Maximal Lifetime Scheduling in Sensor Surveillance Networks 1 Hai Lid, Pengjun Wan2, Chih-Wei Yi', Xiaohua Jia', Sam Makki3 and Nilci Pissinou4 Dept of Computer Science 'City University oEHong Kong 2111incmInstitute of Technology Dept of Electrical Engineering & Computer Science 'Universily of Toledo Telecommunications 8i Int'ormation Technology Institute 4Florida Intemitional University Email: { liuhai@cs.cit vu. edu .U, wan@cs. iit.edu, jia@cs. cit yu. eduhk, Kmakki@eng.utoledo.edu,pissinou@fiu.edu ] Abstroct--This paper addresses the maximal lifetime scheduling problem in sensor surveillance networks, Given a set of sensors and targets in a Euclidean plane, a sensor can watch only one target at a time, our task is to schedule sensors to watch targets, such that the lifetime of the surveillance system is maximized, where the lifetime is the duration that all targets are watched, We propose an optimal solution to find the target watching schedule for sensors that achieves the maximal Lifetime. Our solution consists of three steps: 1) computing the maximal lifetime of the surveillance system and n workload matrix by using linear programming techniques; 2) decomposing the workload matrix into a sequence of schedule matrices that can achieve the maxima1 lifetime; 3) obtaining a target watching timetable for each sensor based on the schedule matrices. Simulations have been conducted to study the complexity of our proposed method and to compare with the performance of a greedy method. Keywords-- Enera efficiency, lifetime, scheduling, sensor network, surveillance system. 1. INTRODUCTIONS A wireless sensor network consists of many low-cost and low-powered sensor devices (called sensor nodes) that collaborate with each other to gather, process, and communicate information using wireless communications [ 41. Applications of sensor networks include military sensmg, traffic surveillance, environment monitoring, building structures monitoring, and so on. One important characteristic of sensor networks is the stringent power budget of wireless sensor nodes, because those nodes are usually powered by batteries and it may not be possible to recharge or replace the batteries after they are deployed in hostile or hazardous environments [15]. The surveillance nature of sensor networks requires a long lifetime. Therefore, it is an important research issue to prolong the lifetime of sensor networks in surveillance services. In this paper, we discuss a scheduling problem in sensor surveillance networks. Given a set of targets and sensors in an area, the sensors are used to watch (or monitor) the targets A sensor can watch targets that are uithm its surveillance range, and a target can be inside several sensors' watching range. Suppose each sensor has a given energy resenle (in terms of the length of time it can operate correctly) and each sensor can watch at most one target at a time. The problem is to find a schedule for sensors to watch the targets, such that all targets should be watched by sensors at anytime and the lifetime of the surveillance is maximized. The lifetime is the duration up to the time when there exists one target that cannot be watched by any sensors due to the depletion of energy of the sensor nodes. By using thls schedule, a sensor can switch off to save energy when it is not its turn to watch a target. We assume the positions of targets and sensors are given and are static. This information can be obtained via a distributed monitoring mechanism [IO] or the scanning method 1 11. Extensive research has been done on extending the lifetime of sensor networks. Authors in [12] studied the upper bounds on the lifetime of sensor networks used in data gathering in various scenarios. Both analytical results and extensive simulations showed that the derived upper bounds are tight for some scenarios and near-tight (about 95%) far the rest. The authors further proposed a technique to find the bounds of lifetime by partitioning the problem into the sub- problems for which the bounds are either already known or easy to derive. A differentiated surveillance service for various target areas in sensor networks was discussed in [ I5). The proposed protocol was based on an energy-efficient sensing coverage protocol that makes full coverage to a certain geographic area. It is also guaranteed to achieve a certain degree of coverage for fault tolerance. Simulations ' This work is supported in part by Hong Kong Research Grant Council under grant No. CityU 1079/02E, NSF CCR-0311174, NSF 0123950, and NSF 9988336. 2482