Deficit Round Robin (DRR), alsoDeficit Weighted Round Robin (DWRR), is a scheduling algorithm for thenetwork scheduler. DRR is, similar toweighted fair queuing (WFQ), a packet-based implementation of the idealGeneralized Processor Sharing (GPS) policy. It was proposed by M. Shreedhar andG. Varghese in 1995 as an efficient (withO(1) complexity) and fair algorithm.^[1]

In DRR, a scheduler handling N flows^[a] is configured with one quantum${\displaystyle Q_i}$ for each flow. This global idea is that, at each round, the flow${\displaystyle i}$ can send at most${\displaystyle Q_i}$ bytes, and the remaining, if any, is reported to the next round. In this way, the minimum rate that flow${\displaystyle i}$ will achieve over a long term is${\displaystyle \frac{Q_i}{(Q_1+Q_2+...+Q_N)}R}$; where${\displaystyle R}$ is the link rate.

The DRR scans all non-empty queues in sequence. When a non-empty queue${\displaystyle i}$ is selected, its deficit counter is incremented by its quantum value. Then, the value of the deficit counter is a maximal number of bytes that can be sent at this turn: if the deficit counter is greater than the packet's size at the head of the queue (HoQ), this packet can be sent, and the value of the counter is decremented by the packet size. Then, the size of the next packet is compared to the counter value, etc. Once the queue is empty or the value of the counter is insufficient, the scheduler will skip to the next queue. If the queue is empty, the value of the deficit counter is reset to 0.

Variables and Constants    const integer N             // Nb of queues    const integer Q[1..N]       // Per queue quantum     integer DC[1..N]            // Per queue deficit counter    queue queue[1..N]           // The queues

Scheduling Loopwhile truedofor i in 1..Ndoif not queue[i].empty()then            DC[i]:= DC[i] + Q[i]while( not queue[i].empty()and                         DC[i] ≥ queue[i].head().size() )do                DC[i] := DC[i] − queue[i].head().size()                send( queue[i].head() )                queue[i].dequeue()end whileif queue[i].empty()then                DC[i] := 0end ifend ifend forend while

Like other GPS-like scheduling algorithm, the choice of the weights is left to the network administrator.

Like WFQ, DRR offers a minimal rate to each flow whatever the size of the packets is. In weighted round robin scheduling, the fraction of bandwidth used depend on the packet's sizes.

Compared with WFQ scheduler that has complexity ofO(log(n)) (n is the number of activeflows/queues), the complexity of DRR isO(1), if the quantum${\displaystyle Q_i}$ is larger than the maximum packet size of this flow. Nevertheless, this efficiency has a cost: the latency,i.e., the distance to the ideal GPS, is larger in DRR than in WFQ.^[2] More on the worst-case latencies can be found here.^[3]

An implementation of the deficit round robin algorithm was written by Patrick McHardy for theLinux kernel^[4] and published under theGNU General Public License.

In Cisco and Juniper routers, modified versions of DRR are implemented: since the latency of DRR can be larger for some class of traffic, these modified versions give higher priority to some queues, whereas the others are served with the standard DRR algorithm.^[5][6]

• Scheduling algorithm
• Fair Queuing
• Generalized processor sharing
• Weighted Fair Queuing
• Weighted round robin
• Fairness measure

• UC Berkeley EE122 lecture: Efficient fair queueing using deficit round robin

• Network scheduling algorithms

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