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Clustered Routing Scheme in IoT During COVID-19 Pandemic Using Hybrid Black Widow Optimization and Harmony Search Algorithm

Author

Listed:
  • Mahyar Sadrishojaei

    (University of Applied Science and Technology (UAST))

  • Faeze Kazemian

    (University of Applied Science and Technology (UAST))

Abstract

The coronavirus, known as COVID-19, is a worldwide disease that has become a fascinating topic for researchers. COVID-19 is rapidly affecting the world and putting pressure on sections of society. Solutions based on new technologies are very efficient. The Internet of Things plays an essential role in many areas, including medical care and health systems. Data such as a patient’s heartbeat, hypertension, oxygen saturation, and temp are relayed through this system in exceptional cases. Nodes with low power consumption on the patient’s body regularly produce reports for the medical center. The unbalanced power consumption of nodes may make it difficult to transfer data to data centers. Therefore, a robust routing protocol is essential for communication and minimizes the power usage of devices. Clustering is one of the most effective routing algorithms for reducing energy usage and extending system lifetime. According to the NP-Hard structure of clustering, a black widow optimization technique and a harmony search algorithm are developed in this article to pick the intermediate and cluster head nodes necessary for routing, respectively. In terms of network lifespan, power consumption, latency, and active and inactive nodes, NS-3 simulation results indicated that the suggested technique outperforms chicken swarm optimization, multipath optimized link state routing, grey wolf optimization, and genetic algorithm. The proposed strategy reduces network energy consumption as well as latency by at least 10% and 11%, respectively, compared to current clustering techniques.

Suggested Citation

  • 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.
    • Handle: RePEc:spr:snopef:v:5:y:2024:i:2:d:10.1007_s43069-024-00331-x
    DOI: 10.1007/s43069-024-00331-x
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    References listed on IDEAS

    as
    1. Surjit Singh & Rajeev Mohan Sharma, 2018. "HSCA: a novel harmony search based efficient clustering in heterogeneous WSNs," Telecommunication Systems: Modelling, Analysis, Design and Management, Springer, vol. 67(4), pages 651-667, April.
    2. 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.
    3. S. T. Sheriba & D. Hevin Rajesh, 2021. "Energy-efficient clustering protocol for WSN based on improved black widow optimization and fuzzy logic," Telecommunication Systems: Modelling, Analysis, Design and Management, Springer, vol. 77(1), pages 213-230, May.
    4. M. Umamaheswari & N. Rengarajan, 2020. "Intelligent exhaustion rate and stability control on underwater wsn with fuzzy based clustering for efficient cost management strategies," Information Systems and e-Business Management, Springer, vol. 18(3), pages 283-294, September.
    5. Amir Masoud Rahmani & Rizwan Ali Naqvi & Mazhar Hussain Malik & Tauqeer Safdar Malik & Mahyar Sadrishojaei & Mehdi Hosseinzadeh & Ali Al-Musawi, 2021. "E-Learning Development Based on Internet of Things and Blockchain Technology during COVID-19 Pandemic," Mathematics, MDPI, vol. 9(24), pages 1-13, December.
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