4.7 Article

Particle swarm optimization based clustering algorithm with mobile sink for WSNs

Publisher

ELSEVIER
DOI: 10.1016/j.future.2016.08.004

Keywords

Sink mobility; Particle swarm optimization; Energy consumption; Wireless sensor network

Funding

  1. National Natural Science Foundation of China [61402234, 61402235, 61472344]
  2. Project of six personnel in Jiangsu Province [2013-WLW-012]
  3. talent project of Green Yangzhou and golden phoenix [2013-50]
  4. Industrial Strategic Technology Development Program by the Ministry of Trade, Industry and'Energy (MOTIE) Korea [10041740]
  5. Industrial Core Technology Development Program - MOTIE Korea [10049079]
  6. Korea Evaluation Institute of Industrial Technology (KEIT) [10041740] Funding Source: Korea Institute of Science & Technology Information (KISTI), National Science & Technology Information Service (NTIS)
  7. National Research Foundation of Korea [21A20131612192] Funding Source: Korea Institute of Science & Technology Information (KISTI), National Science & Technology Information Service (NTIS)

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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. (C) 2016 Elsevier B.V. All rights reserved.

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