Age-Aware Status Update Control for Energy Harvesting IoT Sensors via Reinforcement Learning
Abstract
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.
- Publication:
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arXiv e-prints
- Pub Date:
- April 2020
- DOI:
- 10.48550/arXiv.2004.12684
- arXiv:
- arXiv:2004.12684
- Bibcode:
- 2020arXiv200412684H
- Keywords:
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- Electrical Engineering and Systems Science - Signal Processing;
- Computer Science - Artificial Intelligence;
- Computer Science - Machine Learning
- E-Print:
- 6 pages, 4 figures