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Fair queuing is an example of a max-min fair packet scheduling algorithm for statistical multiplexing and best-effort networks, since it gives scheduling priority to users that have achieved lowest data rate since they became active. In case of equally sized data packets, round-robin scheduling is max-min fair.
On the other hand, if a new user starts a process on the system, the scheduler will reapportion the available CPU cycles such that each user gets 20% of the whole (100% / 5 = 20%). Another layer of abstraction allows us to partition users into groups, and apply the fair share algorithm to the groups as well.
A real-time scheduling algorithm can be classified as static or dynamic. For a static scheduler, task priorities are determined before the system runs. A dynamic scheduler determines task priorities as it runs. [4] Tasks are accepted by the hardware elements in a real-time scheduling system from the computing environment and processed in real-time.
Various scheduling policies can be used at queueing nodes: First in, first out First in first out (FIFO) queue example Also called first-come, first-served (FCFS), [21] this principle states that customers are served one at a time and that the customer that has been waiting the longest is served first. [22] Last in, first out
The scheduler is an operating system module that selects the next jobs to be admitted into the system and the next process to run. Operating systems may feature up to three distinct scheduler types: a long-term scheduler (also known as an admission scheduler or high-level scheduler), a mid-term or medium-term scheduler, and a short-term scheduler.
This scheduling algorithm first selects those processes that have the smallest "slack time". Slack time is defined as the temporal difference between the deadline, the ready time and the run time. More formally, the slack time s {\displaystyle s} for a process is defined as:
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Unrelated-machines scheduling is an optimization problem in computer science and operations research.It is a variant of optimal job scheduling.We need to schedule n jobs J 1, J 2, ..., J n on m different machines, such that a certain objective function is optimized (usually, the makespan should be minimized).