Chronically Evaluated Highest Instantaneous Priority Next: A Novel Algorithm for Processor Scheduling

Pandey, Amit; Singh, Pawan Kumar; Gebreegziabher, Nirayo H.; Kemal, Abdella

doi:10.4236/jcc.2016.44013

Cited by 4 publications

(3 citation statements)

References 4 publications

(6 reference statements)

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“…Modifying the time slice at the beginning of each round is another dynamic version of SRR proposed by Lipika [24], in which the time slice is calculated with respect to the residual burst times (RBT) in the successive rounds. Lipika benefited from SJF in which the processes are ordered increasingly based on their burst times (i.e., the process with the highest burst time will be at the tail of the ready queue and the process with the lowest burst time will be at the head of the queue) [25][26][27]. Adaptive80 RR is a dynamic variant of SRR proposed by Christoph and Jeonghw [6].…”

Section: Related Workmentioning

confidence: 99%

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: Related Workmentioning

confidence: 99%

An Adjustable Variant of Round Robin Algorithm Based on Clustering Technique

Mostafa¹,

Amano²

2021

Computers, Materials &Amp; Continua

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“…The time slice is calculated depending on the remaining burst times in the subsequent rounds. In addition, the author also implemented SJF [35][36][37]. In SJF, the processes located in the ready queue are sorted in increasing order based on their burst times (i.e., the process having lowest burst time will be at the front of the ready queue and process having highest burst time will be at the end of the ready queue).…”

Section: Related Workmentioning

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 method calculates the time slice concerning the residual burst times (RBT) in the successive cycles. The shortest job first will benefit the processes which are sequenced increasingly based on their burst times (i.e., the process with the highest burst time will be at the tail of the ready queue, and the process with the lowest burst time will be at the head of the row) [25]. The present study used preemptive priority scheduling to provide service to emergency patients according to their priority and severity levels.…”

Section: Introductionmentioning

confidence: 99%

An Improved Queuing Model for Reducing Average Waiting Time of Emergency Surgical Patients Using Preemptive Priority Scheduling

2021

IJETER

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Our research objective is to reduce the Average Waiting Time for patients in an Emergency Department of public sector hospital. We have based our model on M/M/s Queuing System, our study revealssignificant findings on arrival rate of patients. During this simulation, we have used a preemptive priority scheduling model. In our practice, the arrival rate followed a Poisson distribution, averaging 30 patients per hour, with the Mean Service time of1.5 hours and Average Waiting Time recorded around 12.13 minutes. This research offersvaluable help to achieve better time management in emergency departments of high-density medical facilities.

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Chronically Evaluated Highest Instantaneous Priority Next: A Novel Algorithm for Processor Scheduling

Cited by 4 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

An Improved Queuing Model for Reducing Average Waiting Time of Emergency Surgical Patients Using Preemptive Priority Scheduling

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