An Efficient Dynamic Round Robin algorithm for CPU scheduling

Farooq, Muhammad Umar; Shakoor, Aamna; Siddique, Abu Bakar

doi:10.1109/c-code.2017.7918936

Cited by 24 publications

(9 citation statements)

References 4 publications

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“…When all of the processes are completed, a quantum is given a new value equal to the highest BT, and the CPU is freed up for the remaining activities. This new technique worked wonderfully in terms of average waiting times, context switches, and turnaround times [18]. B. Dave et al recommended a unique method to CPU scheduling the strategy's objective is to compute the best quantum time depending on the left over burst time in ready queue for the said work.…”

Section: Literature Reviewmentioning

confidence: 99%

Predictive Scaling for Elastic Compute Resources on Public Cloud Utilizing Deep Learning based Long Short-term Memory

Bharanidharan¹,

Jayalakshmi²

2021

IJACSA

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Section: Literature Reviewmentioning

confidence: 99%

Predictive Scaling for Elastic Compute Resources on Public Cloud Utilizing Deep Learning based Long Short-term Memory

Bharanidharan¹,

Jayalakshmi²

2021

IJACSA

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“…CPU scheduling management techniques are intended to decide on short-term scheduling of all ready execution processes. CPU scheduling approaches are the core functions of a multi-programming OS which is tested to maximize CPU use [7] [8].…”

Section: Fig 1 Diagram Of Process Schedulersmentioning

confidence: 99%

CPU Scheduling Techniques: A Review on Novel Approaches Strategy and Performance Assessment

Harki¹,

Ahmed²,

Haji³

2020

JASTT

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The operating system (OS) is now being widely used in many of the various modern applications in recent years, ranging from diabetic monitoring to other strategic planning. The main function of any OS is to control and coordinate all hardware resources among the commands of the same/different user, which increases the efficiency of advanced comprehensive applications. In an autonomous computer system, the CPU is one of the important resources to manage and process all activities which require scheduling techniques on a processor. Since the early days of computing and other multi-programming OS, various studies have been assigned to CPU scheduling techniques based on processes management and performance evaluation. Thus, outlining the many issues related to scheduling methodologies and the weaknesses that need to be addressed. This review paper is organized based on two distinct perspectives: the implement strategies of CPU scheduling technique and criteria-based measures used, which assess how the strategies are analyzed and used under performance evaluation.

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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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An Efficient Dynamic Round Robin algorithm for CPU scheduling

Cited by 24 publications

References 4 publications

Predictive Scaling for Elastic Compute Resources on Public Cloud Utilizing Deep Learning based Long Short-term Memory

Predictive Scaling for Elastic Compute Resources on Public Cloud Utilizing Deep Learning based Long Short-term Memory

CPU Scheduling Techniques: A Review on Novel Approaches Strategy and Performance Assessment

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

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