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A Hybrid Delay Aware Clustered Routing Approach Using Aquila Optimizer and Firefly Algorithm in Internet of Things

Author

Listed:
  • Mehdi Hosseinzadeh

    (Institute of Research and Development, Duy Tan University, Da Nang 550000, Vietnam
    School of Medicine and Pharmacy, Duy Tan University, Da Nang 550000, Vietnam
    Computer Science, University of Human Development, Sulaymaniyah 0778-6, Iraq)

  • Liliana Ionescu-Feleaga

    (Department of Accounting and Audit, Bucharest University of Economic Studies, 010374 Bucharest, Romania)

  • Bogdan-Ștefan Ionescu

    (Department of Management Information System, Bucharest University of Economic Studies, 010374 Bucharest, Romania)

  • Mahyar Sadrishojaei

    (Faculty of Industry, University of Applied Science and Technology (UAST), Tehran 11369, Iran)

  • Faeze Kazemian

    (Department of Computer Science, University of Applied Science and Technology (UAST), Tehran 11369, Iran)

  • Amir Masoud Rahmani

    (Future Technology Research Center, National Yunlin University of Science and Technology, 123 University Road, Section 3, Douliou, Yunlin 64002, Taiwan)

  • Faheem Khan

    (Department of Computer Engineering, Gachon University, Seongnam 13120, Republic of Korea)

Abstract

Protocols for clustering and routing in the Internet of Things ecosystem should consider minimizing power consumption. Existing approaches to cluster-based routing issues in the Internet of Things environment often face the challenge of uneven power consumption. This study created a clustering method utilising swarm intelligence to obtain a more even distribution of cluster heads. In this work, a firefly optimization method and an aquila optimizer algorithm are devised to select the intermediate and cluster head nodes required for routing in accordance with the NP-Hard nature of clustered routing. The effectiveness of this hybrid clustering and routing approach has been evaluated concerning the following metrics: remaining energy, mean distances, number of hops, and node balance. For assessing Internet of things platforms, metrics like network throughput and the number of the living node are crucial, as these systems rely on battery-operated equipment to regularly capture environment data and transmit specimens to a base station. Proving effective, the suggested technique has been found to improve system energy usage by at least 18% and increase the packet delivery ratio by at least 25%.

Suggested Citation

  • Mehdi Hosseinzadeh & Liliana Ionescu-Feleaga & Bogdan-Ștefan Ionescu & Mahyar Sadrishojaei & Faeze Kazemian & Amir Masoud Rahmani & Faheem Khan, 2022. "A Hybrid Delay Aware Clustered Routing Approach Using Aquila Optimizer and Firefly Algorithm in Internet of Things," Mathematics, MDPI, vol. 10(22), pages 1-15, November.
    • Handle: RePEc:gam:jmathe:v:10:y:2022:i:22:p:4331-:d:977181
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    References listed on IDEAS

    as
    1. Jan Lansky & Mahyar Sadrishojaei & Amir Masoud Rahmani & Mazhar Hussain Malik & Faeze Kazemian & Mehdi Hosseinzadeh, 2022. "Development of a Lightweight Centralized Authentication Mechanism for the Internet of Things Driven by Fog," Mathematics, MDPI, vol. 10(22), pages 1-17, November.
    2. Cheng peng Liu & Bin Xia & Liye Zhang & Bo Rong, 2022. "Firefly Optimization-Based Cooperative Localization Algorithm for Intelligent IoT," Discrete Dynamics in Nature and Society, Hindawi, vol. 2022, pages 1-7, June.
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    Cited by:

    1. Mahyar Sadrishojaei & Faeze Kazemian, 2024. "Clustered Routing Scheme in IoT During COVID-19 Pandemic Using Hybrid Black Widow Optimization and Harmony Search Algorithm," SN Operations Research Forum, Springer, vol. 5(2), pages 1-25, June.

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