A New Metric for Modeling the Uneven Sleeping Problem in Coordinated Sensor Node Scheduling

Abstract

Monitoring performance and energy constraint are two conflicting aspects in wireless sensor networks. In order to save battery power in very dense sensor networks, some redundant sensors can be put into the sleep state while other sensor nodes remain active for the sensing and communication tasks. However, if the energy consumptions for some nodes are more than those of the others, these nodes would lose effectiveness earlier than the remaining ones, which subsequently causes the coverage holes. Because of the uneven node scheduling problem in the sensing areas and the partitions of communication network, the coverage holes further influence the sensing and communication qualities and the network life. In this work, we propose the uneven sleeping problem (USP) happening in the coordinated node scheduling in wireless sensor networks. We analyze the key factors that may lead to USP. We design a new metric which can better measure and evaluate USP. This new metric takes the influence of the boundary effects on node schedule into consideration. We experimentally evaluate the performance of our proposal. The results show that our metric can effectively identify the boundary sensor nodes that deserve equal chances of sleep; it thus reduces the number of dead sensors and can help achieve a longer network lifetime than existing methods.