An Information Entropy Approach for Sleep Scheduling in Densely-Deployed Sensor Networks

Wireless sensor networks are usually densely deployed, and it is quite common for sensors to gather and transmit redundant information, which results in unnecessary energy consumption. Sleep scheduling is quite helpful for reducing overall energy consumption of the network, and thus prolongs the network lifetime. In this paper, we propose an Information Entropy Approach for Sleep Scheduling (IEASS). Information entropy is exploited in the algorithm to characterize the correlation of data which is used for determining the eligibility of node sleeping. The main objective of IEASS is to achieve adaptive coverage while keeping network connectivity. From the simulation results, IEASS performs well on coverage ratio and coverage degree with much less active sensor nodes. Moreover, IEASS achieves high flexibility by adjusting the algorithm parameters.