Description

Book Synopsis

Wireless Sensor Networks have a wide range of applications in different areas. Their main constraint is the limited and irreplaceable power source of the sensor nodes. In many applications, energy conservation of the sensor nodes and their replacement or replenishment due to the hostile nature of the environment is the most challenging issue. Energy efficient clustering and routing are the two main important topics studied extensively for this purpose. This book focuses on the energy efficient clustering and routing with a great emphasis on the evolutionary approaches. It provides a comprehensive and systematic introduction of the fundamentals of WSNs, major issues and effective solutions.



Table of Contents

Introduction. A Survey. Meta-heuristic Approaches. Approximation Algorithms for Clustering. Heap and Parameter based Clustering. Genetic Algorithm and Differential Evolution based Clustering. Particle Swarm Optimization for Clustering and Routing. Distributed Clustering and Routing Algorithm.

Clustering and Routing Algorithms for Wireless

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    A Hardback by Prasanta K Jana, Prasanta K Jana

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      Publisher: Taylor & Francis Inc
      Publication Date: Publication Date: 1/20/2017 12:09:00 AM
      ISBN13: 9781498753821, 978-1498753821
      ISBN10: 1498753825

      Description

      Book Synopsis

      Wireless Sensor Networks have a wide range of applications in different areas. Their main constraint is the limited and irreplaceable power source of the sensor nodes. In many applications, energy conservation of the sensor nodes and their replacement or replenishment due to the hostile nature of the environment is the most challenging issue. Energy efficient clustering and routing are the two main important topics studied extensively for this purpose. This book focuses on the energy efficient clustering and routing with a great emphasis on the evolutionary approaches. It provides a comprehensive and systematic introduction of the fundamentals of WSNs, major issues and effective solutions.



      Table of Contents

      Introduction. A Survey. Meta-heuristic Approaches. Approximation Algorithms for Clustering. Heap and Parameter based Clustering. Genetic Algorithm and Differential Evolution based Clustering. Particle Swarm Optimization for Clustering and Routing. Distributed Clustering and Routing Algorithm.

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