KSII Transactions on Internet and Information Systems (TIIS)

Korean Society for Internet Information (한국인터넷정보학회)
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A Rendezvous Node Selection and Routing Algorithm for Mobile Wireless Sensor Network

  • Hu, Yifan (Institute of Oceanographic Instrumentation, Qilu University of Technology (Shandong Academy of Sciences)) ;
  • Zheng, Yi (Institute of Oceanographic Instrumentation, Qilu University of Technology (Shandong Academy of Sciences)) ;
  • Wu, Xiaoming (Qilu University of Technology (Shandong Academy of Sciences), Shandong Computer Science Center (National Supercomputer Center in Jinan), Shandong Provincial Key Laboratory of Computer Networks) ;
  • Liu, Hailin (Institute of Oceanographic Instrumentation, Qilu University of Technology (Shandong Academy of Sciences))
  • Received : 2017.08.10
  • Accepted : 2018.05.31
  • Published : 2018.10.31
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Abstract

Efficient rendezvous node selection and routing algorithm (RNSRA) for wireless sensor networks with mobile sink that visits rendezvous node to gather data from sensor nodes is proposed. In order to plan an optimal moving tour for mobile sink and avoid energy hole problem, we develop the RNSRA to find optimal rendezvous nodes (RN) for the mobile sink to visit. The RNSRA can select the set of RNs to act as store points for the mobile sink, and search for the optimal multi-hop path between source nodes and rendezvous node, so that the rendezvous node could gather information from sensor nodes periodically. Fitness function with several factors is calculated to find suitable RNs from sensor nodes, and the artificial bee colony optimization algorithm (ABC) is used to optimize the selection of optimal multi-hop path, in order to forward data to the nearest RN. Therefore the energy consumption of sensor nodes is minimized and balanced. Our method is validated by extensive simulations and illustrates the novel capability for maintaining the network robustness against sink moving problem, the results show that the RNSRA could reduce energy consumption by 6% and increase network lifetime by 5% as comparing with several existing algorithms.

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References

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