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A Round Robin preemptive scheduling example with quantum=3. Round-robin (RR) is one of the algorithms employed by process and network schedulers in computing. [1] [2] As the term is generally used, time slices (also known as time quanta) [3] are assigned to each process in equal portions and in circular order, handling all processes without priority (also known as cyclic executive).
One common method of logically implementing the fair-share scheduling strategy is to recursively apply the round-robin scheduling strategy at each level of abstraction (processes, users, groups, etc.) The time quantum required by round-robin is arbitrary, as any equal division of time will produce the same results.
It is a mathematical model that contains a calculated simulation of periods in a closed system, where round-robin and time-sharing schedulers fail to meet the scheduling needs otherwise. Rate monotonic scheduling looks at a run modeling of all threads in the system and determines how much time is needed to meet the guarantees for the set of ...
For example, Windows NT/XP/Vista uses a multilevel feedback queue, a combination of fixed-priority preemptive scheduling, round-robin, and first in, first out algorithms. In this system, threads can dynamically increase or decrease in priority depending on if it has been serviced already, or if it has been waiting extensively.
Round-robin scheduling method will give a same amount of time for each process and cycle through them. This method is heavily bases on a lot of time consuming to each process. Too short a lot time will fragment the processes, and too long a lot time will increase waiting time for each process to be executed.
The proportional fair (= and =) scheduler could be called "equal effort scheduler" or "time/spectrum Round Robin scheduler". This technique can be further parametrized by using a "memory constant" that determines the period of time over which the station data rate used in calculating the priority function is averaged.
In weighted round robin scheduling, the fraction of bandwidth used depend on the packet's sizes. Compared with WFQ scheduler that has complexity of O(log(n)) ( n is the number of active flows/queues ), the complexity of DRR is O(1) , if the quantum Q i {\displaystyle Q_{i}} is larger than the maximum packet size of this flow.
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.