LAUSR

The energy constraint is a major issue in wireless sensor networks since battery cells that supply sensor nodes have a limited amount of energy and are neither replaceable nor rechargeable in most cases. A common assumption in previous work is that the energy consumed by sensors in sleep mode is negligible. With this hypothesis, the usual approach is to iteratively consider subsets of nodes that cover all the targets. These subsets, also called cover sets, are then put in the active mode whereas the others are in the low-power or sleep mode. The scheduling of the appropriate cover sets in order to maximize the network lifetime is a challenging problem known to be NP-hard. The consideration of non-zero energy consumption of sensor nodes in sleep mode is more realistic but significantly increases the complexity of the problem. In this paper, we address this question by proposing a greedy algorithm that gives priority to sensors with lowest energy, and uses a blacklist to limit the number of sensors covering critical targets. Simulations show that this algorithm outperforms the previously published solutions. We then propose for regular arrays, an analytical approach which shows that, for any optimal solution, all sensors’ remaining energies are zero. This theoretical approach sheds a new light on ring connected arrays of odd size, that are known to be rather tricky when non-disjoint cover sets are considered.