Abstract: Computer science employs process scheduling algorithms to efficiently arrange and prioritize operating system functions. These algorithms determine how processes admittance CPU, memory, and I/O units. Scheduling algorithms object to maximize throughput, guarantee fairness, and diminish reaction time to optimize system performance. Each scheduling scheme has advantages and drawbacks. To get the finest Round Robin (RR) quantum, we study statistical metrics like Arithmetic Mean, Range, Harmonic Mean, Median, Max value, Min value, Half, and Quarter. Statistical study can help us identify a Round Robin (RR) quantum that minimizes context changes and maximizes throughput. Since context switches burden the CPU, reducing them is crucial. We analyzed 10,000 processes for this. The Discovery of a better and more appropriate quantum for Round Robin (RR) scheduling was our goalmouth. Our research showed that the best outcomes were obtained when the median statistic was used. Our method beat the Arithmetic Mean and Max values with reasonable speed and less context switching. This upgraded quantum allows us to considerably increase the efficiency of the scheduling process.

Keywords: CPU Scheduling, Round Robin Scheduling Algorithm, Turnaround Time, Waiting Time, Context Switching, Statistics Measures

Pages: 450-461