Title: Adjustable rotation gate based quantum evolutionary algorithm for energy optimisation in cloud computing systems

Authors: Jyoti Chauhan; Taj Alam

Addresses: Department of Computer Science and Engineering and Information Technology, Jaypee Institute of Information Technology, Noida U.P., 201309, India ' Department of Computer Science and Engineering and Information Technology, Jaypee Institute of Information Technology, Noida U.P., 201309, India

Abstract: The widespread adoption of cloud computing and a rapid rise in capacity and scale of data centres results in a significant increase in electricity usage, rising data centre ownership costs, and increased carbon footprints. One of the challenging research problems of this point in time is to reduce the energy consumption in cloud data centres which leads motivation of green cloud computing. This article presents an energy efficient improved quantum evolutionary algorithm (QEA) to provide optimal solution for NP-hard task scheduling problems in cloud computing. An adjustable quantum rotation gate operator with adaptively dynamic adjustment of the rotation angle is developed according to the evolutionary generations and change in fitness values in each generation which serves as a major operation to update the population of the conventional QEA. The efficiency and accuracy of proposed QEA are greatly improved to measure the energy efficiency, makespan and resource utilisation in heterogeneous CC environment. Simulation results of the CloudSim shows that proposed QEA is superior to traditional PSO and GA to solve NP-hard task scheduling problems in green CC.

Keywords: cloud computing; scheduling; quantum evolutionary algorithm; QEA; rotation gate; particle swarm optimisation; PSO; genetic algorithm; energy efficiency; task scheduling problem; resource allocation; makespan.

DOI: 10.1504/IJCSE.2024.139693

International Journal of Computational Science and Engineering, 2024 Vol.27 No.4, pp.414 - 433

Received: 11 Oct 2022
Accepted: 04 Jul 2023
Published online: 05 Jul 2024 *

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