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Nature Inspired Computing for Wireless Sensor Networks

  • Debashis De
  • Amartya Mukherjee
  • Santosh Kumar Das
  • Nilanjan Dey
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Part of the Springer Tracts in Nature-Inspired Computing book series (STNIC)

Table of contents

  1. Front Matter
    Pages i-xiv
  2. Debashis De, Amartya Mukherjee, Santosh Kumar Das, Nilanjan Dey
    Pages 1-18
  3. Bio-inspired Optimization

    1. Front Matter
      Pages 19-19
    2. Kanhu Charan Gouda, Santosh Kumar Das, Om Prakash Dubey, Efrén Mezura Montes
      Pages 57-75
    3. Meenakshi Panda, Bhabani Sankar Gouda, Trilochan Panigrahi
      Pages 77-101
    4. Santoshinee Mohapatra, Pabitra Mohan Khilar
      Pages 103-116
  4. Swarm Optimization

  5. Multi-objective Optimization

About this book

Introduction

This book presents nature inspired computing applications for the wireless sensor network (WSN). Although the use of WSN is increasing rapidly, it has a number of limitations in the context of battery issue, distraction, low communication speed, and security. This means there is a need for innovative intelligent algorithms to address these issues.
The book is divided into three sections and also includes an introductory chapter providing an overview of WSN and its various applications and algorithms as well as the associated challenges. Section 1 describes bio-inspired optimization algorithms, such as genetic algorithms (GA), artificial neural networks (ANN) and artificial immune systems (AIS) in the contexts of fault analysis and diagnosis, and traffic management. Section 2 highlights swarm optimization techniques, such as African buffalo optimization (ABO), particle swarm optimization (PSO), and modified swarm intelligence technique for solving the problems of routing, network parameters optimization, and energy estimation. Lastly, Section 3 explores multi-objective optimization techniques using GA, PSO, ANN, teaching–learning-based optimization (TLBO), and combinations of the algorithms presented. As such, the book provides efficient and optimal solutions for WSN problems based on nature-inspired algorithms.

Keywords

Intelligent Sensor Wireless Sensor Network Ubiquitous Sensing Nature Inspired Sensing Cyber Physical System

Editors and affiliations

  • Debashis De
    • 1
  • Amartya Mukherjee
    • 2
  • Santosh Kumar Das
    • 3
  • Nilanjan Dey
    • 4
  1. 1.Department of Computer Science and EngineeringMaulana Abul Kalam Azad UniversityKolkataIndia
  2. 2.Department of Computer Science and EngineeringInstitute of Engineering and ManagementKolkataIndia
  3. 3.School of Computer Science and EngineeringNational Institute of Science and TechnologyBerhampurIndia
  4. 4.Department of Information TechnologyTechno India College of TechnologyKolkataIndia

Bibliographic information

  • DOI https://doi.org/10.1007/978-981-15-2125-6
  • Copyright Information Springer Nature Singapore Pte Ltd. 2020
  • Publisher Name Springer, Singapore
  • eBook Packages Engineering
  • Print ISBN 978-981-15-2124-9
  • Online ISBN 978-981-15-2125-6
  • Series Print ISSN 2524-552X
  • Series Online ISSN 2524-5538
  • Buy this book on publisher's site