An Energy Efficient Reinforcement Learning Based Clustering Approach for Wireless Sensor Network

Kaur, Navpreet and Aulakh, Inderdeep Kaur (2021) An Energy Efficient Reinforcement Learning Based Clustering Approach for Wireless Sensor Network. EAI Endorsed Transactions on Scalable Information Systems, 8 (31). e6. ISSN 2032-9407

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Abstract

Clustering is known to conserve energy and enhance the network lifetime of Wireless Sensor Network (WSN). Although, the topic of energy efficiency has been well researched in conventional WSN, but it has not been extensively studied. In theresearch, Reinforcement Learning (RL) based energy-aware clustering algorithm is proposed by which the neighboring nodes in the cluster selects an appropriate Cluster Head ( CH) by observing the environmental conditions like as energy consumptionand coverage that is computed as distance from the CH to the Base Station (BS). An optimal cluster is selected by each neighboring node, which minimized the energy consumption and network lifetime. The problem of selecting an optimal CH is resolved using the RL approach. Using the RL approach, the CH having the highest reward point is selected for data communication. The results show that energy saving of 7.41%, 3.27%, 4.03%, and 2.79 % is achieved for 100, 200, 300, and 400 deployed nodes, respectively.

Item Type: Article
Uncontrolled Keywords: Wireless Sensor Network (WSN), Clustering, Reinforcement Learning, Energy Consumption, Network Lifetime
Subjects: Q Science > QA Mathematics > QA75 Electronic computers. Computer science
QA75 Electronic computers. Computer science
T Technology > T Technology (General)
Depositing User: EAI Editor IV
Date Deposited: 09 Jul 2021 08:31
Last Modified: 09 Jul 2021 08:31
URI: https://eprints.eudl.eu/id/eprint/4395

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