Journal of Intelligent Systems and Internet of Things

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https://doi.org/10.54216/JISIoT

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Volume 11 , Issue 2 , PP: 08-21, 2024 | Cite this article as | XML | Html | PDF | Full Length Article

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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    [26] Investigation on load harmonic reduction through solar-power utilization in intermittent SSFI using particle swarm, genetic, and modified firefly optimization algorithms,Albert, JohnyRenoald; Sharma, Aditi,Rajani, B., Mishra, Ashish,Saxena, Ankur, Nandagopal, C., Mewada, Shivlal, Journal of Intelligent & Fuzzy Systems, vol. 42, no. 4, pp. 4117-4133, 2022 SCI,IF:2 ,ISSN 1064-1246 (P)

    [27] Utilizing the intelligence edge framework for robotic upper limb rehabilitation in home, MethodsX, Prashant K. Jamwal, Aibek Niyetkaliyev, Shahid Hussain, Aditi Sharma, Paulette Van Vliet, Volume 11, 2023, 102312, ISSN 2215-0161, https://doi.org/10.1016/j.mex.2023.102312, ESCI, Scopus,WoS

    [28] Ant Colony Optimized XGBoost for Early Diabetes Detection: A Hybrid Approach in Machine Learning, Krishna, A.Y. ,Kiran, K.R.,Sai, N.R, Sharma Aditi, .Praveen, S.P.,Pandey, J., Journal of Intelligent Systems and Internet of Things, 2023, 10(2), pp. 76–89

    [29] An Ensemble Learning Approach for detection of Chronic Kidney Disease (CKD), B. Narasimha Swamy,Rajeswari Nakka,Aditi Sharma,S. Phani Praveen,Venkata Nagaraju Thatha,Kumar Gautam. (2023), Journal of Intelligent Systems and Internet of Things, 10 ( 2 ), 38-48.

    [30] Lisha Yugal,Suresh Kaswan,B. S. Bhatia,Aditi Sharma, IoT-based Emulated Performance Evaluation NLP Model for Advanced Learners in Academia 4.0 and Industries 4.0, Journal of Intelligent Systems and Internet of Things, Vol. 10 , No. 2 , (2023) : 36-75 (Doi   :  https://doi.org/10.54216/JISIoT.100206)

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    Cite This Article As :
    Choudhary, Arpita. , C., N.. , Chouhan, Vikas. Energy Efficient Cluster Head Selection Using Hybrid RL-PSO Approach. Journal of Intelligent Systems and Internet of Things, vol. , no. , 2024, pp. 08-21. DOI: https://doi.org/10.54216/JISIoT.110201
    Choudhary, A. C., N. Chouhan, V. (2024). Energy Efficient Cluster Head Selection Using Hybrid RL-PSO Approach. Journal of Intelligent Systems and Internet of Things, (), 08-21. DOI: https://doi.org/10.54216/JISIoT.110201
    Choudhary, Arpita. C., N.. Chouhan, Vikas. Energy Efficient Cluster Head Selection Using Hybrid RL-PSO Approach. Journal of Intelligent Systems and Internet of Things , no. (2024): 08-21. DOI: https://doi.org/10.54216/JISIoT.110201
    Choudhary, A. , C., N. , Chouhan, V. (2024) . Energy Efficient Cluster Head Selection Using Hybrid RL-PSO Approach. Journal of Intelligent Systems and Internet of Things , () , 08-21 . DOI: https://doi.org/10.54216/JISIoT.110201
    Choudhary A. , C. N. , Chouhan V. [2024]. Energy Efficient Cluster Head Selection Using Hybrid RL-PSO Approach. Journal of Intelligent Systems and Internet of Things. (): 08-21. DOI: https://doi.org/10.54216/JISIoT.110201
    Choudhary, A. C., N. Chouhan, V. "Energy Efficient Cluster Head Selection Using Hybrid RL-PSO Approach," Journal of Intelligent Systems and Internet of Things, vol. , no. , pp. 08-21, 2024. DOI: https://doi.org/10.54216/JISIoT.110201