Next Previous Contents

9. More queueing disciplines

The Linux kernel offers us lots of queueing disciplines. By far the most widely used is the pfifo_fast queue - this is the default. This also explains why these advanced features are so robust. They are nothing more than 'just another queue'.

Each of these queues has specific strengths and weaknesses. Not all of them may be as well tested.

9.1 pfifo_fast

This queue is, as the name says, First In, First Out, which means that no packet receives special treatment. At least, not quite. This queue has 3 so called 'bands'. Within each band, FIFO rules apply. However, as long as there are packets waiting in band 0, band 1 won't be processed. Same goes for band 1 and band 2.

9.2 Stochastic Fairness Queueing

SFQ, as said earlier, is not quite deterministic, but works (on average). Its main benefits are that it requires little CPU and memory. 'Real' fair queueing requires that the kernel keep track of all running sessions.

Stochastic Fairness Queueing (SFQ) is a simple implementation of fair queueing algorithms family. It's less accurate than others, but it also requires less calculations while being almost perfectly fair.

The key word in SFQ is conversation (or flow), being a sequence of data packets having enough common parameters to distinguish it from other conversations. The parameters used in case of IP packets are source and destination address, and the protocol number.

SFQ consists of dynamically allocated number of FIFO queues, one queue for one conversation. The discipline runs in round-robin, sending one packet from each FIFO in one turn, and this is why it's called fair. The main advantage of SFQ is that it allows fair sharing the link between several applications and prevent bandwidth take-over by one client. SFQ however cannot determine interactive flows from bulk ones -- one usually needs to do the selection with CBQ before, and then direct the bulk traffic into SFQ.

9.3 Token Bucket Filter

The Token Bucket Filter (TBF) is a simple queue, that only passes packets arriving at rate in bounds of some administratively set limit, with possibility to buffer short bursts.

The TBF implementation consists of a buffer (bucket), constatly filled by some virtual pieces of information called tokens, at specific rate (token rate). The most important parameter of the bucket is its size, that is number of tokens it can store.

Each arriving token lets one incoming data packet of out the queue and is then deleted from the bucket. Associating this algorithm with the two flows -- token and data, gives us three possible scenarios:

The last scenario is very important, because it allows to administratively shape the bandwidth available to data, passing the filter. The accumulation of tokens allows short burst of overlimit data to be still passed without loss, but any lasting overload will cause packets to be constantly dropped.

The Linux kernel seems to go beyond this specification, and also allows us to limit the speed of the burst transmission. However, Alexey warns us:

Note that the peak rate TBF is much more tough: with MTU 1500 P_crit = 150Kbytes/sec. So, if you need greater peak rates, use alpha with HZ=1000 :-)

FIXME: is this still true with TSC (pentium+)? Well sort of

FIXME: if not, add section on raising HZ

9.4 Random Early Detect

RED has some extra smartness built in. When a TCP/IP session starts, neither end knows the amount of bandwidth available. So TCP/IP starts to transmit slowly and goes faster and faster, though limited by the latency at which ACKs return.

Once a link is filling up, RED starts dropping packets, which indicate to TCP/IP that the link is congested, and that it should slow down. The smart bit is that RED simulates real congestion, and starts to drop some packets some time before the link is entirely filled up. Once the link is completely saturated, it behaves like a normal policer.

For more information on this, see the Backbone chapter.

9.5 Ingress policer qdisc

The Ingress qdisc comes in handy if you need to ratelimit a host without help from routers or other Linux boxes. You can police incoming bandwidth and drop packets when this bandwidth exceeds your desired rate. This can save your host from a SYN flood, for example, and also works to slow down TCP/IP, which responds to dropped packets by reducing speed.

FIXME: instead of dropping, can we also assign it to a real queue?

FIXME: shaping by dropping packets seems less desirable than using, for example, a token bucket filter. Not sure though, Cisco CAR works this way, and people appear happy with it.

See the reference to IOS Committed Access Rate at the end of this document.

In short: you can use this to limit how fast your computer downloads files, thus leaving more of the available bandwidth for others.

See the section on protecting your host from SYN floods for an example on how this works.

9.6 WRR

This qdisc is not included in the standard kernels but can be downloaded from Currently the qdisc is only tested with Linux 2.2 kernels but it will probably work with 2.4 kernels too.

The WRR qdisc distributes bandwidth between its classes using the weighted round robin scheme. That is, like the CBQ qdisc it contains classes into which arbitrary qdiscs can be plugged. All classes which have sufficient demand will get bandwidth proportional to the weights associated with the classes. The weights can be set manually using the tc program. But they can also be made automatically decreasing for classes transferring much data.

The qdisc has a build-in classifier which assigns packets coming from or sent to different machines to different classes. Either the MAC or IP and either source or destination addresses can be used. The MAC address can only be used when the Linux box is acting as an ethernet bridge, however. The classes are automatically assigned to machines based on the packets seen.

The qdisc can be very useful at sites such as dorms where a lot of unrelated individuals share an Internet connection. A set of scripts setting up a relevant behavior for such a site is a central part of the WRR distribution.

Next Previous Contents