5th International ICST Conference on Wireless Internet

Research Article

GA-MIP: Genetic algorithm based multiple Mobile Agents itinerary planning in wireless sensor networks

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  • @INPROCEEDINGS{10.4108/ICST.WICON2010.8518,
        author={Wei Cai and Min Chen and Takahiro Hara and Lei Shu},
        title={GA-MIP: Genetic algorithm based multiple Mobile Agents itinerary planning in wireless sensor networks},
        proceedings={5th International ICST Conference on Wireless Internet},
        publisher={IEEE},
        proceedings_a={WICON},
        year={2010},
        month={4},
        keywords={Application software Biomedical monitoring Computerized monitoring Condition monitoring Delay Genetic algorithms Genetic engineering Mobile agents Temperature sensors Wireless sensor networks},
        doi={10.4108/ICST.WICON2010.8518}
    }
    
  • Wei Cai
    Min Chen
    Takahiro Hara
    Lei Shu
    Year: 2010
    GA-MIP: Genetic algorithm based multiple Mobile Agents itinerary planning in wireless sensor networks
    WICON
    IEEE
    DOI: 10.4108/ICST.WICON2010.8518
Wei Cai1,*, Min Chen1,*, Takahiro Hara2,*, Lei Shu2,3,*
  • 1: School of Computer Science and Engineering, Seoul National University, Republic of Korea
  • 2: Department of Multimedia Engineering, Osaka University, Japan
  • 3: Digital Enterprise Research Institute, National University of Ireland, Galway
*Contact email: caiwei@mmlab.snu.ac.kr, minchen@snu.ac.kr, hara@ist.osaka-u.ac.jp, lei.shu@ieee.org

Abstract

It has been proven recently that using Mobile Agent (MA) in wireless sensor networks (WSNs) can drastically help to obtain the flexibility of application-aware deployment. Normally, in any MA based sensor network, it is an important research issue to find out an optimal itinerary for the MA in order to achieve efficient and effective data collection from multiple sensory data source nodes. In this paper, we firstly investigate a number of conventional single MA itinerary planning based schemes, and then indicate some shortcomings of these schemes, since only one MA is used by them. Having these investigations and analysis, a novel genetic algorithm based multiple MAs itinerary planning (GA-MIP) scheme is proposed to address the shortcomings of large latency and global unbalancing of using single MA, and its effectiveness is proved by conducting the extensive experiments in professional environment.