A Survey of the Most Common Task Scheduling Algorithms

Cloud computing (CC) has changed the way organizations manage and access computing resources. CC allows businesses to scale up or down their computing needs on demand, without the need to invest in expensive hardware and infrastructure. Task scheduling in the Cloud environment is considered one of t...

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Bibliographic Details
Published in:	2023 International Telecommunications Conference (ITC-Egypt) pp. 126 - 133
Main Authors:	Abdelrehim, Menna Medhat, Hossny, Eman, Fatma Omara, H.
Format:	Conference Proceeding
Language:	English
Published:	IEEE 18-07-2023
Subjects:	Best-Fit Cloud computing Heuristic algorithms Make-span PSO Scheduling algorithms Sociology Surveys Tabu search Task analysis Task scheduling Telecommunications Worst-Fit
Online Access:	Get full text
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Summary:	Cloud computing (CC) has changed the way organizations manage and access computing resources. CC allows businesses to scale up or down their computing needs on demand, without the need to invest in expensive hardware and infrastructure. Task scheduling in the Cloud environment is considered one of the challenges that could affect the performance because the cloud provider provides services to many users with different demands. Most of the existing task scheduling algorithms are concerned with enhancing the performance of the task execution by using appropriate algorithms such as heuristic algorithms. These heuristic algorithms can be categorized into individual and hybrid algorithms examples of individual algorithms are: Particle Swarm optimization algorithm (PSO), Genetic Algorithm (GA), Ant Colony optimization (ACO), Cuckoo search (CS) algorithms, etc., and the hybrid algorithms are: BF-PSO-Tabu is a combination of a Particle Swarm optimization (PSO) algorithm, best-fit (BF), and Tabu algorithms, where the initial population of the PSO is defined using the best-fit algorithm instead of being defined randomly, and the Tabu algorithm is applied for tuning the final result. According to the work in this paper, a modification to the BF-PSO-Tabu (BSPSOTS) algorithm has been introduced, where the best-fit (BF) algorithm is replaced by the worst-fit (WF) algorithm to define the initial population (WFPSOTS). A comparative study has been done among some individual and hybrid algorithms. The comparative study results prove that the proposed hybrid algorithm (WFPSOTS) achieves better performance than the others with respect to Makespan, Resource utilization, and Load balancing.
DOI:	10.1109/ITC-Egypt58155.2023.10206179