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In computer science, rate-monotonic scheduling (RMS) [1] is a priority assignment algorithm used in real-time operating systems (RTOS) with a static-priority scheduling class. [2] The static priorities are assigned according to the cycle duration of the job, so a shorter cycle duration results in a higher job priority.
Some commonly used RTOS scheduling algorithms are: [5] Cooperative scheduling; Preemptive scheduling. Rate-monotonic scheduling; Round-robin scheduling; Fixed-priority pre-emptive scheduling, an implementation of preemptive time slicing; Fixed-Priority Scheduling with Deferred Preemption; Fixed-Priority Non-preemptive Scheduling
Instead, most real-time computer systems use fixed-priority scheduling (usually rate-monotonic scheduling). With fixed priorities, it is easy to predict that overload conditions will cause the low-priority processes to miss deadlines, while the highest-priority process will still meet its deadline.
Higher schedulable utilization means higher utilization of resource and the better the algorithm. In preemptible scheduling, dynamic priority scheduling such as earliest deadline first (EDF) provides the optimal schedulable utilization of 1 in contrast to less than 0.69 with fixed priority scheduling such as rate-monotonic (RM). [1]
Tasks with the highest rate of execution are given the highest priority using rate-monotonic scheduling. [14] This scheduling algorithm is used in real-time operating systems (RTOS) with a static-priority scheduling class .
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It uses notions of virtual time, eligible time, virtual requests and virtual deadlines for determining scheduling priority. [1] It has the property that when a job keeps requesting service, the amount of service obtained is always within the maximum quantum size of what it is entitled.
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