On Efficient Selection and Orientation of Directional Sensors in Visual Sensor Networks

Abstract

A visual sensor network (VSN) is a part of wireless sensor networks (WSNs) that consists of different kinds of sensors to ensure the coverage of a certain area. We study the “Maximum Coverage with Minimum Sensors” (MCMS) problem for VSNs consisting of randomly deployed targets and directional sensors. The existing solutions cause high computational complexity and unnecessary coverage redundancy. To overcome such problems, we devise a modified version of an existing centralized greedy algorithm that comes with a new target oriented approach minimizing the number of active sensors and reducing the run time. The approach is based on a novel idea of conflict edge between two or more sensors. As far as we know, no previous work has used conflict edge concept to solve the MCMS problem. Our strategy ensures that no target in the network will remain uncovered. Finally, our simulation and few comparison analyses show that the method provides the most robust results.