Localized Self-Deployment of Mobile Sensors for Optimal Focused-Coverage Formation

In this paper, we pinpoint a new sensor selfdeployment problem, achieving focused coverage around a Point of Interest (POI), and introduce an evaluation metric, coverage radius, that reflects the significance of distance from the POI to uncovered areas. Then we propose two solution protocols, Greedy Advance (GA) and GreedyRotation-Greedy (GRG), which are to our best knowledge the first sensor self-deployment algorithms that operate in a strictly localized manner and yet provide coverage guarantee. The two proposed algorithms drive sensors to move along a locally-computed equilateral triangle tessellation (TT) to surround the POI. In GA, nodes greedily proceed as close to the POI as they can; in GRG, when their greedy advance is blocked, nodes rotate around the POI to a TT vertex where greedy advance can resume. In both algorithms, when sensors are compactly placed or collide, they may move away from the POI. Both GA and GRG yield a connected network of TT layout with hole-free coverage; GRG furthermore assures a hexagon coverage shape centered at the POI. Thanks to their purely localized nature, the two algorithms are resilient to node failures and work regardless of network disconnectivity. We prove their correctness and analyze their coverage radius property. Our study shows that GRG guarantees optimal hexagonal coverage radius, and optimal or near optimal circular coverage radius. We evaluate their performance on convergence time, energy consumption and node collision through extensive simulation.