Modified Particle Swarm Optimization Based on Aging Leaders and Challengers Model for Task Scheduling in Cloud Computing

Shikha Chaudhary, Vijay Kumar Sharma, R. N. Thakur, Amit Rathi, Pramendra Kumar, Sachin Sharma and SeyedSaeid Mirkamali

Mathematical Problems in Engineering, 2023, vol. 2023, 1-11

Abstract: In cloud computing, a shared, configurable pool of computing resources is made accessible online and allocated to users according to their needs. It is essential for a cloud provider to schedule jobs in the cloud to keep up service quality and boost system efficiency. In this paper, we present a scheduling technique based on modified particle swarm optimization to combat the issues of excessively long scheduling time and high computation costs associated with scheduling jobs in a cloud environment. The modified PSO is used to allocate the jobs to virtual machines in order to minimize the objective function consisting of cost and makespan. The algorithm relies on biological changes that occur in organisms to regulate premature convergence and improve local search capability. The technique is analyzed and simulated using CloudSim, and the simulation results demonstrate that the proposed approach decreases makespan and cost effectively as compared to standard PSO.

Date: 2023
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Persistent link: https://EconPapers.repec.org/RePEc:hin:jnlmpe:3916735

DOI: 10.1155/2023/3916735

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