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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.
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.
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
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]
In computer science, priority inversion is a scenario in scheduling in which a high-priority task is indirectly superseded by a lower-priority task, effectively inverting the assigned priorities of the tasks. This violates the priority model that high-priority tasks can only be prevented from running by higher-priority tasks.
Deadline-monotonic priority assignment is a priority assignment policy used with fixed-priority pre-emptive scheduling. With deadline-monotonic priority assignment, tasks are assigned priorities according to their deadlines. The task with the shortest deadline is assigned the highest priority. [1]
This is a sub-category of Category:Scheduling algorithms, focusing on heuristic algorithms for scheduling tasks (jobs) to processors (machines). For optimization problems related to scheduling, see Category:Optimal scheduling.
An algorithm is fundamentally a set of rules or defined procedures that is typically designed and used to solve a specific problem or a broad set of problems.. Broadly, algorithms define process(es), sets of rules, or methodologies that are to be followed in calculations, data processing, data mining, pattern recognition, automated reasoning or other problem-solving operations.