The performance of Round Robin algorithm depends heavily ona)size of t...
In round robin algorithm, the size of time quanta plays a very important role as: If size of quanta is too small: Context switches will increase and it is counted as the waste time, so CPU utilization will decrease. If size of quanta is too large: Larger time quanta will lead to Round robin regenerated into FCFS scheduling algorithm. So, option (D) is correct.
The performance of Round Robin algorithm depends heavily ona)size of t...
Introduction:
The Round Robin algorithm is a widely used CPU scheduling algorithm in operating systems. It is a preemptive algorithm that assigns a fixed time quantum to each process in a circular manner. When a process's time quantum expires, it is preempted and moved to the back of the ready queue.
Explanation:
The performance of the Round Robin algorithm depends heavily on the size of the time quantum. Let's understand why:
1. Fairness and Responsiveness:
The Round Robin algorithm aims to provide fairness and responsiveness to all processes. By assigning a fixed time quantum to each process, it ensures that no single process monopolizes the CPU for an extended period. This prevents any process from becoming starved and provides equal opportunities to all processes.
2. Context Switching Overhead:
Context switching is the process of saving and restoring the state of a process so that it can be resumed later. In Round Robin, context switching occurs whenever a process's time quantum expires. The smaller the time quantum, the more frequently context switches occur, leading to higher overhead due to the additional time required to save and restore the process state.
3. Throughput and Turnaround Time:
The time quantum affects the throughput and turnaround time of processes. A smaller time quantum allows for more frequent context switches and better response time, but it also increases the overhead due to context switching. On the other hand, a larger time quantum reduces the frequency of context switches but may lead to longer response times for interactive processes.
4. Overhead and Efficiency:
A smaller time quantum reduces the overhead due to context switching but may result in a higher number of context switches. This can lead to decreased overall efficiency as more time is spent on context switching rather than executing the actual processes. Conversely, a larger time quantum reduces the number of context switches but can result in lower responsiveness for processes.
Conclusion:
In conclusion, the performance of the Round Robin algorithm is heavily dependent on the size of the time quantum. It is crucial to strike a balance between fairness, responsiveness, overhead, throughput, and turnaround time when choosing an appropriate time quantum for a given system.