# Age-Aware Status Update Control for Energy Harvesting IoT Sensors via Reinforcement Learning

arXiv: https://arxiv.org/abs/2004.12684 · HTML: https://mlsanity.com/paper/2004.12684/

## Key facts

- Cited by 1 papers in the map (data through 14 Oct 2026).
- First posted on arXiv 27 Apr 2020.

## Built on by (most cited first, 1 of 1)

- [Learning to Minimize Age of Information over an Unreliable Channel with Energy Harvesting](https://mlsanity.com/paper/2106.16037/) (2021)

## Abstract (arXiv)

We consider an IoT sensing network with multiple users, multiple energy harvesting sensors, and a wireless edge node acting as a gateway between the users and sensors. The users request for updates about the value of physical processes, each of which is measured by one sensor. The edge node has a cache storage that stores the most recently received measurements from each sensor. Upon receiving a request, the edge node can either command the corresponding sensor to send a status update, or use the data in the cache. We aim to find the best action of the edge node to minimize the average long-term cost which trade-offs between the age of information and energy consumption. We propose a practical reinforcement learning approach that finds an optimal policy without knowing the exact battery levels of the sensors.