An adjustable variant of round robin algorithm based on clustering technique

Samih M. Mostafa, Hirofumi Amano

    Research output: Contribution to journalArticlepeer-review

    Abstract

    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.

    Original languageEnglish
    Pages (from-to)3253-3270
    Number of pages18
    JournalComputers, Materials and Continua
    Volume66
    Issue number3
    DOIs
    Publication statusPublished - 2020

    All Science Journal Classification (ASJC) codes

    • Biomaterials
    • Modelling and Simulation
    • Mechanics of Materials
    • Computer Science Applications
    • Electrical and Electronic Engineering

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