This article examines the control and routing protocols of wireless sensor networks that have been able to use reinforcement learning techniques, which is one of the machine learning methods, to achieve energy efficiency in the network. This technique is based on the method of reward and punishment, which is similar to the process of learning in children. Proper energy management and therefore increasing the lifetime of wireless sensor networks is always one of the main challenges of this type of network due to energy limitations in its nodes. The purpose of writing this article is to learn more about the methods presented. In this paper, various methods that try to use the reinforcement learning process to improve the behavior of wireless sensor networks and make them smarter are introduced and examined. Also, the evolution of these methods and the ratio of the superiority of each to the other have been examined.
Forghani, A., Binesh Marvasti, M. R., & Asghari, S. A. (2024). An Overview of Control and Routing Methods in Wireless Sensor Networks Using Reinforcement Learning. Electronics Industries, 13(3), 99-120.
MLA
Ali Forghani; Mohammad Reza Binesh Marvasti; Seyyed Amir Asghari. "An Overview of Control and Routing Methods in Wireless Sensor Networks Using Reinforcement Learning". Electronics Industries, 13, 3, 2024, 99-120.
HARVARD
Forghani, A., Binesh Marvasti, M. R., Asghari, S. A. (2024). 'An Overview of Control and Routing Methods in Wireless Sensor Networks Using Reinforcement Learning', Electronics Industries, 13(3), pp. 99-120.
VANCOUVER
Forghani, A., Binesh Marvasti, M. R., Asghari, S. A. An Overview of Control and Routing Methods in Wireless Sensor Networks Using Reinforcement Learning. Electronics Industries, 2024; 13(3): 99-120.
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