Optimizing Version Innovation Age for Monitoring Markovian Source in Energy-Harvesting Systems

TL;DR

This paper develops an optimal transmission policy for energy-harvesting systems monitoring a Markov process, minimizing the Version Innovation Age metric, and demonstrates its superiority over baseline policies through numerical analysis.

Contribution

It introduces a threshold-based optimal policy for minimizing VIA in energy-harvesting Markov source monitoring, validated through analytical and numerical methods.

Findings

Optimal policy is threshold-based, depending on battery, state, and VIA.

Numerical results show the proposed policy outperforms baseline strategies.

Analytical structure of the policy is verified through simulations.

Abstract

We study the real-time remote tracking of a two-state Markov process by an energy harvesting source. The source decides whether to transmit over an unreliable channel based on the state. We formulate this scenario as a Markov decision process (MDP) to determine the optimal transmission policy that minimizes the average Version Innovation Age (VIA) as a performance metric. We demonstrate that the optimal transmission policy is threshold-based, determined by the battery level, source state, and VIA value. We numerically verify the analytical structure of the optimal policy and compare the performance of our proposed policy against two baseline policies across various system parameters, establishing the superior performance of our approach.