Distributed routing in wireless sensor networks using energy welfare metric

There are several requirements for a routing algorithm in wireless sensor networks. First, it should achieve both energy-efficiency and energy-balancing together, in order to prolong the lifetime of sensor networks. Second, the algorithm should follow a distributed control scheme so that it is applicable to large-scale networks. Third, it needs to be robust to diverse potential event generation patterns. The routing algorithm, MaxEW, designed in this study satisfies such requirements. It adopts the social welfare function from social sciences to compute energy welfare as a goodness measure for energy populations. When each sensor tries to maximize energy welfare of its local society, it collectively leads to globally efficient energy-balancing. This emergent property consequently supports preparedness and hence robustness to diverse event generation patterns. We demonstrate the effectiveness of the proposed routing algorithm through extensive simulation-based experiments, by comparing with other existing algorithms as well as optimal routing solutions.