Title: Task scheduling optimisation for wireless sensor modules in cloud-based systems

Authors: A. Ananya; B.V. Santhosh Krishna; A. Murugavel; C. Sivakumaran

Addresses: Department of Artificial Intelligence and Machine Learning, M. Kumarasamy College of Engineering, Karur and Salem, Tamil Nadu, India ' Department of Computer Science and Engineering, Bangalore Technological Institute, Bengaluru 560035, Karnataka, India ' Department of Computer Science Engineering, V.S.B. Engineering College, Coimbatore, Tamil Nadu, India ' Science Academy Press, Photon Technologies, Chennai, Tamil Nadu, India

Abstract: Scheduling algorithms demonstrate the critical function they play in the cloud data centres in determining a potential time table for the work. Since the goal is to achieve the shortest total execution time, existing research has demonstrated that the job scheduling issue is NP-complete. We address the problem of minimising total layover time by scheduling a set of l jobs across a set of |G| groups and m cloud resources. Here, we describe a pair-based work scheduling method based on the well-known optimisation process known as the Hungarian algorithm for cloud data centres. Two performance indicators, specifically makespan and averaged cloud utilisation, are used to assess their performances via simulation. The method will decrease task waiting times and increase resource efficiency as a consequence. The results of the experiment demonstrate that the suggested technique enhances resource consumption while decreasing task execution times.

Keywords: task management; Hungarian method; normalisation; cloud computing; makespan cloud use; node weight method; Hopfield neural network.

DOI: 10.1504/IJIPT.2026.152211

International Journal of Internet Protocol Technology, 2026 Vol.19 No.1, pp.1 - 8

Accepted: 15 Mar 2025
Published online: 11 Mar 2026 *

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