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Journal of Intelligent Systems and Internet of Things
Volume 11 , Issue 2, PP: 08-21 , 2024 | Cite this article as | XML | Html |PDF

Title

Energy Efficient Cluster Head Selection Using Hybrid RL-PSO Approach

  Arpita Choudhary 1 * ,   N. C. Barwar 2 ,   Vikas Chouhan 3

1  Department of Computer science and Engineering, MBM University Jodhpur, India
    (erarpita@gmail.com)

2  Department of Computer science and Engineering, MBM University Jodhpur, India
    ( ncbarwar@gmail.com )

3  Canadian Institute for Cybersecurity, NB, Canada
    (vikas.chouhan@unb.ca)


Doi   :   https://doi.org/10.54216/JISIoT.110201

https://doi.org/10.54216/JISIoT.110201

Abstract :

Wireless Sensor Networks (WSNs) are crucial in several applications, highlighting the need of effective clustering and fault detection systems.  This paper introduces a novel approach that uses Reinforcement Learning (RL) and Particle Swarm Optimization (PSO) to optimize cluster head selection and enhance fault detection capabilities within WSNs. The proposed hybrid algorithm operates in two phases, combining the explorative capabilities of RL with the optimization process of PSO to select cluster heads based on residual energy and connectivity considerations. By continuously monitoring the network's residual energy state and the number of active nodes, the proposed method ensures prolonged network lifetime and improved overall performance. Our experimental results demonstrate the superior performance of the hybrid RL-PSO approach compared to traditional clustering algorithms, showcasing significant improvements in optimizer accuracy, residual energy preservation, and fault detection efficiency.

Keywords :

Wireless Sensor Networks (WSNs); Clustering; Reinforcement Learning (RL); Particle Swarm Optimization (PSO) and Fault Detection

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Cite this Article as :
Style #
MLA Arpita Choudhary , N. C. Barwar , Vikas Chouhan. "Energy Efficient Cluster Head Selection Using Hybrid RL-PSO Approach." Journal of Intelligent Systems and Internet of Things, Vol. 11, No. 2, 2024 ,PP. 08-21 (Doi   :  https://doi.org/10.54216/JISIoT.110201)
APA Arpita Choudhary , N. C. Barwar , Vikas Chouhan. (2024). Energy Efficient Cluster Head Selection Using Hybrid RL-PSO Approach. Journal of Journal of Intelligent Systems and Internet of Things, 11 ( 2 ), 08-21 (Doi   :  https://doi.org/10.54216/JISIoT.110201)
Chicago Arpita Choudhary , N. C. Barwar , Vikas Chouhan. "Energy Efficient Cluster Head Selection Using Hybrid RL-PSO Approach." Journal of Journal of Intelligent Systems and Internet of Things, 11 no. 2 (2024): 08-21 (Doi   :  https://doi.org/10.54216/JISIoT.110201)
Harvard Arpita Choudhary , N. C. Barwar , Vikas Chouhan. (2024). Energy Efficient Cluster Head Selection Using Hybrid RL-PSO Approach. Journal of Journal of Intelligent Systems and Internet of Things, 11 ( 2 ), 08-21 (Doi   :  https://doi.org/10.54216/JISIoT.110201)
Vancouver Arpita Choudhary , N. C. Barwar , Vikas Chouhan. Energy Efficient Cluster Head Selection Using Hybrid RL-PSO Approach. Journal of Journal of Intelligent Systems and Internet of Things, (2024); 11 ( 2 ): 08-21 (Doi   :  https://doi.org/10.54216/JISIoT.110201)
IEEE Arpita Choudhary, N. C. Barwar, Vikas Chouhan, Energy Efficient Cluster Head Selection Using Hybrid RL-PSO Approach, Journal of Journal of Intelligent Systems and Internet of Things, Vol. 11 , No. 2 , (2024) : 08-21 (Doi   :  https://doi.org/10.54216/JISIoT.110201)