Priority based round robin (PBRR) CPU scheduling algorithm

Zouaoui, Sonia; Boussaid, Lotfi; mtibaa, abdellatif

doi:10.11591/ijece.v9i1.pp190-202

Cited by 26 publications

(16 citation statements)

References 12 publications

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“…The proposed work can provide a solution to handle this critical situation. This work mainly focuses on fuzzy rulebased approach [49][50][51][52][53] that uses priority-based method [54,55] to manage and assign the hospital beds for the treatment of COVID-19 infected patients. The proposed approach is compared with the FCFS-based [56,57] approach to analyze the practical scenario during the assignment of hospital beds.…”

Section: Proposed Methodologymentioning

confidence: 99%

A fuzzy rule-based efficient hospital bed management approach for coronavirus disease-19 infected patients

Jena

Bhoi

Prasad

et al. 2021

Neural Comput & Applic

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) is a very dangerous infectious disease for the entire world in the current scenario. Coronavirus spreads from one person to another person very rapidly. It spreads exponentially throughout the globe. Everyone should be cautious to avoid the spreading of this novel disease. In this paper, a fuzzy rule-based approach using priority-based method is proposed for the management of hospital beds for COVID-19 infected patients in the worst-case scenario where the number of hospital beds is very less as compared to the number of COVID-19 infected patients. This approach mainly attempts to minimize the number of hospital beds as well as emergency beds requirement for the treatment of COVID-19 infected patients to handle such a critical situation. In this work, higher priority has given to severe COVID-19 infected patients as compared to mild COVID-19 infected patients to handle this critical situation so that the survival probability of the COVID-19 infected patients can be increased. The proposed method is compared with first-come first-serve (FCFS)-based method to analyze the practical problems that arise during the assignment of hospital beds and emergency beds for the treatment of COVID-19 patients. The simulation of this work is carried out using MATLAB R2015b.

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Section: Proposed Methodologymentioning

confidence: 99%

A fuzzy rule-based efficient hospital bed management approach for coronavirus disease-19 infected patients

Jena

Bhoi

Prasad

et al. 2021

Neural Comput & Applic

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“…It means that GPOSs must support multi-tasking [8], [14]. On the other hand, task scheduling and allocation are performed without priority levels of the tasks in GPOSs [15]. It is possible to execute lower priority tasks  ISSN: 2088-8708 Int J Elec & Comp Eng, Vol.…”

Section: Introductionmentioning

confidence: 99%

Performance analysis of real-time and general-purpose operating systems for path planning of the multi-robot systems

Canbaz

Erdemir²

2022

IJECE

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In general, modern operating systems can be divided into two essential parts, real-time operating systems (RTOS) and general-purpose operating systems (GPOS). The main difference between GPOS and RTOS is the system istime-critical or not. It means that; in GPOS, a high-priority thread cannot preempt a kernel call. But, in RTOS, a low-priority task is preempted by a high-priority task if necessary, even if it’s executing a kernel call. Most Linux distributions can be used as both GPOS and RTOS with kernel modifications. In this study, two Linux distributions, Ubuntu and Pardus, were analyzed and their performances were compared both as GPOS and RTOS for path planning of the multi-robot systems. Robot groups with different numbers of members were used to perform the path tracking tasks using both Ubuntu and Pardus as GPOS and RTOS. In this way, both the performance of two different Linux distributions in robotic applications were observed and compared in two forms, GPOS, and RTOS.

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“…Processes in the computer system have dissimilar forms for example "dis-joint process, co-operating process, and interacting processes". Figure 1 presents the process lifecycle [4].…”

Section: Introductionmentioning

confidence: 99%

“…Figure 1. Process lifecycle [4] The long term determines which tasks or processes are to be accepted to get the ready queue so when establishing an attempt for process execution, its admission to the band of executing processes currently which is either authorized or stayed (delay) through the long-term scheduler. Hence, this scheduler orders which processes are to run on a system and the concurrency level should be backed at any time.…”

Section: Introductionmentioning

confidence: 99%

Comparative analysis of the essential CPU scheduling algorithms

2021

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CPU scheduling algorithms have a significant function in multiprogramming operating systems. When the CPU scheduling is effective a high rate of computation could be done correctly and also the system will maintain in a stable state. As well as, CPU scheduling algorithms are the main service in the operating systems that fulfill the maximum utilization of the CPU. This paper aims to compare the characteristics of the CPU scheduling algorithms towards which one is the best algorithm for gaining a higher CPU utilization. The comparison has been done between ten scheduling algorithms with presenting different parameters, such as performance, algorithm’s complexity, algorithm’s problem, average waiting times, algorithm’s advantages-disadvantages, allocation way, etc. The main purpose of the article is to analyze the CPU scheduler in such a way that suits the scheduling goals. However, knowing the algorithm type which is most suitable for a particular situation by showing its full properties.

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Priority based round robin (PBRR) CPU scheduling algorithm

Cited by 26 publications

References 12 publications

A fuzzy rule-based efficient hospital bed management approach for coronavirus disease-19 infected patients

A fuzzy rule-based efficient hospital bed management approach for coronavirus disease-19 infected patients

Performance analysis of real-time and general-purpose operating systems for path planning of the multi-robot systems

Comparative analysis of the essential CPU scheduling algorithms

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