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Natural Computing

Erschienen in:

14.09.2015

An improved dynamic deployment method for wireless sensor network based on multi-swarm particle swarm optimization

verfasst von: Qingjian Ni, Huimin Du, Qianqian Pan, Cen Cao, Yuqing Zhai

Erschienen in: Natural Computing | Ausgabe 1/2017

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Abstract

Dynamic deployment methods for wireless sensor network (WSN) can improve the quality of service (QoS) of the network by adjusting positions of mobile nodes. In the dynamic deployment problem model of this paper, not only the coverage rate of WSN but also the moving distance of mobile nodes is taken into consideration. This kind of model can be abstracted into multi-objective optimization problem, and particle swarm optimization (PSO) is introduced to solve this problem. In this paper, combined with previous work, an improved dynamic deployment method is proposed based on multi-swarm PSO. Specifically, we propose a discrete PSO to calculate the distance of mobile solutions, and a multi-swarm PSO is designed to optimize network performance for enhancing the QoS of deployment which includes higher coverage rate and lower energy consumption of mobile nodes. Experimental results demonstrate that the proposed method has a good performance in solving the WSN deployment problem.

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Titel: An improved dynamic deployment method for wireless sensor network based on multi-swarm particle swarm optimization
verfasst von: Qingjian Ni
Huimin Du
Qianqian Pan
Cen Cao
Yuqing Zhai
Publikationsdatum: 14.09.2015
Verlag: Springer Netherlands
Erschienen in: Natural Computing / Ausgabe 1/2017
Print ISSN: 1567-7818
Elektronische ISSN: 1572-9796
DOI: https://doi.org/10.1007/s11047-015-9519-0

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