A Survey of Variants of Round Robin Cpu Scheduling Algorithms

Abstract

Quite a number of scheduling algorithms have been implemented in the past, including First Come First Served (FCFS), Shortest Job First (SJF), Priority and Round Robin (RR). However, RR seems better than others because of its impartiality during the usage of its quantum time. Despite this, there is a big challenge with respect to the quantum time to use. This is because when the quantum time is too large, it leads to FCFS, and if the quantum time is too short, it increases the number of switches from the processes. As a result of this, this paper provides a descriptive review of various algorithms that have been implemented in the past 10 years, for various quantum time in order to optimize the performance of CPU utilization. This attempt will open more research areas for researchers, serve as a reference source and articulate various algorithms that have been used in the previous years – and as such, the paper will serve as a guide for future work. This research work further suggests novel hybridization and ensemble of two or more techniques so as to improve CPU performance by decreasing the number of context switch, turnaround time, waiting time and response time and in overall increasing the throughput and CPU utilization.

Optimizing Task Execution: The Impact of Dynamic Time Quantum and Priorities on Round Robin Scheduling

“…Moreover, the RR algorithm and its variants are comprehensively reviewed in [13][14][15][16]. The authors in [17] designed an MMRR (Median Mean Round Robin) method for process scheduling.…”

“…One of the critical aspects of scheduling is the ability to measure the algorithm's performance. This section will discuss three standard performance measures used in scheduling: turnaround time, waiting time, and context switching [10,15].…”

RRDTool: A Round Robin Database for Network Monitoring

“…Data does not arrive exactly in that interval. It takes the actual arrival time under the curve and creates new points in time between these time intervals and makes a curve beneath the real curve (Omotehinwa et al, 2019;Olofintuyi et al, 2019;Rad et al, 2017;Zaidi and Shukla, 2018). Thus traffic latency will be the same but the numbers shown may differ.…”

Examining the developments in scheduling algorithms research: A bibliometric approach

“…They have largely taken a narrow path that either focus on specific topics or area of applications of scheduling algorithms. These studies ( Almansour and Allah, 2019 ; Arora and Banyal, 2022 ; Arunarani et al., 2019 ; Ghafari et al., 2022 ; Kumar et al., 2019 ; Sana and Li, 2021 ) focused on the extensive review of scheduling techniques in cloud computing ( Agrawal et al., 2021 ; Davis and Burns, 2011 ; Olofintuyi et al., 2020 ), focused on the review of operating system scheduling algorithms while other studies such as ( Maipan-Uku et al., 2017 ; Prajapati and Shah, 2014 ; Yousif et al., 2015 ) focused on scheduling in grid computing. A general overview of scheduling algorithms is necessary at this time to understand the trends over time and to discover a new research focus.…”