Abstract

In this paper, we develop a novel algorithm to deploy an energy-efficient wireless sensor network (WSN) for the target-location service that is one of the major applications of sensor networks. Such sensor network has to be designed to achieve complete coverage quality of surveillance and full discrimination for predetermined resolution on the sensor field. To extend lifetime of sensor network, the duplicate deployment approach is a simple and intuitive way. However, such approach will result in increasing too much deployment cost. In this paper, we propose a novel strategy to cope with the problem. We consider deploying K independent sets of sensors to monitoring the area in turn and locating the intruder together. With this strategy, the duty cycle of each sensor is only 1/K and the lifetime of the sensor network will be extended up to K times. Such sensor placement problem is a variant of the set K-cover problem, which is NP-complete. We formulate the problem as a 0/1 integer-programming problem. A Lagrangean relaxation based heuristic then is proposed for solving the optimization problem. The experimental results show that the proposed strategy gets a significant improvement in the lifetime of sensor network compared to the duplicate deployment approach under the deployment cost constraint. The proposed algorithm is highly effective in terms of the overall deployment cost. Furthermore, the algorithm is very efficient and scalable in terms of the solution time. I. INTRODUCTION The rapid growth in sensor technology and wireless com- munication has led to the development of wireless sensor networks (WSNs). A wireless sensor network comprises sev- eral sensors, sink nodes, and back-end systems. These tiny, low-cost, and low power sensors are deployed in an ad hoc manner in an interested area. These sensors collect physical information from the area, process and forward the information to the sink nodes. Afterward, the back-ends can obtain global views according to the information provided by the sink nodes

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