Energy-Based Lifetime Maximization and Security of Wireless-Sensor Networks With General Nonideal Battery Models

Abstract

We study the problem of maximizing the lifetime of a sensor network by means of routing and initial energy allocation over its nodes. We consider a general state space battery model and show that similar results to our previous work with simpler battery dynamics are still valid. In particular, we show that under this general dynamic battery model, there exists an optimal policy consisting of time-invariant routing probabilities in a fixed topology network and these can be obtained by solving a set of nonlinear programming (NLP) problems. Moreover, we show that the problem can be reformulated as a single NLP problem. In addition, we consider a joint routing and initial energy allocation problem over the network nodes with the same network lifetime maximization objective. We prove that the solution to this problem is given by a policy that depletes all node energies at the same time and that the corresponding energy allocation and routing probabilities are obtained by solving an NLP problem. Finally, we examine a network's performance under security threats, typified by faked-cost attacks, in terms of its lifetime and its normalized throughput. We illustrate how the optimal routing probabilities, as well as the network lifetime, are robust under such forms of routing attacks even though its normalized throughput can be significantly reduced.