2nd International ICST Conference on Broadband Networks

Research Article

Lifetime maximization using observation time scheduling in multi-hop sensor networks

  • @INPROCEEDINGS{10.1109/ICBN.2005.1589703,
        author={Zhao Qun and Mohan Gurusamy},
        title={Lifetime maximization using observation time scheduling in multi-hop sensor networks},
        proceedings={2nd International ICST Conference on Broadband Networks},
        publisher={IEEE},
        proceedings_a={BROADNETS},
        year={2006},
        month={2},
        keywords={},
        doi={10.1109/ICBN.2005.1589703}
    }
    
  • Zhao Qun
    Mohan Gurusamy
    Year: 2006
    Lifetime maximization using observation time scheduling in multi-hop sensor networks
    BROADNETS
    IEEE
    DOI: 10.1109/ICBN.2005.1589703
Zhao Qun1,*, Mohan Gurusamy1,*
  • 1: Electrical and Computer Engineering Department, National University of Singapore
*Contact email: zhaoqun@nus.edu.sg, elegm@nus.edu.sg

Abstract

Prolonging lifetime is a key challenge in wireless sensor networks comprising unattended, limited resource sensor nodes. As sensors are usually densely deployed, redundant data is produced by multiple observations on the same event, which decreases the network lifetime. With each observing sensor acting as a source of data, we schedule the time when these sources are allowed to send data to prolong the network lifetime with the guarantee that the total data provided satisfies the application requirement at any time. Considering k-coverage of each target as the application requirement, we propose the observation time scheduling for network lifetime maximization (OSLM) problem and solve it for two observation scenarios: a) a sensor node can distinguish the targets in its sensing range and selects a subset of targets to observe and b) a sensor node has to simultaneously observe all the targets in its sensing range as it cannot distinguish targets. We develop an optimal solution using a linear programming (LP) problem formulation for OSLM problem for the first observation scenario and solve it using CPLEX package. We prove that OSLM problem for the second observation scenario is NP-complete. A heuristic algorithm for the second scenario is then proposed. The performance is evaluated by the numerical results obtained from CPLEX and extensive simulation results