by Saikat Guha) Fall 2009, Lecture 6 Enum, Typedef, Structures and Unions CS 2022, Fall 2009, Lecture 6 Numerical Types I int: machine-dependent I Standard integers I defined in stdint.h (#include <stdint.h>) I int8 t: 8-bits signed I int16 t: 16-bits signed I int32 t: 32-bits signed I int64 t: 64-bits signed I uint8 t, uint32 t, ...: unsigned I Floating point numbers I float: 32-bits I double: 64-bits Enum, Typedef, Structures and Unions CS 2022, Fall 2009, Lecture 6 Complex Types I Enumerations (user-defined weekday: sunday, monday, ...) I Structures (user-defined combinations of other types) I Unions (same data, multiple interpretations) I Function pointers I Arrays and Pointers of the above Enum, Typedef, Structures and Unions CS 2022, Fall 2009, Lecture 6 Enumerations enum days {mon, tue, wed, thu, fri, sat, sun}; // Same as: // #define mon 0 // #define tue 1 // ... // #define sun 6 enum days {mon=3, tue=8, wed, thu, fri, sat, sun}; // Same as: // #define mon 3 // #define tue 8 // ... // #define sun 13 Enum, Typedef, Structures and Unions CS 2022, Fall 2009, Lecture 6 Enumerations enum days day; // Same as: int day; for(day = mon; day <= sun; day++) { if (day == sun) { printf("Sun\n"); } else { printf("day = %d\n", day); } } Enum, Typedef, Structures and Unions CS 2022, Fall 2009, Lecture 6 Enumerations I Basically integers I Can use in expressions like ints I Makes code easier to read I Cannot get string equiv. -
Data Structures, Buffers, and Interprocess Communication
Data Structures, Buffers, and Interprocess Communication We’ve looked at several examples of interprocess communication involving the transfer of data from one process to another process. We know of three mechanisms that can be used for this transfer: - Files - Shared Memory - Message Passing The act of transferring data involves one process writing or sending a buffer, and another reading or receiving a buffer. Most of you seem to be getting the basic idea of sending and receiving data for IPC… it’s a lot like reading and writing to a file or stdin and stdout. What seems to be a little confusing though is HOW that data gets copied to a buffer for transmission, and HOW data gets copied out of a buffer after transmission. First… let’s look at a piece of data. typedef struct { char ticker[TICKER_SIZE]; double price; } item; . item next; . The data we want to focus on is “next”. “next” is an object of type “item”. “next” occupies memory in the process. What we’d like to do is send “next” from processA to processB via some kind of IPC. IPC Using File Streams If we were going to use good old C++ filestreams as the IPC mechanism, our code would look something like this to write the file: // processA is the sender… ofstream out; out.open(“myipcfile”); item next; strcpy(next.ticker,”ABC”); next.price = 55; out << next.ticker << “ “ << next.price << endl; out.close(); Notice that we didn’t do this: out << next << endl; Why? Because the “<<” operator doesn’t know what to do with an object of type “item”. -
Chapter 5: Substitutes for C Constructs
CHAPTER 5 Substitutes for C Constructs THE Java programming language shares many similarities with the C program- ming language, but several C constructs have been omitted. In most cases, it’s obvi- ous why a C construct was omitted and how to make do without it. This chapter suggests replacements for several omitted C constructs whose replacements are not so obvious. The common thread that connects the items in this chapter is that all of the omitted constructs are data-oriented rather than object-oriented. The Java pro- gramming language provides a powerful type system, and the suggested replace- ments take full advantage of that type system to deliver a higher quality abstraction than the C constructs they replace. Even if you choose to skip this chapter, it’s probably worth reading Item 21, which discusses the typesafe enum pattern, a replacement for C’s enum construct. This pattern is not widely known at the time of this writing, and it has several advan- tages over the methods currently in common use. Item 19: Replace structures with classes The C struct construct was omitted from the Java programming language because a class does everything a structure does and more. A structure merely groups multi- ple data fields into a single object; a class associates operations with the resulting object and allows the data fields to be hidden from users of the object. In other words, a class can encapsulate its data into an object that is accessed solely by its methods, allowing the implementor the freedom to change the representation over time (Item 12). -
Evaluation of On-Ramp Control Algorithms
CALIFORNIA PATH PROGRAM INSTITUTE OF TRANSPORTATION STUDIES UNIVERSITY OF CALIFORNIA, BERKELEY Evaluation of On-ramp Control Algorithms Michael Zhang, Taewan Kim, Xiaojian Nie, Wenlong Jin University of California, Davis Lianyu Chu, Will Recker University of California, Irvine California PATH Research Report UCB-ITS-PRR-2001-36 This work was performed as part of the California PATH Program of the University of California, in cooperation with the State of California Business, Transportation, and Housing Agency, Department of Transportation; and the United States Department of Transportation, Federal Highway Administration. The contents of this report reflect the views of the authors who are responsible for the facts and the accuracy of the data presented herein. The contents do not necessarily reflect the official views or policies of the State of California. This report does not constitute a standard, specification, or regulation. Final Report for MOU 3013 December 2001 ISSN 1055-1425 CALIFORNIA PARTNERS FOR ADVANCED TRANSIT AND HIGHWAYS Evaluation of On-ramp Control Algorithms September 2001 Michael Zhang, Taewan Kim, Xiaojian Nie, Wenlong Jin University of California at Davis Lianyu Chu, Will Recker PATH Center for ATMS Research University of California, Irvine Institute of Transportation Studies One Shields Avenue University of California, Davis Davis, CA 95616 ACKNOWLEDGEMENTS Technical assistance on Paramics simulation from the Quadstone Technical Support sta is also gratefully acknowledged. ii EXECUTIVE SUMMARY This project has three objectives: 1) review existing ramp metering algorithms and choose a few attractive ones for further evaluation, 2) develop a ramp metering evaluation framework using microscopic simulation, and 3) compare the performances of the selected algorithms and make recommendations about future developments and eld tests of ramp metering systems.