A local search based approximation algorithm for strong minimum energy topology problem in wireless sensor networks

Abstract

Energy-aware network management is extremely important in wireless sensor networks as sensors in the network are powered by battery and it may not be possible to recharge the batteries of sensors after they are deployed. Topology control problem deals with the transmission power assignments to the nodes of a wireless sensor network so that the induced graph topology satisfies some specified properties. Given a set of sensors in the plane, the Strong Minimum Energy Topology (SMET) problem is to assign transmit power to each sensor such that the sum total of powers assigned to all the sensors is minimized subject to the constraint that the induced topology containing only bidirectional links is strongly connected. This will allow the sensors to communicate with each other, while conserving battery power as much as possible leading to increased network life time. So this problem is significant in both theory and application. However, the SMET problem is known to be NP-hard. Several heuristics have been proposed for SMET problem by various researchers. In this paper we propose a local search based heuristic for the SMET problem. We prove that our local search based heuristic is a 2-approximation algorithm. We compare our algorithm with several heuristic algorithms available in the literature. Simulation result shows that the local search based heuristic performs better than the existing heuristics. © 2013 Springer-Verlag Berlin Heidelberg.