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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).
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.
Weighted round robin (WRR) is a network scheduler for data flows, but also used to schedule processes. Weighted round robin [ 1 ] is a generalisation of round-robin scheduling . It serves a set of queues or tasks.
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 uses one queue per packet flow and services them in rotation, such that each flow can "obtain an equal fraction of the resources". [1] [2]The advantage over conventional first in first out (FIFO) or priority queuing is that a high-data-rate flow, consisting of large packets or many data packets, cannot take more than its fair share of the link capacity.
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.
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.