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Learning nodes: machine learning-based energy and data management strategy.
- Source :
-
EURASIP Journal on Wireless Communications & Networking . 9/15/2021, Vol. 2021 Issue 1, p1-16. 16p. - Publication Year :
- 2021
-
Abstract
- The efficient use of resources in wireless communications has always been a major issue. In the Internet of Things (IoT), the energy resource becomes more critical. The transmission policy with the aid of a coordinator is not a viable solution in an IoT network, since a node should report its state to the coordinator for scheduling and it causes serious signaling overhead. Machine learning algorithms can provide the optimal distributed transmission mechanism with little overhead. A node can learn by itself by utilizing the machine learning algorithm and make the optimal transmission decision on its own. In this paper, we propose a novel learning Medium Access Control (MAC) protocol with learning nodes. Nodes learn the optimal transmission policy, i.e., minimizing the data and energy queue levels, using the Q-learning algorithm. The performance evaluation shows that the proposed scheme enhances the queue states and throughput. [ABSTRACT FROM AUTHOR]
Details
- Language :
- English
- ISSN :
- 16871472
- Volume :
- 2021
- Issue :
- 1
- Database :
- Academic Search Index
- Journal :
- EURASIP Journal on Wireless Communications & Networking
- Publication Type :
- Academic Journal
- Accession number :
- 152461675
- Full Text :
- https://doi.org/10.1186/s13638-021-02047-6