Quality-Aware Target Coverage in Energy Harvesting Sensor Networks

Sensing coverage is a fundamental problem in wireless sensor networks for event detection, environment monitoring, and surveillance purposes. In this paper, we study the sensing coverage problem in an energy harvesting sensor network deployed for monitoring a set of targets for a given monitoring period, where sensors are powered by renewable energy sources and operate in duty-cycle mode, for which we first introduce a new coverage quality metric to measure the coverage quality within two different time scales. We then formulate a novel coverage quality maximization problem that considers both sensing coverage quality and network connectivity that consists of active sensors and the base station. Due to the NP-hardness of the problem, we instead devise efficient centralized and distributed algorithms for the problem, assuming that the harvesting energy prediction at each sensor is accurate during the entire monitoring period. Otherwise, we propose an adaptive framework to deal with energy prediction fluctuations, under which we show that the proposed centralized and distributed algorithms are still applicable. We finally evaluate the performance of the proposed algorithms through experimental simulations. Experimental results demonstrate that the proposed solutions are promising.