Reward Rate Maximization and Optimal Transmission Policy of EH Device With Temporal Death in EH-WSNs

For the perpetual wireless sensor network (WSN), energy harvesting (EH) technology is emerging as a promising solution. However, the randomness and the instability of the harvested energy may lead to the occurrence of the temporal death, which is harmful to the functions of the WSN, and has negative impact on the quality of service of the network. With temporal death being taken into account, this paper proposes a novel and overall framework, namely, a multi-layer Markov fluid queue (MLMFQ) model, for modeling and analyzing the data transmission nature of the EH devices (EHDs). We formulate the model of the whole system in terms of MLMFQ, and obtain the stead-state probabilities of the EHD. We study the issue of how to maximize the steady-state average reward rate of the reported data packets. We then propose an optimization model, in which one can maximize the overall steady-state average reward rate with relation to transmission policy under the specific constraints. On this basis, we are able to propose an algorithm for calculating the optimal transmission policy of the EHD with temporal death. We validate our results using a numerical example and report some interesting findings from our numerical studies.