Improving Round Robin Scheduling with Dynamic Time Quantum (IRRDQ)

Abstract

In the realm of real-time and multitasking environments, the Round Robin (RR) CPU scheduling algorithm is extensively utilized. Renowned for its fairness and avoidance of process starvation, RR allocates a specific time quantum to each process. However, the frequent context switching between processes during CPU scheduling, owing to the short time quantum, can adversely impact system performance by increasing average waiting time and response waiting time. To address these concerns, this paper introduces "Improving Round Robin Scheduling Using Dynamic Time Quantum (IRRDQ)," a modified version of RR aimed at diminishing turnaround time, average waiting time, and context switching. In our proposed approach, we arrange all incoming processes based on minimum burst time and dynamically assign an optimal time quantum to each process using the Shortest Job First (SJF) algorithm. The computation of time quantum is tailored to the burst times of individual processes. Through experimental demonstrations, we showcase the significant performance improvement of our algorithm compared to RR and other existing algorithms.