Quadratic Particle Swarm Optimisation Algorithm for Task Scheduling Based on Cloud Computing Server

Guanghui Wei ()
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Guanghui Wei: Artificial Intelligence and Big Data College, Chongqing College of Electronic Engineering, Chongqing 401331, P. R. China

Journal of Information & Knowledge Management (JIKM), 2023, vol. 22, issue 01, 1-13

Abstract: The task scheduling is one of the core problems of cloud computing and aims to assign tasks reasonably, realise the optimal scheduling strategy and improve the operating efficiency of overall cloud computing system. For the shortcomings of traditional particle swarm optimisation (PSO) algorithm in total completion time and average completion time, a quadratic particle swarm optimisation (QPSO) algorithm is proposed. Using the proposed algorithm, people can find a scheduling result with the short total completion time of task and also ensuring the short average completion time of task. Finally, the research made a simulation experiment with Cloud Sim. Experiment results show that in the same condition setting, the algorithm proposed is superior to the traditional PSO algorithm. When the number of tasks increases, the comprehensive scheduling performance of QPSO is more than 20% higher than that of PSO.

Keywords: Cloud computing; particle swarm optimisation (PSO); quadratic particle swarm optimisation (QPSO) (search for similar items in EconPapers)
Date: 2023
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DOI: 10.1142/S0219649222500678

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