Nature inspired computing for wireless sensor networks / Debashis De, Amartya Mukherjee, Santosh Kumar Das, Nilanjan Dey, editors.
De, Debashis.; Mukherjee, Amartya.; Das, Santosh Kumar.; Dey, Nilanjan, 1984-
2020
TK7872.D48
Available Online

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Title Nature inspired computing for wireless sensor networks / Debashis De, Amartya Mukherjee, Santosh Kumar Das, Nilanjan Dey, editors.
ISBN 9789811521256 (electronic book)
9811521255 (electronic book)
9811521247
9789811521249
Publication Details Sinagpore : Springer, 2020.
Language English
Description 1 online resource
Call Number TK7872.D48
Dewey Decimal Classification 006.2/5
Summary 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.
Access Note Access limited to authorized users.
Added Author De, Debashis.
Mukherjee, Amartya.
Das, Santosh Kumar.
Dey, Nilanjan, 1984-
Series Springer tracts in nature-inspired computing.
Available in Other Form Print version: 9789811521249
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Wireless Sensor Network: Applications, Challenges and Algorithms
Section 1: Bio-Inspired Optimization
A GA based Fault-Aware Routing Algorithm for Wireless Sensor Networks
GA based Fault Diagnosis Technique for Enhancing Network Lifetime of Wireless Sensor Network
A GA based Intelligent Traffic Management Technique for Wireless Body Area Sensor Networks
Fault Diagnosis in Wireless Sensor Networks using a Neural Network Constructed by Deep Learning Technique
Section 2: Swarm Optimization
Intelligent Routing in Wireless Sensor Network based on African Buffalo Optimization
Robust Estimation of Feedback Systems Parameter in Wireless Sensor Network using Distributed Particle Swarm Optimization
On the Development of Energy Efficient Distributed Source Localization Algorithm in Wireless Sensor Networks using Modified Swarm Intelligence
Swarm Intelligence Approach for Ad-Hoc & Sensor Networks
Section 3: Multi-Objective Optimization
A Comparensive Survey of Intelligent-based Hierarchical Routing Protocols for Wireless Sensor Networks
A Qualitative Survey on Sensor Node Deployment, Load Balancing & Energy Utilization in Sensor Network
Bio-Inspired Algorithm for Multi-Objective Optimization in Wireless Sensor Network
TLBO based Multi-objective Optimization System in Wireless Sensor Networks
Nature Inspired Algorithms for Reliable, Low-Latency Communication in Wireless Sensor Networks for Pervasive Healthcare Applications.

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