Stimulus-based adaptive sleeping for wireless sensor networks

Wireless sensor networks have been widely deployed for monitoring environments of interest. The diffusion stimulus (DS) is a very common and important one in real environments, which is characterized by originating at a source spot and continuously spreading outward. DS-based applications are usually time-sensitive and require high accuracy. It is very challenging, however, for sensor networks to monitor a DS when those sensors could usually monitor one point (the sensing range is zero) only. No existing algorithm is effective and energy-efficient for DS monitoring. In this paper, we propose stimulus-based adaptive sleeping (SAS), to tackle this unique challenge. With SAS, each node independently determines its sleep duration based on its local observations on the stimulus. SAS enables sensors near the stimulus boundary to stay alert to accurately capture the stimulus arrival, and those far away from the stimulus to safely sleep longer for energy efficiency.