Tversky-Hillenger distance-based fuzzy local information C-means clustering technique in IoT routing for cluster head selection

Amit Vijay Kore and Mishra Manoj Ranjan

International Journal of Industrial and Systems Engineering, 2026, vol. 53, issue 1, 99-120

Abstract: Dependable and secure IoT communication and correlation are necessary for the appropriate operation of IoT networks. An effectual CHS approach is developed using the proposed Tversky-Hillenger distance-based FLICM clustering algorithm. However, the CHS model is newly developed by derived by the incorporation of the Tversky index and Hillenger distance and FILCM clustering algorithm, respectively. At first, nodes are simulated in the IoT environment. The sensor nodes are permitted to sense data from an environment, such that this data is effectively routed to the BS through CH. The quality of data communication is enhanced by transferring data to BS through CH, which improves the performance of routing. However, the routing link must be error-free during the transfer of data between CH and BS. Thus, the developed CHS model achieved better performance with a throughput of 0.4390, delay of 0.5882 s, and energy consumption of 0.5614 J.

Keywords: rider optimisation algorithm; cluster head selection; Tversky index; Hillenger distance; routing. (search for similar items in EconPapers)
Date: 2026
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