An Adjustable Variant of Round Robin Algorithm Based on Clustering Technique

Mostafa, Samih M.; Amano, Hirofumi

doi:10.32604/cmc.2021.014675

Cited by 8 publications

(10 citation statements)

References 21 publications

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“…Samih et al proposed DRR (Dynamic Round Robin) which uses clustering technique in grouping similar processes in a cluster, it differs from its predecessors in that it allocates time for the cluster and all processes get the same time within the same cluster [7]. Mostafa et al [24] proposed DTS (Dynamic Time Slice), DTS takes the same approach as DRR in clustering the processes using K-means clustering technique, the only difference between them is the method of calculating the time slice. The process features PW, PTQ, PBT, and NCS basically depend on BT.…”

Section: Silhouette Methodsmentioning

confidence: 99%

“…The proposed algorithm behaved similar to the DTS algorithm [24] which takes into consideration not only the burst time of the process in the current round, but also the in the successive rounds. In addition, the proposed algorithm splits the queue into Q1 for short processes (shorter than median) and Q2 for long processes (longer than median) [20].…”

Section: Dynamic Implementationmentioning

confidence: 99%

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

Mostafa¹,

Idris²,

Kaur³

2022

Computers, Materials &Amp; Continua

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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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Section: Silhouette Methodsmentioning

confidence: 99%

Section: Dynamic Implementationmentioning

confidence: 99%

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

Mostafa¹,

Idris²,

Kaur³

2022

Computers, Materials &Amp; Continua

Self Cite

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“…Mostafa also proposed the Adjustable Round Robin (ARR) method, in which the short process has the opportunity to complete without pausing [9] . Dynamic Time Slice (DTS) algorithm uses K-means clustering technology to cluster processes [10] . Unferth et al [11] Modified Dynamic Round Robin (ADRR) is proposed to allocate time slices to processes according to the burst time.…”

Section: Introductionmentioning

confidence: 99%

An adjustable time slice process scheduling algorithm based on feature similarity clustering

Gong,

Ding

2023

Fourth International Conference on Artificial Intelligence and Electromechanical Automation (AIEA 2023)

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In order to improve the efficiency of the operating system scheduler, this paper proposes an adjustable time slice process scheduling algorithm ATSPS (Adjustable Time Slice Process Scheduling) based on feature similarity clustering, which can reduce the cost of the operating system process scheduling time, reduce the process turnaround time, and improve the process execution efficiency. ATSPS forms different process clusters by clustering the characteristics of process burst time, time slice, weight, and context switching times. It uses the same specification time slice for each type of process cluster. Through queue scheduling adjustment, it accelerates the execution efficiency of computationally intensive processes, reduces the number of contexts switching times caused by the expiration of time slice, and saves scheduling time. The scheduling process of robot grabbing program in the operating system is simulated by MATLAB, and the ready queue, blocking queue and execution queue of the operating system are simulated. The robot grabbing program is simulated, including visual process, force control process and posture process. ATSPS is compared with five classical scheduling algorithms. The experimental results show that on the scheduling criteria of three CPU scheduling algorithms, namely, waiting time, turnaround time and context switching times, ATSPS algorithm reduces the time cost of process scheduling, realizes the real-time scheduling of operating system process, and provides guarantee for the realtime control of robot.

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“…However, different approaches reveal distinct limitations [12]. When the time slice is too large, the processes in the ready queue become starved [13]. In the other side, the context switching time is high when TQ is small.…”

Section: Introductionmentioning

confidence: 99%

A New Round Robin Algorithm for Task Scheduling in Real-time System

2022

IJIES

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The modern human life is strongly reliant on real-time systems. The operating system is one of the most significant real-time systems. To meet the demands of the future, operating systems must be upgraded. Nowadays, a lot of systems are used; like mobile applications and internet of things. Task scheduling is so important in the operating system to enhance the performance in these systems. Round Robin algorithm has been widely used in task scheduling. In this paper, a Median Mean Round Robin (MMRR) algorithm is proposed to significantly enhance the performance of the Round Robin algorithm. The proposed algorithm finds an optimal dynamic time quantum └(median+ mean)/2)┘ and generated for each cluster depending on the remaining burst time of the processes. The performance has been enhanced in terms of waiting time, turnaround time and context switching. The experimental results show that the proposed algorithm outperforms ADRR, HYRR, EDRR and MARR algorithms.

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An Adjustable Variant of Round Robin Algorithm Based on Clustering Technique

Cited by 8 publications

References 21 publications

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

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

An adjustable time slice process scheduling algorithm based on feature similarity clustering

A New Round Robin Algorithm for Task Scheduling in Real-time System

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