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FONIC: an energy-conscious fuzzy-based optimized nature-inspired clustering technique for IoT networks

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Abstract

The Internet of Things (IoT) has developed into a new area of study that promises to elevate human culture to a higher level of sophistication. The network is essential in IoT since it is responsible for relaying information from sensors to the sink. In the IoT, where many devices share finite resources, extending the lifespan of the network is a difficult challenge. The lifespan of a network can be prolonged by the use of clustering. However, initial network nodes’ energy might be quickly depleted by incorrectly selecting cluster heads (CHs). This research aims to provide a solution by suggesting a fuzzy-based optimized nature-inspired clustering technique (FONIC) to choose the best CH to sustain the network over time. When dealing with unreliable network conditions, the precise solution provided by fuzzy logic (FL) is invaluable. Therefore, in order to calculate a fitness value, FL is used on network metrics such as energy, distance, degree, and centrality. In the end, the right CH is chosen with the help of the Penguin Search Optimization Algorithm (PeSOA). Python is utilized to do extensive simulations that confirm the effectiveness of the suggested FONIC protocol. Other protocols, including FIGWO, HMGWO, LEACH-PRO, FGWSTERP, and SSMOECHS, are contrasted with the proposed FONIC protocol. Compared to other top-tier protocols, the suggested FONIC protocol was shown to perform better than any of them, improving the ratio of packet transmission by 10% and network lifespans by 10–15%.

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The data that support the findings of this study, the software application or custom code used to solve the proposed methods of this study is available from the corresponding author upon request

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Acknowledgements

The University of Babylon and Al-Mustaqbal University in Iraq are greatly appreciated for their assistance, which the writers really appreciate.

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Authors and Affiliations

  1. Department of Information Networks, College of Information Technology, University of Babylon, Babylon, Iraq

    Suha Abdulhussein Abdulzahra

  2. Department of Cyber Security, College of Sciences, Al-Mustaqbal University, Babylon, Hillah, 51001, Iraq

    Ali Kadhum M. Al-Qurabat

  3. Department of Computer Science, College of Science for Women, University of Babylon, Babylon, Iraq

    Ali Kadhum M. Al-Qurabat

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  1. Suha Abdulhussein Abdulzahra
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  2. Ali Kadhum M. Al-Qurabat
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Correspondence to Ali Kadhum M. Al-Qurabat.

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Abdulzahra, S.A., Al-Qurabat, A.K.M. FONIC: an energy-conscious fuzzy-based optimized nature-inspired clustering technique for IoT networks. J Supercomput 80, 19845–19897 (2024). https://doi.org/10.1007/s11227-024-06229-z

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