Performance Evaluation of Dynamic Round Robin Algorithms for CPU Scheduling

Alsulami, Abdulaziz A.; Al‐Haija, Qasem Abu; Thanoon, Mohammed I.; Mao, Qian

doi:10.1109/southeastcon42311.2019.9020439

Cited by 14 publications

(5 citation statements)

References 4 publications

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“…The most common of the preemptive scheduling algorithms is the RR scheduling [5], known hereafter as Standard RR (SRR), used in timesharing and real-time operating systems [6]. In RR scheduling, the operating system is driven by a regular interrupt by the system timer after a short fixed interval called standard time slice (STS) [7][8][9][10]. After that interruption, the scheduler switches the context to the next process selected from the circular queue [11,12].…”

Section: Cpu Schedulingmentioning

confidence: 99%

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An Adjustable Variant of Round Robin Algorithm Based on Clustering Technique

Mostafa¹,

Amano²

2021

Computers, Materials &Amp; Continua

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CPU scheduling is the basic task within any time-shared operating system. One of the main goals of the researchers interested in CPU scheduling is minimizing time cost. Comparing between CPU scheduling algorithms is subject to some scheduling criteria (e.g., turnaround time, waiting time and number of context switches (NCS)). Scheduling policy is divided into preemptive and non-preemptive. Round Robin (RR) algorithm is the most common preemptive scheduling algorithm used in the time-shared operating systems. In this paper, the authors proposed a modified version of the RR algorithm, called dynamic time slice (DTS), to combine the advantageous of the low scheduling overhead of the RR and favor short process for the sake of minimizing time cost. Each process has a weight proportional to the weights of all processes. The process's weight determines its time slice within the current period. The authors benefit from the clustering technique in grouping the processes that are similar in their attributes (e.g., CPU service time, weight, allowed time slice (ATS), proportional burst time (PBT) and NCS). Each process in a cluster is assigned the average of the processes' time slices in this cluster. A comparative study of six popular scheduling algorithms and the proposed approach on nine groups of processes vary in their attributes was performed and the evaluation was measured in terms of waiting and turnaround times, and NCS. The experiments showed that the proposed algorithm gives better results.

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Section: Cpu Schedulingmentioning

confidence: 99%

“…In addition, the proposed algorithm gives a process more time in the current and successive rounds according to the condition in Eq. (10). The comparison was done between the proposed algorithm and six common algorithms from the point of view of waiting time, turnaround time, and NCS.…”

Section: Performance Evaluationmentioning

confidence: 99%

An Adjustable Variant of Round Robin Algorithm Based on Clustering Technique

Mostafa¹,

Amano²

2021

Computers, Materials &Amp; Continua

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“…Processes are selected in a fixed sequence for execution [8]. A process receiving CPU service is interrupted by the system timer after a short fixed interval called time slice which usually is much shorter than the CPU service period (or CPU burst) of the process [9][10][11]. After that interruption, the scheduler performs a context switch to the next process selected from the ready queue which is treated as a circular queue [12,13].…”

Section: Cpu Schedulingmentioning

confidence: 99%

Dynamic Round Robin CPU Scheduling Algorithm Based on K-Means Clustering Technique

Mostafa

Amano

2020

Applied Sciences

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Minimizing time cost in time-shared operating system is the main aim of the researchers interested in CPU scheduling. CPU scheduling is the basic job within any operating system. Scheduling criteria (e.g., waiting time, turnaround time and number of context switches (NCS)) are used to compare CPU scheduling algorithms. Round robin (RR) is the most common preemptive scheduling policy used in time-shared operating systems. In this paper, a modified version of the RR algorithm is introduced to combine the advantageous of favor short process and low scheduling overhead of RR for the sake of minimizing average waiting time, turnaround time and NCS. The proposed work starts by clustering the processes into clusters where each cluster contains processes that are similar in attributes (e.g., CPU service period, weights and number of allocations to CPU). Every process in a cluster is assigned the same time slice depending on the weight of its cluster and its CPU service period. The authors performed comparative study of the proposed approach and popular scheduling algorithms on nine groups of processes vary in their attributes. The evaluation was measured in terms of waiting time, turnaround time, and NCS. The experiments showed that the proposed approach gives better results.

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“…This study compares four RR algorithms: Adaptive RR algorithm, best time quantum RR CPU scheduling, optimal RR scheduling using the Manhattan distance algorithm, and improved RR scheduling algorithm. Four performance indicators were used to compare these algorithms: the amount of context switching (NCS), average waiting time (AWT), average turnaround time (ATT), and average response time (ART) [23]. The simulation results show that both the adaptive RR and optimal RR scheduling using Manhattan distance algorithms are more effective to use because they report the lowest performance factor values [23].…”

Section: Introductionmentioning

confidence: 99%

“…Four performance indicators were used to compare these algorithms: the amount of context switching (NCS), average waiting time (AWT), average turnaround time (ATT), and average response time (ART) [23]. The simulation results show that both the adaptive RR and optimal RR scheduling using Manhattan distance algorithms are more effective to use because they report the lowest performance factor values [23].…”

Section: Introductionmentioning

confidence: 99%

Cloud service analysis using round-robin algorithm for quality-of-service aware task placement for internet of things services

Pakhrudin

Kassim

Idris

2023

IJECE

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Round-robin (RR) is a process approach to sharing resources that requires each user to get a turn using them in an agreed order in cloud computing. It is suited for time-sharing systems since it automatically reduces the problem of priority inversion, which are low-priority tasks delayed. The time quantum is limited, and only a one-time quantum process is allowed in round-robin scheduling. The objective of this research is to improve the functionality of the current RR method for scheduling actions in the cloud by lowering the average waiting, turnaround, and response time. CloudAnalyst tool was used to enhance the RR technique by changing the parameter value in optimizing the high accuracy and low cost. The result presents the achieved overall min and max response times are 36.69 and 650.30 ms for running 300 min RR. The cost for the virtual machines (VMs) is identified from $0.5 to $3. The longer the time used, the higher the cost of the data transfer. This research is significant in improving communication and the quality of relationships within groups.

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Performance Evaluation of Dynamic Round Robin Algorithms for CPU Scheduling

Cited by 14 publications

References 4 publications

An Adjustable Variant of Round Robin Algorithm Based on Clustering Technique

An Adjustable Variant of Round Robin Algorithm Based on Clustering Technique

Dynamic Round Robin CPU Scheduling Algorithm Based on K-Means Clustering Technique

Cloud service analysis using round-robin algorithm for quality-of-service aware task placement for internet of things services

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