6th International ICST Conference on Collaborative Computing: Networking, Applications, Worksharing

Research Article

Data collection for distributed surveillance sensor networks in disaster-hit regions

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  • @INPROCEEDINGS{10.4108/icst.collaboratecom.2010.45,
        author={Yao Zhao and Xin Wang and Jin Zhao and Azman Osman Lim},
        title={Data collection for distributed surveillance sensor networks in disaster-hit regions},
        proceedings={6th International ICST Conference on Collaborative Computing: Networking, Applications, Worksharing},
        publisher={IEEE},
        proceedings_a={COLLABORATECOM},
        year={2011},
        month={5},
        keywords={Complexity theory Delay Density measurement Educational institutions Encoding Monitoring Silicon compounds},
        doi={10.4108/icst.collaboratecom.2010.45}
    }
    
  • Yao Zhao
    Xin Wang
    Jin Zhao
    Azman Osman Lim
    Year: 2011
    Data collection for distributed surveillance sensor networks in disaster-hit regions
    COLLABORATECOM
    ICST
    DOI: 10.4108/icst.collaboratecom.2010.45
Yao Zhao1,*, Xin Wang1,*, Jin Zhao1,*, Azman Osman Lim2,*
  • 1: School of Computer Science, Fudan University, China
  • 2: School of Information Science, Japan Advanced Institute of Science and Technology, Japan
*Contact email: 082024092@fudan.edu.cn, xinw@fudan.edu.cn, jzhao@fudan.edu.cn, aolim@jaisLac.jp

Abstract

The objective of many applications with the surveillance missions in wireless sensor networks is to provide long-term monitoring of the specific environments, such as disaster-hit regions. These applications usually perform continuous monitoring without any maintenance, even if some sensor nodes fail. A significant challenge when designing the data collection approaches for such systems is that the conventional communication protocols for wireless sensor networks would present low efficiency, since the network topology changes rapidly due to the node failure. Thus the sensor nodes in such systems should use an automatic transmission approach to disseminate their sensed data to the sink in a distributed manner. In this paper, we propose a novel Coding-based Probabilistic Routing (CPR) to address this specific problem of data collection for distributed surveillance sensor networks in disaster-hit regions. CPR dynamically adapts to node failure to collect the maximum data in any given time and chooses an optimal probabilistic routing to decrease the transmission consumption. The extensive simulation results are presented to show that CPR outperforms other strategies.