Optimal Update for Energy Harvesting Sensor with Reliable Backup Energy

TL;DR

This paper develops an optimal updating policy for energy-harvesting sensors with backup energy, minimizing Age of Information and backup energy costs, using a Markov decision process with a threshold structure.

Contribution

It introduces a novel threshold-based optimal policy for energy-harvesting sensors with reliable backup energy, improving update timeliness and energy efficiency.

Findings

Optimal policy outperforms baseline policies.

Threshold structure simplifies policy computation.

Significant reduction in AoI and backup energy use.

Abstract

In this paper, we consider an information update system where a wireless sensor sends timely updates to the destination over an erasure channel with the supply of harvested energy and reliable backup energy. The metric Age of Information(AoI) is adopted to measure the timeliness of the received updates at the destination. We aim to find the optimal information updating policy that minimizes the time-average weighted sum of the AoI and the reliable backup energy cost by formulating an infinite state Markov decision process(MDP). The optimal information updating policy is proved to have a threshold structure. Based on this special structure, an algorithm for efficiently computing the optimal policy is proposed. Numerical results show that the optimal updating policy proposed outperforms baseline policies.