Energy efficient k-barrier coverage in limited mobile wireless sensor networks

Abstract

Energy cost and reliability are two main concerns in barrier coverage for wireless sensor networks. In this paper, we take the energy cost and reliability as objectives respectively to study two problems of k-barrier coverage: the minimum energy cost k-barrier coverage problem in static wireless sensor networks and the maximum k-barrier coverage problem in limited mobile wireless sensor networks. For the minimum energy cost k-barrier coverage problem, all sensors are stationary, and each sensor has l+1 sensing power levels in the network, the objective of the problem is to find a sensing level assignment to form k-barrier coverage such that the total power consumed by the k-barrier is minimized. We firstly transform it into a minimum cost flow problem with side constraints and use Lagrangian relaxation technique to solve the minimum cost flow problem. Then, we also propose a heuristic algorithm. For the maximum k-barrier coverage problem, each sensor can move within the limited range, the objective of the problem is to form more barriers while some sensors can move within limited range. We formulate the problem into an integer linear programming (ILP), then propose two heuristic algorithms based on the linear programming (LP) relaxation. The simulation results demonstrate our algorithms are efficient.