A Stochastic Calculus for Network Systems with Renewable Energy Sources

TL;DR

This paper develops a stochastic calculus framework to model and analyze the performance of network systems powered by renewable energy sources, accounting for environmental unpredictability and enabling probabilistic QoS guarantees.

Contribution

It introduces a novel stochastic calculus approach for modeling energy dynamics and deriving performance bounds in renewable-powered network systems, linking energy supply uncertainty with QoS guarantees.

Findings

Derived bounds on remaining energy levels under stochastic energy rates

Established probabilistic QoS guarantees based on energy constraints

Showed how performance bounds improve with stronger assumptions

Abstract

We consider the performance modeling and evaluation of network systems powered with renewable energy sources such as solar and wind energy. Such energy sources largely depend on environmental conditions, which are hard to predict accurately. As such, it may only make sense to require the network systems to support a soft quality of service (QoS) guarantee, i.e., to guarantee a service requirement with a certain high probability. In this paper, we intend to build a solid mathematical foundation to help better understand the stochastic energy constraint and the inherent correlation between QoS and the uncertain energy supply. We utilize a calculus approach to model the cumulative amount of charged energy and the cumulative amount of consumed energy. We derive upper and lower bounds on the remaining energy level based on a stochastic energy charging rate and a stochastic energy discharging rate. By building the bridge between energy consumption and task execution (i.e., service), we study the QoS guarantee under the constraint of uncertain energy sources. We further show how performance bounds can be improved if some strong assumptions can be made.