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Particle swarm optimization based clustering algorithm with mobile sink for WSNs

Citation

Wang, J and Cao, Y and Li, B and Kim, H-J and Lee, S, Particle swarm optimization based clustering algorithm with mobile sink for WSNs, Future Generation Computer Systems, 76 pp. 452-457. ISSN 0167-739X (2016) [Refereed Article]

Copyright Statement

Copyright 2016 Elsevier B.V.

DOI: doi:10.1016/j.future.2016.08.004

Abstract

Wireless sensor networks with fixed sink node often suffer from hot spots problem since sensor nodes close to the sink usually have more traffic burden to forward during transmission process. Utilizing mobile sink has been shown as an effective technique to enhance the network performance such as energy efficiency, network lifetime, and latency, etc. In this paper, we propose a particle swarm optimization based clustering algorithm with mobile sink for wireless sensor network. In this algorithm, the virtual clustering technique is performed during routing process which makes use of the particle swarm optimization algorithm. The residual energy and position of the nodes are the primary parameters to select cluster head. The control strategy for mobile sink to collect data from cluster head is well designed. Extensive simulation results show that the energy consumption is much reduced, the network lifetime is prolonged, and the transmission delay is reduced in our proposed routing algorithm than some other popular routing algorithms.

Item Details

Item Type:Refereed Article
Keywords:sink mobility, particle swarm optimization, energy consumption, wireless sensor network
Research Division:Information and Computing Sciences
Research Group:Distributed computing and systems software
Research Field:Distributed systems and algorithms
Objective Division:Information and Communication Services
Objective Group:Communication technologies, systems and services
Objective Field:Network systems and services
UTAS Author:Lee, S (Professor Sungyoung Lee)
ID Code:122924
Year Published:2016
Web of Science® Times Cited:149
Deposited By:Information and Communication Technology
Deposited On:2017-12-06
Last Modified:2018-04-04
Downloads:0

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