Guide to Graph Algorithms, 1st ed. 2018
Sequential, Parallel and Distributed

Texts in Computer Science Series

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Language: Anglais

74.56 €

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473 p. · 15.5x23.5 cm · Hardback
This clearly structured textbook/reference presents a detailed and comprehensive review of the fundamental principles of sequential graph algorithms, approaches for NP-hard graph problems, and approximation algorithms and heuristics for such problems. The work also provides a comparative analysis of sequential, parallel and distributed graph algorithms – including algorithms for big data – and an investigation into the conversion principles between the three algorithmic methods.

Topics and features:
- Presents a comprehensive analysis of sequential graph algorithms
- Offers a unifying view by examining the same graph problem from each of the three paradigms of sequential, parallel and distributed algorithms
- Describes methods for the conversion between sequential, parallel and distributed graph algorithms
- Surveys methods for the analysis of large graphs and complex network applications
- Includes full implementation details for the problems presented throughout the text
- Provides additional supporting material at an accompanying website

This practical guide to the design and analysis of graph algorithms is ideal for advanced and graduate students of computer science, electrical and electronic engineering, and bioinformatics. The material covered will also be of value to any researcher familiar with the basics of discrete mathematics, graph theory and algorithms.

Introduction

Part I: Fundamentals

Introduction to Graphs

Graph Algorithms

Parallel Graph Algorithms

Distributed Graph Algorithms

Part II: Basic Graph Algorithms

Trees and Graph Traversals

Weighted Graphs

Connectivity

Matching

Independence, Domination and Vertex Cover

Coloring

Part III: Advanced Topics

Algebraic and Dynamic Graph Algorithms

Analysis of Large Graphs

Complex Networks

Epilogue

Appendix A: Pseudocode Conventions

Appendix B: Linear Algebra Review

Dr. K. Erciyes is an Emeritus Professor of Computer Engineering at Ege University, Turkey. His other publications include the Springer titles Distributed Graph Algorithms for Computer Networks and Distributed and Sequential Algorithms for Bioinformatics.
Presents detailed coverage of sequential graph algorithms, together with some sample parallel and distributed graph algorithm design methods - Provides a comparative analysis of the three methods of sequential, parallel and distributed graph algorithms - Describes techniques for conversion between the different methods