Quality of Service in Heterogeneous Networks. 6th International ICST Conference on Heterogeneous Networking for Quality, Reliability, Security and Robustness, QShine 2009 and 3rd International Workshop on Advanced Architectures and Algorithms for Internet Delivery and Applications, AAA-IDEA 2009, Las Palmas, Gran Canaria, November 23-25, 2009 Proceedings

Research Article

Multi-Agent Itinerary Planning for Wireless Sensor Networks

Download130 downloads
  • @INPROCEEDINGS{10.1007/978-3-642-10625-5_37,
        author={Min Chen and Sergio Gonzalez and Yan Zhang and Victor Leung},
        title={Multi-Agent Itinerary Planning for Wireless Sensor Networks},
        proceedings={Quality of Service in Heterogeneous Networks. 6th International ICST Conference on Heterogeneous Networking for Quality, Reliability, Security and Robustness, QShine 2009 and 3rd International Workshop on Advanced Architectures and Algorithms for Internet Delivery and Applications, AAA-IDEA 2009, Las Palmas, Gran Canaria, November 23-25, 2009 Proceedings},
        proceedings_a={QSHINE},
        year={2012},
        month={10},
        keywords={Wireless sensor networks mobile agent itinerary planning},
        doi={10.1007/978-3-642-10625-5_37}
    }
    
  • Min Chen
    Sergio Gonzalez
    Yan Zhang
    Victor Leung
    Year: 2012
    Multi-Agent Itinerary Planning for Wireless Sensor Networks
    QSHINE
    Springer
    DOI: 10.1007/978-3-642-10625-5_37
Min Chen1,*, Sergio Gonzalez2,*, Yan Zhang3,*, Victor Leung2,*
  • 1: Seoul National University
  • 2: University of British Columbia
  • 3: Simula Research Laboratory
*Contact email: mchen@mmlab.snu.ac.kr, vleung@ece.ubc.ca, yanzhang@ieee.org, vleung@ece.ubc.ca

Abstract

Agent-based data collection and aggregation have been proved to be efficient in wireless sensor networks (WSNs). While most of existing work focus on designing various single agent based itinerary planning (SIP) algorithms by considering energy-efficiency and/or aggregation efficiency, this paper identifies the drawbacks of this approach in large scale network, and proposes a solution through multi-agent based itinerary planning (MIP). A novel framework is presented to divide our MIP algorithm into four parts: visiting central location (VCL) selection algorithm, source-grouping algorithm, SIP algorithm and its iterative algorithm. Our simulation results have demonstrated that the proposed scheme lowers delay and improves the integrated energy-delay performance compared to the existing solutions with the similar computation complexity.