Distributed Energy-Aware Mobile Sensor Coverage Game with Inter-Agent Communication

Mobile Sensor Networks (MSN) are used to monitor large areas and collect measurements, e.g. temperature, humidity, or pressure data. Mobile sensors try to optimize their benefit from sensing a particular area, while keeping their energy consumption at the lowest possible level. We formulate this energy-aware sensor coverage problem as a potential game, where the mobile sensor nodes are considered as agents. The utility function of the game captures the trade-off between the benefit from coverage and the energy consumption. We also propose a distributed learning strategy for this potential game. The algorithm enables a bit-valued information exchange between the agents. Finally, it is proved that the learning rule converges to a Nash Equilibrium.