Battery recovery aware sensor networks

Many applications of sensor networks require batteries as the energy source, and hence critically rely on energy optimisation of sensor batteries. But as often neglected by the networking community, most batteries are non-ideal energy reservoirs and can exhibit battery recovery effect - the deliverable energy in batteries can be replenished per se, if left idling for sufficient duration. We made several contributions towards harnessing battery recovery effect in sensor networks. First, we empirically examine the gain of battery runtime due to battery recovery effect, and found this effect significant and duration-dependent. Second, based on our findings, we model the battery recovery effect in the presence of random sensing activities by a Markov chain model, and study the effect of duty cycling and buffering to harness battery recovery effect. Third, we propose a more energy-efficient duty cycling scheme that is aware of battery recovery effect, and analyse its performance with respect to the latency of data delivery.