Dynamic Round Robin with Adaptive Time Quanta (DRRATQ): A Proposed Algorithm

Abstract

The operating system (OS) acts as a resource manager whose responsibility is to manage the resources of a computer system. Among all resources, the CPU is one of the most crucial resources that manage the processes. Process management is achieved by a specific type of algorithm called CPU scheduling algorithm. CPU scheduling is a vital task of the OS and the whole performance of the system depends on the CPU scheduling criteria such as reducing waiting time, turnaround time, response time, and number of context switches, while enhancing the CPU utilization. Several well-known CPU scheduling algorithms like First Come-First-Served (FCFS), Shortest Job First (SJF), Shortest Remaining Time First (SRTF), Highest Response Ratio Next (HRRN), Round Robin (RR), and Priority Scheduling algorithms are coming into the picture. In time-shared environment, RR CPU scheduling is preferred, but the system's performance depends on choosing the most appropriate time quantum. By fusing the advantages of RR with features of SJF, this paper provides an intuitive approach to enhance the conventional RR CPU scheduling algorithm with adaptive time quanta that intends to improve system performance over the improver version like IRRVQ, MRR, Tajwar et al. and Fiad et al. The work offers experimental evidence that the proposed algorithm Dynamic Round Robin with Adaptive Time Quanta (DRRATQ) performs better than the conventional RR and other existing work, by decreasing the waiting time, turnaround time, response time, and number of context switches. Implementing this algorithm to a time-sharing or distributed environment will undoubtedly improve system performance and help avoid issues like thrashing, incorporate aging, CPU affinity, and starvation. Since the proposed scheduling is work-conserving in nature, it can be used for statistical multiplexing and best-effort packet switching in a network packet scheduling environment.