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

## TL;DR

This paper develops optimal transmission policies for energy harvesting devices monitoring processes with alarms, extending Age of Information metrics to account for process states and demonstrating energy reservation strategies through numerical evaluation.

## Contribution

It introduces a Markov Decision Process framework that incorporates process states and AoI penalties to optimize energy use in alarm-monitoring systems.

## Key findings

- Policies effectively reserve energy for future alarms
- Extended AoI metrics account for process state changes
- Numerical results show improved energy management

## Abstract

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.