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Dynamic priority scheduling is a type of scheduling algorithm in which the priorities are calculated during the execution of the system. The goal of dynamic priority scheduling is to adapt to dynamically changing progress and to form an optimal configuration in a self-sustained manner.
Fixed-priority preemptive scheduling is a scheduling system commonly used in real-time systems. [1] With fixed priority preemptive scheduling, the scheduler ensures that at any given time, the processor executes the highest priority task of all those tasks that are currently ready to execute.
Every priority level is represented by its own queue, with round-robin scheduling among the high-priority threads and FIFO among the lower-priority ones. In this sense, response time is short for most threads, and short but critical system threads get completed very quickly.
Earliest deadline first (EDF) or least time to go is a dynamic priority scheduling algorithm used in real-time operating systems to place processes in a priority queue. Whenever a scheduling event occurs (task finishes, new task released, etc.) the queue will be searched for the process closest to its deadline.
Least slack time (LST) scheduling is an algorithm for dynamic priority scheduling. It assigns priorities to processes based on their slack time. Slack time is the amount of time left after a job if the job was started now. This algorithm is also known as least laxity first.
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.
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