A Hybrid Gravitational Emulation Local Search-Based Algorithm for Task Scheduling in Cloud Computing. (4th February 2023)

• Record Type: Journal Article
• Authors: Praveen, S. Phani; Ghasempoor, Hesam; Shahabi, Negar; Izanloo, Fatemeh
• Other Names: Mohammadzadeh Ardashir Academic Editor.
• Is Part Of: Mathematical problems in engineering. Volume 2023(2023)
• Publication Date: 2023-02-04
• Subjects: Engineering mathematics -- Periodicals; 510.2462
• DOI: 10.1155/2023/6516482
• Languages: English
• ISSNs: 1024-123X

Abstract

Abstract : The flexibility of cloud computing to provide a dynamic and adaptable infrastructure in the context of information technology and service quality has made it one of the most challenging issues in the computer industry. Task scheduling is a major challenge in cloud computing. Scheduling tasks so that they may be processed by the most effective cloud network resources has been identified as a critical challenge for maximizing cloud computing's performance. Due to the complexity of the issue and the size of the search space, random search techniques are often used to find a solution. Several algorithms have been offered as possible solutions to this issue. In this study, we employ a combination of the genetic algorithm (GA) and the gravitational emulation local search (GELS) algorithm to overcome the task scheduling issue in cloud computing. GA and the particle swarm optimization (PSO) algorithms are compared to the suggested algorithm to demonstrate its efficacy. The suggested algorithm outperforms the GA and PSO, as shown by the experiments.