A Review of Metaheuristic Optimization Algorithms in Wireless Sensor Networks

Essam H. Houssein, Mohammed R. Saad, Kashif Hussain, Hassan Shaban, M. Hassaballah

Research output: Chapter in Book/Report/Published conference proceedingChapter


The proliferation of wireless sensor network (WSNs) applications span different domains of life, including medicine, engineering, industry, agriculture, and military. A notable part of research pertaining to WSNs relates to metaheuristic algorithms, implemented to address difficulties in the deployment of these networks. Due to robust and cost effective optimization ability, these algorithms efficiently optimize sensor locations for maximum coverage and extended energy consumption. This chapter presents the definitions of metaheuristic intelligence, wireless sensor network, and their respective types. Also, a wide range of scientific research works that include improving the performance of wireless sensor networks in terms of deployment, localization, and energy using optimization algorithms. Finally, the evaluation criteria for deployment and localization in wireless sensor networks are introduced.
Original languageEnglish
Title of host publicationMetaheuristics in Machine Learning: Theory and Applications
EditorsDiego Oliva, Essam H. Houssein, Salvador Hinojosa
Place of PublicationCham
PublisherSpringer International Publishing AG
Number of pages25
ISBN (Electronic)978-3-030-70542-8
ISBN (Print)978-3-030-70541-1
Publication statusPublished - 14 Jul 2021

Publication series

NameStudies in Computational Intelligence

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