bounds, and bounding the energy consumption with an upper bound, they showed that a device can operate forever as long as it has a storage capacity greater than the total burstiness defined by the upper and lower bounds [@Kansal:2004:PAT:1012888.1005714]. They provided the stability condition such that the average energy arrival rate is less than or equal to the average energy demanded for consumption. Although these deterministic bounds provide a framework to study the steady-state behavior of energy production and consumption processes, they indeed capture the worst-case scenario. Also, these bounds do not take advantage of the statistical nature of the energy arrival and consumption processes. Separately, considering statistical bounds, Srivastava *et al.* invoked large deviation theory and showed that the energy underflow probability, i.e., the probability that the energy level in the battery is below a defined threshold, scales exponentially as a function of the battery size and a constant in the asymptotic regime of large battery size [@srivastava2013basic]. Finally, the authors in [@jia2017data] characterized the average backlog for both constant and random data arrivals at a finite-size data buffer considering a Bernoulli energy arrival process.

Last but not least, considering a network of energy harvesters, namely energy packet networks 