A Distributed Energy Optimized Routing Using Virtual Potential Field in Wireless Sensor Networks

Energy is an extremely critical resource for battery-powered wireless sensor networks. Since data transmission typically consumes more energy than any other activities on a sensor node, it is of great importance to design energy optimized routing algorithm to achieve both energy efficiency and energy balance together, in order to prolong the network lifetime. In this paper, with the help of the concept of potential field in physics, we design a distributed energy optimized routing by constructing a hybrid potential field. The goal of this basic approach is to force packets to move toward the sink at the same time to achieve energy balance among neighbors. We adopt the social welfare function from social sciences to predict equality of residual energy of neighbors after selecting different next nodes, which is used to compute the potential value in energy balance potential field. Simulation results show that the algorithm effectively extends the network lifetime, has good performance on energy balance of sensors, and decreases the average hop of data transmission with the increase of the number of sinks, compared with similar algorithms.