Balancing sensing and coverage in mobile sensor networks: A min-max approach

Abstract

This paper presents a min-max algorithm for assigning mobile robots in a mobile wireless sensor network to different tasks that the network must perform. The algorithm minimizes the maximum penalty that is imposed when one of the tasks is not fully attended. The particular problem that we study is how to uniformly distribute autonomous mobile sensing robots inside a convex region while also quickly locating one or more sensory sources that might appear inside the region. The limited sensing capabilities of each robot suggest that several agents should collaborate to locate each source. The issue is then how to assign a sufficient number of robots to the sensing task and move them towards the source (even though some of them might initially not sense it), thereby diminishing the coverage of the region. We show that the proposed algorithm converges towards a stable equilibrium point. The algorithm is fully distributed and thus scalable. Simulation results that verify the theoretical claims are also presented.

Seeking Optimal Equilibria for Coverage Games

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