own energy values but also the receiver’s energy values.

One more fundamental consideration in using certain EH sources, which is different from those in using non-rechargeable batteries, is the maximum rate at which we can utilize the harvested energy [@Kansal:2007:PME:1274858.1274870]. Therefore, we have to capture the uncertainty in not only the energy source but also the consumption. With this motivation in mind, the authors in [@993375] modeled a battery similarly to a server with a finite service capacity, and the data packets similarly to customers to be served, and analyzed the performance using a queueing-theoretic approach. This work is one of the earlier attempts to model the battery using queueing theory. Regarding a sensor node as a paired queueing system with two buffers, one for the accumulated energy and the other for the arriving data, Cuypere *et al.* analyzed its performance numerically, and investigated the energy-information tradeoff [@3229100]. A more comprehensive and practical, yet simple enough, model, which also takes the variations in harvested energy into consideration, appeared in [@Kansal:2007:PME:1274858.1274870] and [@Kansal:2004:PAT:1012888.1005714]. We can easily incorporate the aforementioned queueing model to a general class of stochastic energy sources. Bounding the energy arrival from an energy source with lower and upper 