Ad Hoc Networks. Second International Conference, ADHOCNETS 2010, Victoria, BC, Canada, August 18-20, 2010, Revised Selected Papers

Research Article

Balanced Itinerary Planning for Multiple Mobile Agents in Wireless Sensor Networks

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  • @INPROCEEDINGS{10.1007/978-3-642-17994-5_28,
        author={Min Chen and Wei Cai and Sergio Gonzalez and Victor Leung},
        title={Balanced Itinerary Planning for Multiple Mobile Agents in Wireless Sensor Networks},
        proceedings={Ad Hoc Networks. Second International Conference, ADHOCNETS 2010, Victoria, BC, Canada, August 18-20, 2010, Revised Selected Papers},
        proceedings_a={ADHOCNETS},
        year={2012},
        month={5},
        keywords={mobile agent itinerary planning minimum spanning tree wireless sensor networks},
        doi={10.1007/978-3-642-17994-5_28}
    }
    
  • Min Chen
    Wei Cai
    Sergio Gonzalez
    Victor Leung
    Year: 2012
    Balanced Itinerary Planning for Multiple Mobile Agents in Wireless Sensor Networks
    ADHOCNETS
    Springer
    DOI: 10.1007/978-3-642-17994-5_28
Min Chen1,*, Wei Cai1,*, Sergio Gonzalez2,*, Victor Leung2,*
  • 1: Seoul National University
  • 2: University of British Columbia
*Contact email: minchen@ieee.org, caiwei@mmlab.snu.ac.kr, sergiog@ece.ubc.ca, vleung@ece.ubc.ca

Abstract

In this paper, we consider the use of multiple mobile software agents to perform different tasks in wireless sensor networks (WSNs). To this regard, determining the number of mobile agents in the WSN remains an open issue in solving multi-agent itinerary planning (MIP) problem. We propose a novel scheme entitled MST-MIP based on minimum spanning tree, where each branch stemmed from the sink corresponds to a group of source nodes assigned for a mobile agent to visit. Furthermore, a balancing factor is introduced to achieve a flexible trade-off control between energy cost and task duration, and the balancing MST-MIP algorithm is named BST-MIP. Extensive experiments show that MST-MIP has lower energy consumption than previous MIP proposals, while BST-MIP decreases the task duration up to 50%.