2nd International ICST Conference on Communications and Networking in China

Research Article

Energy Efficient Top-k Query Processing in Dynamic Sensor Network

  • @INPROCEEDINGS{10.1109/CHINACOM.2007.4469512,
        author={Qunhua Pan and Shuwang Li and Minglu  Li and Min-You Wu},
        title={Energy Efficient Top-k Query Processing in Dynamic Sensor Network},
        proceedings={2nd International ICST Conference on Communications and Networking in China},
        publisher={IEEE},
        proceedings_a={CHINACOM},
        year={2008},
        month={3},
        keywords={cached data  dynamic  query processing  sensor network  top-k},
        doi={10.1109/CHINACOM.2007.4469512}
    }
    
  • Qunhua Pan
    Shuwang Li
    Minglu Li
    Min-You Wu
    Year: 2008
    Energy Efficient Top-k Query Processing in Dynamic Sensor Network
    CHINACOM
    IEEE
    DOI: 10.1109/CHINACOM.2007.4469512
Qunhua Pan1,*, Shuwang Li2,*, Minglu Li1,*, Min-You Wu1,*
  • 1: Department of Computer Science and Engineering, Shanghai JiaoTong University
  • 2: Information Center, The Ministry of Public Security P.R.China
*Contact email: oct-panmy}@cs.sjtu.edu.cn, lishuwang@vip.sina.com, li-mlmy}@cs.sjtu.edu.cn, wu-my@cs.sjtu.edu.cn

Abstract

Sensor networks may generate a large amount of data during the monitoring process. It is crucial to conserve energy when processing these data. The detected sensory data vary in long monitoring period. The problem is how to design query processing with minimal energy and obtain correct result. In this paper, we propose a history-based approach to optimizing top-k query processing in sensor network and design Threshold-Estimate-Prune-Query algorithm. Energy consumption can be reduced by pruning unnecessary sub-queries and query message can be guided to right direction by cached data. Subset of the sensor network will respond the query. We design Local-Expand-Query method to get more correct data when the environment changed. Simulation results show that the number of queried nodes can be significantly reduced in top-k query processing. The expand query can get more accuracy data when the environment varies and data distribution changed.