# Control of Status Updates for Energy Harvesting Devices that Monitor Processes with Alarms

arXiv: https://arxiv.org/abs/1907.03826 · HTML: https://mlsanity.com/paper/1907.03826/

## Key facts

- Cited by 3 papers in the map (data through 14 Oct 2026).
- First posted on arXiv 8 Jul 2019.

## Built on by (most cited first, 3 of 3)

- [Semantic-Aware Remote Estimation of Multiple Markov Sources Under Constraints](https://mlsanity.com/paper/2403.16855/) (2024)
- [Proactive and AoI-aware Failure Recovery for Stateful NFV-enabled Zero-Touch 6G Networks: Model-Free DRL Approach](https://mlsanity.com/paper/2103.03817/) (2021)
- [Semantic Text Transmission via Prediction with Small Language Models: Cost-Similarity Trade-off](https://mlsanity.com/paper/2403.00290/) (2024)

## Abstract (arXiv)

In this work, we derive optimal transmission policies in an energy harvesting status update system. The system monitors a stochastic process which can be either in a normal or in an alarm state of operation. We capture the freshness of status updates for each state of the stochastic process by introducing two Age of Information (AoI) variables and extend the definition of AoI to account for the state changes of the stochastic process. We formulate the problem at hand as a Markov Decision Process which, under the assumption that the demand for status updates is higher when the stochastic process is in the alarm state, utilizes a transition cost function that applies linear and non-linear penalties based on AoI and the state of the stochastic process. Finally, we evaluate numerically the derived policies and illustrate their effectiveness for reserving energy in anticipation of future alarm states.