Target Coverage in Wireless Sensor Networks  Chang Wu Yu Department of Computer Science and Information Engineering Chung Hua University Taiwan, R.O.C. cwyu@chu.edu.tw Chin-Tsai Lin Department of Information Engineering Kun Shan University Taiwan, R.O.C. ctlin@mail.ksu.edu.tw Kun-Ming Yu Department of Computer Science and Information Engineering Chung Hua University Taiwan, R.O.C. yu@chu.edu.tw Chen Yi Lin Department of Computer Science and Information Engineering Chung Hua University Taiwan, R.O.C. m09802046@chu.edu.tw Wei-Ting So Department of Computer Science and Information Engineering Chung Hua University Taiwan, R.O.C. m09602019@chu.edu.tw Abstract—Coverage problems are fundamental and crucial in designing a wireless sensor networks. The target coverage problem is finding an optimal scheduling for sensors such that the time (called lifetime) to monitor every target can be as long as possible. Unfortunately, the target coverage problem has been proved to be NP-complete. Most of previous work only considers one or two factors exclusively and thus fails to prolong the lifetime to near the optimum. The main objective of this work is to design efficient scheduling algorithms to maximize the lifetime of a given whole wireless sensor network by considering adjusting sensing range, locations of target and sensors, residue battery power of sensor nodes, and assignment between sensors and targets simultaneously. A maximum weighted matching algorithm is devised by considering full coverage and the maximum total monitored duration for each target-sensor assignments. We also conduct simulations to demonstrate that the proposed algorithms can achieve very high network lifetime closed to the optimum. I. INTRODUCTION Wireless sensor networks (WSNs) receive lots of attention in recent years due to its promising techniques and wide-ranging applications. A WSN consists of a large number of low-cost, low-power, small-size, and multifunction sensor nodes which sense and process environmental data and communicate with other nodes in short distance [7]. Wireless sensor networks have been used in many areas such as health care, military, and surveillance. For example, on health care, we can place sensor nodes on clothes or wearable devices to monitor biological states of patients, elders, or children. Since sensor nodes are usually equipped with scarce battery power and thus limited in their active lifetime, how to prolong the operational lifetime has been a major issue in WSNs. Moreover, lots of research issues in wireless sensor networks including medium access control [1, 2], power saving [7], target tracking, routing method [7, 15], network coverage [6, 10], and network connectivity have been discussed extensively. Coverage problems are fundamental and crucial in designing a wireless sensor networks. Usually coverage problems in wireless sensor networks can be classified into three categories: (1) Target coverage problems: There exists a set of predetermined targets which need to be monitored (covered) in a fixed deployed area. Due to the limited batter energy of deployed sensors, target coverage problems are focusing on designing effective scheduling algorithms to prolong the time for monitoring these targets. (2) Area coverage problems: In an interested area, we have to ensure that every point of the whole area can be monitored by at least k sensor, where k1. The coverage problem is to maximize the time for monitoring the whole area. (3) Barrier coverage problems: Given a barrier, we want to guarantee that every object moves across the barrier will be detected by the deployed sensors. Among these problems, area coverage problems have already received extensive attention in these years [12]. On the other hand, the remaining two problems begin to draw attention recently [3, 4, 8]. This work focuses on the target coverage problem in both static and mobile wireless sensor networks. An example of target coverage is given as follows. In Figure 1(a), targets r 1 , r 2 , and r 3 denote targets which need to be covered (or monitored) and sensors s 1 , s 2 , s 3 , and s 4 denote the deployed sensor nodes. Specifically, Figure 1(a) shows that target r 1 is covered by s 1 , s 3 , and s 4 ; target r 2 is covered by s 1 , s 2 , and s 4 ; target r 3 is covered by s 2 , s 3 , and s 4 . The coverage relation among targets and deployed sensors can be represented by a bipartite graph G=(S, R, E) where S and R denote the target node set and sensor node set, respectively. Whenever a target r is located in the sensing range of a sensor s, there exists an edge (s, r) in E. Figure 1(b) gives an example of the corresponding bipartite graph of Figure 1(a). 2011 Seventh International Conference on Mobile Ad-hoc and Sensor Networks 978-0-7695-4610-0/11 $26.00 © 2011 IEEE DOI 10.1109/MSN.2011.78 409 2011 Seventh International Conference on Mobile Ad-hoc and Sensor Networks 978-0-7695-4610-0/11 $26.00 © 2011 IEEE DOI 10.1109/MSN.2011.78 408 2011 Seventh International Conference on Mobile Ad-hoc and Sensor Networks 978-0-7695-4610-0/11 $26.00 © 2011 IEEE DOI 10.1109/MSN.2011.78 408