Title: Novel routing techniques based on ant colony optimisation for static and dynamic internet of things network

Authors: Anukriti Sharma; Sharad Sharma; Dushyant Gupta

Addresses: Electronics and Communication Engineering Department, Maharishi Markandeshwar (Deemed to be University), Mullana – Ambala, Haryana, India ' Electronics and Communication Engineering Department, Maharishi Markandeshwar (Deemed to be University), Mullana – Ambala, Haryana, India ' Electronics Department, Institute of Honors and Evening Studies, Kurukshetra University, Kurukshetra, Haryana, India

Abstract: In this paper, two meta-heuristic approaches have been optimised using swarm intelligence (SI) optimisation technique. The method comprises computation of shortest path of both, static and dynamic internet of things (IoT) network using world's best algorithms, namely, 'breadth first search' and 'Dijkstra algorithm'. Further, the determined route has been optimised using ant colony optimisation. The issue of route selection to reach the destination, as well as parameters such as network energy, departed node count, residual energy of IoT nodes, and critical points of IoT nodes have been explored using proposed smart routing techniques. The two unique routing approaches have been simulated with rigorous iteration run, t = 2,000. The proposed methods, ABMS technique and ABMD technique has been simulated using MATLAB. After comparing efficiency between both techniques, ABMS method outperforms the ABMD routing technique for IoT network. A significant energy savings has been reported, extending network lifetime of a static IoT network scenario.

Keywords: intelligent systems; swarm intelligence; ant colony optimisation; internet of things; IoT.

DOI: 10.1504/IJISTA.2024.139740

International Journal of Intelligent Systems Technologies and Applications, 2024 Vol.22 No.2, pp.193 - 212

Received: 13 Jul 2022
Accepted: 02 Nov 2023
Published online: 05 Jul 2024 *

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