Energy efficient movement of wireless sensors with adjustable sensing ranges for mending barrier gaps

Barrier coverage is an important issue in wireless sensor networks. When sensors are randomly deployed, barrier gaps may occur if the number of deployed sensors is not large enough or some sensors start malfunctioning or run out of energy. In this paper, we study how to efficiently mend these barrier gaps in a hybrid sensor network which consists of both the stationary and the mobile sensors with adjustable sensing ranges. First we detect all barrier gaps, then we find possible target locations where mobile sensors should be relocated with corresponding sensing ranges to mend these gaps. We propose two movement schemes: the min-cost scheme and the adaptive greedy movement scheme. The first is a centralized scheme and the second is a distributed movement algorithm based on adaptive greedy target location selection. Simulation results show that the first scheme can globally minimize the energy consumption after mending all gaps, while the second scheme can achieve high energy efficiency in an adaptive and distributed manner.