Optimal CPU Jobs Scheduling Method Based on Simulated Annealing Algorithm

Authors

DOI:

https://doi.org/10.24996/ijs.2022.63.8.38

Keywords:

Operation System, CPU Tasks Scheduling, Artificial Intelligent, Meta-Heuristic Techniques, Optimization Techniques

Abstract

     Task scheduling in an important element in a distributed system. It is vital how the jobs are correctly assigned for each computer’s processor to improve performance. The presented approaches attempt to reduce the expense of optimizing the use of the CPU. These techniques mostly lack planning and in need to be comprehensive. To address this fault, a hybrid optimization scheduling technique is proposed for the hybridization of both First-Come First-Served (FCFS), and Shortest Job First (SJF). In addition, we propose to apply Simulated Annealing (SA) algorithm as an optimization technique to find optimal job’s execution sequence considering both job’s entrance time and job’s execution time to balance them to reduce the job’s waiting time to be executed. As a result, this research proves that the proposed technique achieves an optimization efficiency with a percentage average 45.5 % according to the FCFS algorithm and 54.5% according to SJF method.

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Published

2022-08-31

How to Cite

Abdul Kareem, E. . I. ., & Hussein, S. . A. . . (2022). Optimal CPU Jobs Scheduling Method Based on Simulated Annealing Algorithm. Iraqi Journal of Science, 63(8), 3640–3651. https://doi.org/10.24996/ijs.2022.63.8.38

Issue

Section

Computer Science