Energy-Efficient Communication in Wireless Sensor Networks: An Integrated Approach on Power Control and Load Balancing
Yu Wang, Hongyi Wu and Nian-Feng Tzeng
Energy efficiency is a critical design issue in wireless sensor networks, where each sensor node relies on its limited battery power for data acquisition, processing, transmission, and reception. In this paper, we study an integrated approach on power control and load balancing, aiming at even distribution of the residual energy of the sensors and thus prolonging the lifetime of overall wireless sensor networks. More specifically, an Integer Linear Programming (ILP) algorithm, a Distributed Energy Efficient Routing (DEER) protocol, and a neural network based approach are pro-posed for time-driven sensor networks. A Residual Energy-based Traffic Splitting (RETS) protocol is introduced for event-driven sensor networks. We have carried out extensive simulations to evaluate the proposed energy efficient communication protocols. Our simulation results show that most heuristic approaches yield network lifetimes far smaller than the upper bound obtained from the ILP algorithm. The neural network approach performs very well, if it is trained before being adopted by sensor networks targeting at the same applications, able to yield results approaching the upper bound. The proposed DEER and RETS approaches can effectively distribute energy consumption evenly among the sensor nodes to prolong the network lifetime by up to 200% or more, when compared with other approaches in the literature.