MMMRR: a Modified Median Mean Round Robin Algorithm for Task Scheduling

Abstract

Real-time task scheduling is a critical part of systems since processes must finish their work at a certain time. Large data streams require high energy efficiency and rapid response times. Real-time system performance must be improved through task scheduling on resources. Numerous researchers have recently and rapidly proposed enormous efforts with enhancements in numerous task scheduling methods. Round Robin algorithm has been commonly utilized in task scheduling. In this paper, a Modified Median Mean Round Robin (MMMRR) algorithm is proposed to significantly enhance the performance of the Round Robin algorithm. The proposed algorithm finds an ideal dynamic time quantum └(median+ mean)/2)┘ and generated for each round depending on the remaining burst time of the processes. The system performance has been enhanced in terms of waiting time, turnaround time and context switching. The experimental results show that the proposed algorithm outperforms ADRR, HYRR, EDRR, MARR and MMRR algorithms.