Stochastic Routing and Scheduling Policies for Energy Harvesting Communication Networks

TL;DR

This paper introduces stochastic routing and scheduling policies for energy harvesting communication networks, ensuring queue stability under sustainable energy and data arrivals, with minimal performance gap compared to traditional methods.

Contribution

Proposes two novel energy harvesting-aware routing-scheduling policies based on stochastic subgradient methods, guaranteeing queue stability in energy harvesting networks.

Findings

Policies guarantee queue stability under sustainable conditions.

Numerical results show minimal performance gap with classical algorithms.

Proposed methods adapt stochastic backpressure algorithms for energy harvesting scenarios.

Abstract

In this paper, we study the joint routing-scheduling problem in energy harvesting communication networks. Our policies, which are based on stochastic subgradient methods on the dual domain, act as an energy harvesting variant of the stochastic family of backpresure algorithms. Specifically, we propose two policies: (i) the Stochastic Backpressure with Energy Harvesting (SBP-EH), in which a node's routing-scheduling decisions are determined by the difference between the Lagrange multipliers associated to their queue stability constraints and their neighbors'; and (ii) the Stochastic Soft Backpressure with Energy Harvesting (SSBP-EH), an improved algorithm where the routing-scheduling decision is of a probabilistic nature. For both policies, we show that given sustainable data and energy arrival rates, the stability of the data queues over all network nodes is guaranteed. Numerical results corroborate the stability guarantees and illustrate the minimal gap in performance that our policies offer with respect to classical ones which work with an unlimited energy supply.