Highest Response Ratio Next (HRRN) Scheduling Algorithm: Balancing Fairness and Efficiency
Learn about the Highest Response Ratio Next (HRRN) scheduling algorithm, a non-preemptive algorithm that prioritizes processes based on their response ratio, balancing fairness and minimizing average waiting time. This guide explains HRRN's calculation and its advantages over simpler scheduling algorithms.
Highest Response Ratio Next (HRRN) Scheduling Algorithm
Understanding HRRN Scheduling
The Highest Response Ratio Next (HRRN) algorithm is a non-preemptive scheduling algorithm that aims to provide a balance between minimizing average waiting time and ensuring fairness among processes. Unlike simpler algorithms like First-Come, First-Served (FCFS), HRRN considers both the waiting time and the service time (burst time) of each process when determining which process should run next. It is designed to improve fairness compared to simple algorithms that only prioritize shorter processes.
The Response Ratio
HRRN uses a metric called the response ratio to prioritize processes. The response ratio for a process is calculated as:
Response Ratio = (Waiting Time + Service Time) / Service Time
Where:
Waiting Time
: The time the process has spent waiting in the ready queue.Service Time
(or Burst Time): The time the process requires to complete its execution.
The process with the highest response ratio is selected to run next.
How HRRN Prioritizes Processes
The response ratio formula balances two factors:
- Waiting Time (W): Processes that have waited longer get a higher priority.
- Service Time (S): Shorter processes still have an advantage (larger 1/S).
This helps to prevent starvation (where some processes wait indefinitely), as longer waiting times increase the response ratio, giving longer jobs a better chance to run.
Non-Preemptive Nature
HRRN is a non-preemptive algorithm. Once a process begins execution, it continues until it completes or enters a waiting state. This minimizes the context-switching overhead associated with preemptive scheduling.