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International Journal of Machine Learning and Cybernetics
Erschienen in: International Journal of Machine Learning and Cybernetics 9/2020

28.02.2020 | Original Article

An evolution strategy based approach for cover scheduling problem in wireless sensor networks

verfasst von: Gaurav Srivastava, Pandiri Venkatesh, Alok Singh

Erschienen in: International Journal of Machine Learning and Cybernetics | Ausgabe 9/2020

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Abstract

Cover scheduling problem in wireless sensor networks (WSN-CSP) aims to find a schedule of covers which minimizes the longest continuous duration of time for which no sensor in the network is able to monitor a target. This problem arises in those sensing environments which permit the coverage breach, i.e., at any instant of time, all targets need not be monitored. The coverage breach may occur owing to either technical restrictions or intentionally. It is an \(\mathcal {NP}\)-hard problem. This paper presents a \((1 + 1)\)-evolution strategy based approach to address WSN-CSP problem. We have compared our approach with the state-of-art approaches available in literature. Computational results show that our approach is significantly superior in comparison to the existing approaches for WSN-CSP.
Vorheriger Artikel Fully-connected LSTM–CRF on medical concept extraction
Nächster Artikel Extreme learning machine with hybrid cost function of G-mean and probability for imbalance learning

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Metadaten
Titel
An evolution strategy based approach for cover scheduling problem in wireless sensor networks
verfasst von
Gaurav Srivastava
Pandiri Venkatesh
Alok Singh
Publikationsdatum
28.02.2020
Verlag
Springer Berlin Heidelberg
Erschienen in
International Journal of Machine Learning and Cybernetics / Ausgabe 9/2020
Print ISSN: 1868-8071
Elektronische ISSN: 1868-808X
DOI
https://doi.org/10.1007/s13042-020-01088-5

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