ATS: A Novel Time-Sharing CPU Scheduling Algorithm Based on Features Similarities

Minimizing time cost in time-shared operating systems is considered basic and essential task, and it is the most significant goal for the researchers who interested in CPU scheduling algorithms. Waiting time, turnaround time, and number of context switches are the most time cost criteria used to com...

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Vydané v:Computers, materials & continua Ročník 70; číslo 3; s. 6271 - 6288
Hlavní autori: M. Mostafa, Samih, Ahmed Idris, Sahar, Kaur, Manjit
Médium: Journal Article
Jazyk:English
Vydavateľské údaje: Henderson Tech Science Press 2022
Predmet:
Algorithms
Context
Datasets
Preempting
Scheduling
Similarity
Switches
Time sharing
ISSN:1546-2226, 1546-2218, 1546-2226
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Shrnutí:Minimizing time cost in time-shared operating systems is considered basic and essential task, and it is the most significant goal for the researchers who interested in CPU scheduling algorithms. Waiting time, turnaround time, and number of context switches are the most time cost criteria used to compare between CPU scheduling algorithms. CPU scheduling algorithms are divided into non-preemptive and preemptive. Round Robin (RR) algorithm is the most famous as it is the basis for all the algorithms used in time-sharing. In this paper, the authors proposed a novel CPU scheduling algorithm based on RR. The proposed algorithm is called Adjustable Time Slice (ATS). It reduces the time cost by taking the advantage of the low overhead of RR algorithm. In addition, ATS favors short processes allowing them to run longer time than given to long processes. The specific characteristics of each process are; its CPU execution time, weight, time slice, and number of context switches. ATS clusters the processes in groups depending on these characteristics. The traditional RR assigns fixed time slice for each process. On the other hand, dynamic variants of RR assign time slice for each process differs from other processes. The essential difference between ATS and the other methods is that it gives a set of processes a specific time based on their similarities within the same cluster. The authors compared between ATS with five popular scheduling algorithms on nine datasets of processes. The datasets used in the comparison vary in their features. The evaluation was measured in term of time cost and the experiments showed that the proposed algorithm reduces the time cost.
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ISSN:1546-2226
1546-2218
1546-2226
DOI:10.32604/cmc.2022.021978