Abstract-This paper addresses the maximal lifetime scheduling problem in sensor surveillance systems. Given a set of sensors and targets in an area, a sensor can watch only one target at a time, our task is to schedule sensors to watch targets and forward the sensed data to the base station, such that the lifetime of the surveillance system is maximized, where the lifetime is the duration that all targets are watched and all active sensors are connected to the base station. 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 a workload matrix by using the linear programming technique; 2) decomposing the workload matrix into a sequence of schedule matrices that can achieve the maximal lifetime; and 3) determining the sensor surveillance trees based on the above obtained schedule matrices, which specify the active sensors and the routes to pass sensed data to the base station. This is the first time in the literature that the problem of maximizing lifetime of sensor surveillance systems has been formulated and the optimal solution has been found.

The prohlem Min-Power k-Connectivity seeks a power assignment to the nodes in a given wireless ad hoc network such that the produced network topology is k-connected and the total power is the lowest, In this paper, we present several approximation algorithms for this problem. Specifically, we propose a Yk-approximatiun algorithm for any k 2 3, a (k-t E H (k))-approximation algorithm for k (2k-1) 5 TI where n is the network size, a (k + 2 [(k i-1) /21)-approximatiun algorithm for 2 5 k 5 7, a &approximation algorithm for k = 3, and a 9-approximation algorithm fur k = 4. index Terms-I;-connectivity, power assignment, wireless ad hoc sensor networks I. INTRODUCTION One of the major concerns in ad hoc wireless networks is reducing node power consumption. In fact, nodes are usually powered by batteries of limited capacity. Once the nodes are deployed, it is very difficult or even impossible to recharge or replace their batteries in many application scenarios. Hence, reducing, power consumption is often the only way to extend network lifetime, For the purpose of energy conservation, each node can (possibly dynamically) adjust its transmitting power between zero and its maximal transmission power. Throughout this paper, we use V to denote the set of networking nodes and p(v) to denote the maximal transmission power of node ' II. In addition, we use c (U V) to represent the power requirement for both node U and

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Recent advancements in micro-computing have provided the exponential increase in the capabilities of a wide range of devices and have allowed the implementation of complex mobile wireless sensor networks (mWSNs). The common batterypowered sensor nodes require security techniques that eliminate redundant processing overhead for resource conservation, without compromising the overall network performance. To address this issue, this paper presents USAS: Unpredictable Software-based Attestation Solution, a node compromise detection algorithm in mWSNs. USAS deploys dynamic node attestation chains to decrease checksum computation time by almost 48% for selective attested nodes. By decentralizing the network, the attestation is unpredictable to prevent malicious data injection. The performance of USAS is estimated in terms of node compromise detection rate.

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