A Review Paper on Progressive Approach to Reduce Context Switching in Round Robin Scheduling Algorithm

Abstract

Processes/tasks are scheduled in order to finish the task on time. CPU Scheduling is a technique that permits one process to utilize the CPU while other is delayed (on standby) due to a lack of resources such as I/O allowing the CPU to be fully utilized. The goal of CPU scheduling is to improve the system's efficiency, speed, and fairness. When the CPU is not being used, the operating system chooses one of the processes in the queue to start. A temporary CPU scheduler performs the selecting process. The scheduler chooses one of the memory processes that are ready to run and assigns CPU to it. Every system software must have scheduling, and practically, all virtual machines are scheduled over before use. To enhance CPU efficiency, CPU utilization, delay, and CPU cycles is the primary objective of all presently available CPU scheduling techniques. There are various ways to tackle this, for example, algorithms like FCFS, SJN, priority scheduling, and many more, but in this paper, we chose to work with Round Robin (RR) Scheduling algorithm. RR algorithm solves the stated challenges as it’s method's reasoning is significantly influenced by the length of the timeslot. In comparison, time slices should be huge than of the context switch time, as it enhances the performance by lowering the load on CPU. In this study, we review an existing technique to reduce context switching and break the fixed. With optimization, the range of the time quantum is utilized through the RR scheduling algorithm. This paper is researching mainly on the employment of context switching, and RR scheduling. Scheduling is discussing about how time slice of one process is completed, processor is allocated to next process, and saving of the state of process is needed because for the next time, it can run the process from the place it was halted. The review of this paper signifies the comparison of context switching based on different scheduling algorithm and the past work significance of study.