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Wireless Networks: Applications, Challenges, and Security Issues Read chapter Read first chapter

2021 | OriginalPaper | Chapter

Wireless Sensor Network Routing Protocols Using Machine Learning

Authors : Chaya Shivalingagowda, Hifzan Ahmad, P. V. Y. Jayasree, Dinesh Kumar Sah

Published in: Architectural Wireless Networks Solutions and Security Issues

Publisher: Springer Singapore

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Abstract

Routing is a predominant challenge in the field of WSNs because of insufficient power supply in each node. And low-transmission bandwidth required less memory space and handling limit. These sensors distributed randomly in nature and the environment, and each sensor nodes gather data from that environment for further analysis and additional processing and transmits the information and data to the base station. We discussed the different machine learning algorithms to develop routing protocols for the WSNs. These technologies have allowed the sensor to learn the experience data to make appropriate routing decisions and respond to changing the environment. We covered a wide range of machine learning (ML)-based routing protocols, such as distributed regression (DR), self-organizing map (SOM), and reinforcement learning (RL). This chapter affords a complete evaluation of the literature on the topic. The review has structured in such a way that suggests how network characteristics and necessities gradually viewed over time.

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previous chapter Fuzzy Rule-Based System for Route Selection in WSN Using Quadratic Programming
next chapter Distributed Traversal Based Fault Diagnosis for Wireless Sensor Network
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Metadata
Title
Wireless Sensor Network Routing Protocols Using Machine Learning
Authors
Chaya Shivalingagowda
Hifzan Ahmad
P. V. Y. Jayasree
Dinesh Kumar Sah
Copyright Year
2021
Publisher
Springer Singapore
Book
Architectural Wireless Networks Solutions and Security Issues

Print ISBN: 978-981-16-0385-3

Electronic ISBN: 978-981-16-0386-0

Copyright Year: 2021

DOI
https://doi.org/10.1007/978-981-16-0386-0_7