QoS-aware target coverage in wireless sensor networks

  • Authors:

  • Yu Gu;Yusheng Ji;Jie Li;Baohua Zhao

  • Affiliations:

  • Dept. of Comp. Sci., Univ. of Sci. and Technol. of China, Hefei, Anhui 230027 and State Key Lab. of Networking and Switching Technology, Beijing 100876, China and Dept. of Comp. Sci., Univ. of Tsu ...;Information Systems Architecture Science Research Division, National Institute of Informatics, Tokyo, Japan;Department of Computer Science, University of Tsukuba, Tsukuba Science City, Ibaraki 305-8573, Japan;Dept. of Comp. Sci., Univ. of Sci. and Technol. of China, Hefei, Anhui 230027 and State Key Laboratory of Networking and Switching Technology, Beijing 100876, China

  • Venue:
  • Wireless Communications & Mobile Computing
  • Year:
  • 2009

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Abstract

Wireless sensor networks have emerged recently as an effective way of monitoring remote or inhospitable physical targets, which usually have different quality of service (QoS) constraints, i.e., different targets may need different sensing quality in terms of the number of transducers, sampling rate, etc. In this paper, we address the problem of optimizing network lifetime while capturing those diversified QoS coverage constraints in such surveillance sensor networks. We show that this problem belongs to NP-complete class. We define a subset of sensors meeting QoS requirements as a coverage pattern, and if the full set of coverage patterns is given, we can mathematically formulate the problem. Directly solving this formulation however is difficult since number of coverage patterns may be exponential to number of sensors and targets. Hence, a column generation (CG)-based approach is proposed to decompose the original formulation into two subproblems and solve them iteratively. Here a column corresponds to a feasible coverage pattern, and the idea is to find a column with steepest ascent in lifetime, based on which we iteratively search for the maximum lifetime solution. An initial feasible set of patterns is generated through a novel random selection algorithm (RSA), in order to launch our approach. Experimental data demonstrate that the proposed CG-based approach is an efficient solution, even in a harsh environment. Simulation results also reveal the impact of different network parameters on network lifetime, giving certain guidance on designing and maintaining such surveillance sensor networks. Copyright © 2009 John Wiley & Sons, Ltd.