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Distributed Graph Algorithms for Computer Networks

Kayhan Erciyes
Livre relié | Anglais | Computer Communications and Networks
152,95 €
+ 305 points
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Description

Graph theory is an invaluable tool for the designer of algorithms for distributed systems.

This hands-on textbook/reference presents a comprehensive review of key distributed graph algorithms for computer network applications, with a particular emphasis on practical implementation. Each chapter opens with a concise introduction to a specific problem, supporting the theory with numerous examples, before providing a list of relevant algorithms. These algorithms are described in detail from conceptual basis to pseudocode, complete with graph templates for the stepwise implementation of the algorithm, followed by its analysis. The chapters then conclude with summarizing notes and programming exercises.

Topics and features: introduces a range of fundamental graph algorithms, covering spanning trees, graph traversal algorithms, routing algorithms, and self-stabilization; reviews graph-theoretical distributed approximation algorithms with applications in ad hoc wireless networks; describes in detail the implementation of each algorithm, with extensive use of supporting examples, and discusses their concrete network applications; examines key graph-theoretical algorithm concepts, such as dominating sets, and parameters for mobility and energy levels of nodes in wireless ad hoc networks, and provides a contemporary survey of each topic; presents a simple simulator, developed to run distributed algorithms; provides practical exercises at the end of each chapter.

This classroom-tested and easy-to-follow textbook is essential reading for all graduate students and researchers interested in discrete mathematics, algorithms and computer networks.

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Editeur:

Contenu

Nombre de pages :
324
Langue:
Anglais
Collection :

Caractéristiques

EAN:
9781447151722
Date de parution :
04-06-13
Format:
Livre relié
Format numérique:
Genaaid
Dimensions :
156 mm x 234 mm
Poids :
657 g

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