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Neural Processing Letters
Erschienen in: Neural Processing Letters 1/2018

08.09.2017

Sensor Deployment Scheme Based on Social Spider Optimization Algorithm for Wireless Sensor Networks

verfasst von: Yongquan Zhou, Ruxin Zhao, Qifang Luo, Chunming Wen

Erschienen in: Neural Processing Letters | Ausgabe 1/2018

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Abstract

Wireless sensor networks (WSNs) consist of large numbers of micro-sensor nodes that have both communication and computing capabilities. The size of the coverage area of each sensor node determines the overall performance of the WSN. In this paper, a novel sensor deployment scheme based on the social spider optimization (SSO) algorithm is proposed to enable increased coverage for WSNs. In the SSO algorithm, the individual simulated social spiders’ habits and their labor and cooperation efforts are divided according to gender differences. Simulations experiment are used to demonstrate the effectiveness of the proposed method.
Vorheriger Artikel Pruning the Ensemble of ANN Based on Decision Tree Induction
Nächster Artikel Temperature-Based Deep Boltzmann Machines

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Metadaten
Titel
Sensor Deployment Scheme Based on Social Spider Optimization Algorithm for Wireless Sensor Networks
verfasst von
Yongquan Zhou
Ruxin Zhao
Qifang Luo
Chunming Wen
Publikationsdatum
08.09.2017
Verlag
Springer US
Erschienen in
Neural Processing Letters / Ausgabe 1/2018
Print ISSN: 1370-4621
Elektronische ISSN: 1573-773X
DOI
https://doi.org/10.1007/s11063-017-9701-8

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