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Erschienen in:
Wireless Sensor Network: Applications, Challenges, and Algorithms Kapitel lesen Erstes Kapitel lesen

2020 | OriginalPaper | Buchkapitel

6. Immune Inspired Fault Diagnosis in Wireless Sensor Network

verfasst von : Santoshinee Mohapatra, Pabitra Mohan Khilar

Erschienen in: Nature Inspired Computing for Wireless Sensor Networks

Verlag: Springer Singapore

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Abstract

Scientist and researchers have shown higher interest in the development of biologically inspired algorithms in recent years, to solve multiple complex computational problems. Different solutions were proposed by various authors using artificial immune system (AIS), ant colony optimization (ACO), particle swarm optimization (PSO), artificial bee colony (ABC) algorithm, and genetic algorithm (GA). Fault diagnosis in wireless sensor network (WSN) is very crucial because of the application where it is used. The issue of fault diagnosis in wireless sensor network can be comparable in many aspects with an artificial immune system. Different approaches to artificial immune system have been discussed in this chapter that can be applied to fault diagnosis of wireless sensor network. An overall view of the biological immune system is explained in detail. Different artificial immune system’s applications are also discussed.

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Vorheriges Kapitel Fault Diagnosis in Wireless Sensor Networks Using a Neural Network Constructed by Deep Learning Technique
Nächstes Kapitel Intelligent Routing in Wireless Sensor Network Based on African Buffalo Optimization
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Metadaten
Titel
Immune Inspired Fault Diagnosis in Wireless Sensor Network
verfasst von
Santoshinee Mohapatra
Pabitra Mohan Khilar
Copyright-Jahr
2020
Verlag
Springer Singapore
Buch
Nature Inspired Computing for Wireless Sensor Networks

Print ISBN: 978-981-15-2124-9

Electronic ISBN: 978-981-15-2125-6

Copyright-Jahr: 2020

DOI
https://doi.org/10.1007/978-981-15-2125-6_6

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