Round-robin scheduling

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A Round Robin preemptive scheduling example with quantum=3 Round Robin Schedule Example.jpg
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). Round-robin scheduling is simple, easy to implement, and starvation-free. Round-robin scheduling can be applied to other scheduling problems, such as data packet scheduling in computer networks. It is an operating system concept.

Contents

The name of the algorithm comes from the round-robin principle known from other fields, where each person takes an equal share of something in turn.

Process scheduling

To schedule processes fairly, a round-robin scheduler generally employs time-sharing, giving each job a time slot or quantum [4] (its allowance of CPU time), and interrupting the job if it is not completed by then. The job is resumed next time a time slot is assigned to that process. If the process terminates or changes its state to waiting during its attributed time quantum, the scheduler selects the first process in the ready queue to execute. In the absence of time-sharing, or if the quanta were large relative to the sizes of the jobs, a process that produced large jobs would be favored over other processes.

Round-robin algorithm is a pre-emptive algorithm as the scheduler forces the process out of the CPU once the time quota expires.

For example, if the time slot is 100 milliseconds, and job1 takes a total time of 250 ms to complete, the round-robin scheduler will suspend the job after 100 ms and give other jobs their time on the CPU. Once the other jobs have had their equal share (100 ms each), job1 will get another allocation of CPU time and the cycle will repeat. This process continues until the job finishes and needs no more time on the CPU.

  1. First allocation = 100 ms.
  2. Second allocation = 100 ms.
  3. Third allocation = 100 ms but job1 self-terminates after 50 ms.
  4. Total CPU time of job1 = 250 ms

Consider the following table with the arrival time and execute time of the process with the quantum time of 100 ms to understand the round-robin scheduling:

Process nameArrival timeExecute time
P00250
P150170
P213075
P3190100
P4210130
P535050
Round Robin Scheduling RoundRobin.jpg
Round Robin Scheduling

Another approach is to divide all processes into an equal number of timing quanta such that the quantum size is proportional to the size of the process. Hence, all processes end at the same time.

Network packet scheduling

In best-effort packet switching and other statistical multiplexing, round-robin scheduling can be used as an alternative to first-come first-served queuing.

A multiplexer, switch, or router that provides round-robin scheduling has a separate queue for every data flow, where a data flow may be identified by its source and destination address. The algorithm allows every active data flow that has data packets in the queue to take turns in transferring packets on a shared channel in a periodically repeated order. The scheduling is work-conserving, meaning that if one flow is out of packets, the next data flow will take its place. Hence, the scheduling tries to prevent link resources from going unused.

Round-robin scheduling results in max-min fairness if the data packets are equally sized, since the data flow that has waited the longest time is given scheduling priority. It may not be desirable if the size of the data packets varies widely from one job to another. A user that produces large packets would be favored over other users. In that case fair queuing would be preferable.

If guaranteed or differentiated quality of service is offered, and not only best-effort communication, deficit round-robin (DRR) scheduling, weighted round-robin (WRR) scheduling, or weighted fair queuing (WFQ) may be considered.

In multiple-access networks, where several terminals are connected to a shared physical medium, round-robin scheduling may be provided by token passing channel access schemes such as Token Ring, or by polling or resource reservation from a central control station.

In a centralized wireless packet radio network, where many stations share one frequency channel, a scheduling algorithm in a central base station may reserve time slots for the mobile stations in a round-robin fashion and provide fairness. However, if link adaptation is used, it will take a much longer time to transmit a certain amount of data to "expensive" users than to others since the channel conditions differ. It would be more efficient to wait with the transmission until the channel conditions are improved, or at least to give scheduling priority to less expensive users. Round-robin scheduling does not utilize this. Higher throughput and system spectrum efficiency may be achieved by channel-dependent scheduling, for example a proportionally fair algorithm, or maximum throughput scheduling. Note that the latter is characterized by undesirable scheduling starvation. This type of scheduling is one of the very basic algorithms for Operating Systems in computers which can be implemented through a circular queue data structure.

See also

Related Research Articles

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In computing, scheduling is the action of assigning resources to perform tasks. The resources may be processors, network links or expansion cards. The tasks may be threads, processes or data flows.

Fair-share scheduling is a scheduling algorithm for computer operating systems in which the CPU usage is equally distributed among system users or groups, as opposed to equal distribution of resources among processes.

Weighted round robin (WRR) is a network scheduler for data flows, but also used to schedule processes.

Deficit Round Robin (DRR), also Deficit Weighted Round Robin (DWRR), is a scheduling algorithm for the network scheduler. DRR is, like weighted fair queuing (WFQ), a packet-based implementation of the ideal Generalized Processor Sharing (GPS) policy. It was proposed by M. Shreedhar and G. Varghese in 1995 as an efficient and fair algorithm.

In computer science, a multilevel feedback queue is a scheduling algorithm. Scheduling algorithms are designed to have some process running at all times to keep the central processing unit (CPU) busy. The multilevel feedback queue extends standard algorithms with the following design requirements:

  1. Separate processes into multiple ready queues based on their need for the processor.
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<span class="mw-page-title-main">Statistical time-division multiplexing</span>

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Generalized processor sharing (GPS) is an ideal scheduling algorithm for process schedulers and network schedulers. It is related to the fair-queuing principle which groups packets into classes and shares the service capacity between them. GPS shares this capacity according to some fixed weights.

In computer science, an input queue is a collection of processes in storage that are waiting to be brought into memory to run a program. Input queues are mainly used in Operating System Scheduling which is a technique for distributing resources among processes. Input queues not only apply to operating systems (OS), but may also be applied to scheduling inside networking devices. The purpose of scheduling is to ensure resources are being distributed fairly and effectively; therefore, it improves the performance of the system.

<span class="mw-page-title-main">Shortest job next</span> Scheduling policy

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Proportional-fair scheduling is a compromise-based scheduling algorithm. It is based upon maintaining a balance between two competing interests: Trying to maximize the total throughput of the network while at the same time allowing all users at least a minimal level of service. This is done by assigning each data flow a data rate or a scheduling priority that is inversely proportional to its anticipated resource consumption.

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<span class="mw-page-title-main">I/O scheduling</span> Arbiter for mass storage access in an operating system

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<span class="mw-page-title-main">Completely Fair Scheduler</span> Linux process scheduler

The Completely Fair Scheduler (CFS) was a process scheduler that was merged into the 2.6.23 release of the Linux kernel. It was the default scheduler of the tasks of the SCHED_NORMAL class and handled CPU resource allocation for executing processes, aiming to maximize overall CPU utilization while also maximizing interactive performance.

<span class="mw-page-title-main">Brain Fuck Scheduler</span> Process scheduler in Linux

The Brain Fuck Scheduler (BFS) is a process scheduler designed for the Linux kernel in August 2009 based on earliest eligible virtual deadline first scheduling (EEVDF), as an alternative to the Completely Fair Scheduler (CFS) and the O(1) scheduler. BFS was created by Con Kolivas.

References

  1. ↑ Arpaci-Dusseau, Remzi H.; Arpaci-Dusseau, Andrea C. (2014), Operating Systems: Three Easy Pieces [Chapter: Scheduling Introduction] (PDF), Arpaci-Dusseau Books
  2. ↑ Guowang Miao, Jens Zander, Ki Won Sung, and Ben Slimane, Fundamentals of Mobile Data Networks, Cambridge University Press, ISBN   1107143217, 2016.
  3. ↑ Stallings, William (2015). Operating Systems: Internals and Design Principles. Pearson. p. 409. ISBN   978-0-13-380591-8.
  4. ↑ Silberschatz, Abraham; Galvin, Peter B.; Gagne, Greg (2010). "Process Scheduling". Operating System Concepts (8th ed.). John Wiley & Sons (Asia). p. 194. ISBN   978-0-470-23399-3. 5.3.4 Round Robin Scheduling
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