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Clustering Based Optimal Cluster Head Selection Using Bio-Inspired Neural Network in Energy Optimization of 6LowPAN

Author

Listed:
  • Mudassir Khan

    (Department of Computer Science, College of Science & Arts Tanumah, King Khalid University, Abha 62529, Saudi Arabia)

  • A. Ilavendhan

    (Department of Computer Science and Engineering, Veltech Rangarajan Dr. Sagunthala R&D Institute of Science and Technology, Avadi, Chennai 600062, India)

  • C. Nelson Kennedy Babu

    (Department of Computer Science and Engineering, Saveetha School of Engineering, Chennai 602105, India)

  • Vishal Jain

    (Department of Computer Science and Engineering, School of Engineering and Technology, Sharda University, Greater Noida 201310, India)

  • S. B. Goyal

    (Faculty of Information Technology, City University, Petaling Jaya 46100, Malaysia)

  • Chaman Verma

    (Department of Media and Educational Informatics, Faculty of Informatics, Eotvos Lorand University, 1053 Budapest, Hungary)

  • Calin Ovidiu Safirescu

    (Environment Protection Department, Faculty of Agriculture, University of Agriculture Sciences and Veterrnary Medicine Cluj-Napoca, Calea Manastur No 3-5, 400372 Cluj-Napoca, Romania)

  • Traian Candin Mihaltan

    (Faculty of Building Services, Technical University of Cluj-Napoca, 400114 Cluj-Napoca, Romania)

Abstract

The goal of today’s technological era is to make every item smart. Internet of Things (IoT) is a model shift that gives a whole new dimension to the common items and things. Wireless sensor networks, particularly Low-Power and Lossy Networks (LLNs), are essential components of IoT that has a significant influence on daily living. Routing Protocol for Low Power and Lossy Networks (RPL) has become the standard protocol for IoT and LLNs. It is not only used widely but also researched by various groups of people. The extensive use of RPL and its customization has led to demanding research and improvements. There are certain issues in the current RPL mechanism, such as an energy hole, which is a huge issue in the context of IoT. By the initiation of Grid formation across the sensor nodes, which can simplify the cluster formation, the Cluster Head (CH) selection is accomplished using fish swarm optimization (FSO). The performance of the Graph-Grid-based Convolution clustered neural network with fish swarm optimization (GG-Conv_Clus-FSO) in energy optimization of the network is compared with existing state-of-the-art protocols, and GG-Conv_Clus-FSO outperforms the existing approaches, whereby the packet delivery ratio (PDR) is enhanced by 95.14%.

Suggested Citation

  • Mudassir Khan & A. Ilavendhan & C. Nelson Kennedy Babu & Vishal Jain & S. B. Goyal & Chaman Verma & Calin Ovidiu Safirescu & Traian Candin Mihaltan, 2022. "Clustering Based Optimal Cluster Head Selection Using Bio-Inspired Neural Network in Energy Optimization of 6LowPAN," Energies, MDPI, vol. 15(13), pages 1-14, June.
    • Handle: RePEc:gam:jeners:v:15:y:2022:i:13:p:4528-:d:844146
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    References listed on IDEAS

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    Cited by:

    1. Regonda Nagaraju & Venkatesan C & Kalaivani J & Manju G & S. B. Goyal & Chaman Verma & Calin Ovidiu Safirescu & Traian Candin Mihaltan, 2022. "Secure Routing-Based Energy Optimization for IoT Application with Heterogeneous Wireless Sensor Networks," Energies, MDPI, vol. 15(13), pages 1-16, June.

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