| AQM working group | T. Høiland-Jørgensen |
| Internet-Draft | Karlstad University |
| Intended status: Informational | P. McKenney |
| Expires: January 5, 2016 | IBM Linux Technology Center |
| D. Taht | |
| Teklibre | |
| J. Gettys | |
| E. Dumazet | |
| Google, Inc. | |
| July 04, 2015 |
FlowQueue-Codel
draft-ietf-aqm-fq-codel-01
This memo presents the FQ-CoDel hybrid packet scheduler/AQM algorithm, a powerful tool for fighting bufferbloat and reducing latency.
FQ-CoDel mixes packets from multiple flows and reduces the impact of head of line blocking from bursty traffic. It provides isolation for low-rate traffic such as DNS, web, and videoconferencing traffic. It improves utilisation across the networking fabric, especially for bidirectional traffic, by keeping queue lengths short; and it can be implemented in a memory- and CPU-efficient fashion across a wide range of hardware.
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The FQ-CoDel algorithm is a combined packet scheduler and AQM developed as part of the bufferbloat-fighting community effort. It is based on a modified Deficit Round Robin (DRR) queue scheduler, with the CoDel AQM algorithm operating on each queue. This document describes the combined algorithm; reference implementations are available for ns2 and ns3 and it is included in the mainline Linux kernel as the fq_codel queueing discipline.
The rest of this document is structured as follows: This section gives some concepts and terminology used in the rest of the document, and gives a short informal summary of the FQ-CoDel algorithm. Section 2 gives an overview of the CoDel algorithm. Section 3 covers the flow hashing and DRR portion. Section 4 defines the parameters and data structures employed by FQ-CoDel. Section 5 describes the working of the algorithm in detail. Section 6 describes implementation considerations, and Section 7 lists some of the limitations of using flow queueing. Section 8 outlines the current status of FQ-CoDel deployment and lists some possible future areas of inquiry, and finally, Section 12 concludes.
Flow: A flow is typically identified by a 5-tuple of source IP, destination IP, source port, destination port, and protocol. It can also be identified by a superset or subset of those parameters, or by mac address, or other means.
Queue: A queue of packets represented internally in FQ-CoDel. In most instances each flow gets its own queue; however because of the possibility of hash collisions, this is not always the case. In an attempt to avoid confusion, the word ‘queue’ is used to refer to the internal data structure, and ‘flow’ to refer to the actual stream of packets being delivered to the FQ-CoDel algorithm.
Scheduler: A mechanism to select which queue a packet is dequeued from.
CoDel AQM: The Active Queue Management algorithm employed by FQ-CoDel.
DRR: Deficit round-robin scheduling.
Quantum: The maximum amount of bytes to be dequeued from a queue at once.
FQ-CoDel is a hybrid of DRR [DRR] and CoDel [CODELDRAFT], with an optimisation for sparse flows similar to SQF [SQF2012] and DRR++ [DRRPP]. We call this “Flow Queueing” rather than “Fair Queueing” as flows that build a queue are treated differently than flows that do not.
FQ-CoDel stochastically classifies incoming packets into different queues by hashing the 5-tuple of IP protocol number and source and destination IP and port numbers, perturbed with a random number selected at initiation time (although other flow classification schemes can optionally be configured instead). Each queue is managed by the CoDel AQM algorithm. Packet ordering within a queue is preserved, since queues have FIFO ordering.
The FQ-CoDel algorithm consists of two logical parts: the scheduler which selects which queue to dequeue a packet from, and the CoDel AQM which works on each of the queues. The subtleties of FQ-CoDel are mostly in the scheduling part, whereas the interaction between the scheduler and the CoDel algorithm are fairly straight forward:
At initialisation, each queue is set up to have a separate set of CoDel state variables. By default, 1024 queues are created. The current implementation supports anywhere from one to 64K separate queues, and each queue maintains the state variables throughout its lifetime, and so acts the same as the non-FQ CoDel variant would. This means that with only one queue, FQ-CoDel behaves essentially the same as CoDel by itself.
On dequeue, FQ-CoDel selects a queue from which to dequeue by a two-tier round-robin scheme, in which each queue is allowed to dequeue up to a configurable quantum of bytes for each iteration. Deviations from this quantum is maintained as a deficit for the queue, which serves to make the fairness scheme byte-based rather than a packet-based. The two-tier round-robin mechanism distinguishes between “new” queues (which don’t build up a standing queue) and “old” queues, that have queued enough data to be around for more than one iteration of the round-robin scheduler.
This new/old queue distinction has a particular consequence for queues that don’t build up more than a quantum of bytes before being visited by the scheduler: Such queues are removed from the list, and then re-added as a new queue each time a packet arrives for it, and so will get priority over queues that do not empty out each round (except for a minor modification to protect against starvation, detailed below). Exactly how little data a flow has to send to keep its queue in this state is somewhat difficult to reason about, because it depends on both the egress link speed and the number of concurrent flows. However, in practice many things that are beneficial to have prioritised for typical internet use (ACKs, DNS lookups, interactive SSH, HTTP requests, ARP, RA, ICMP, VoIP) tend to fall in this category, which is why FQ-CoDel performs so well for many practical applications. However, the implicitness of the prioritisation means that for applications that require guaranteed priority (for instance multiplexing the network control plane over the network itself), explicit classification is still needed.
This scheduling scheme has some subtlety to it, which is explained in detail in the remainder of this document.
CoDel is described in the the ACM Queue paper [CODEL2012], and the AQM working group draft [CODELDRAFT]. The basic idea is to control queue length, maintaining sufficient queueing to keep the outgoing link busy, but avoiding building up the queue beyond that point. This is done by preferentially dropping packets that remain in the queue for “too long”. Packets are dropped by head drop, which lowers the time for the drop signal to propagate back to the sender by the length of the queue, and helps trigger TCP fast retransmit sooner.
The CoDel algorithm itself will not be described here; instead we refer the reader to the CoDel draft [CODELDRAFT].
The intention of FQ-CoDel’s scheduler is to give each flow its own queue, hence the term Flow Queueing. Rather than a perfect realisation of this, a hashing-based scheme is used, where flows are hashed into a number of buckets which each has its own queue. The number of buckets are configurable, and presently defaults to 1024 in the Linux implementation. This is enough to avoid hash collisions on a moderate number of flows as seen for instance in a home gateway. Depending on the characteristics of the link, this can be tuned to trade off memory for a lower probability of hash collisions. See Section 6 for a more in-depth discussion of this.
By default, the flow hashing is performed on the 5-tuple of source and destination IP and port numbers and IP protocol number. While the hashing can be customised to match on arbitrary packet bytes, care should be taken when doing so: Much of the benefit of the FQ-CoDel scheduler comes from this per-flow distinction. However, the default hashing does have some limitations, as discussed in Section 7.
FQ-CoDel’s DRR scheduler is byte-based, employing a deficit round-robin mechanism between queues. This works by keeping track of the current byte deficit of each queue. This deficit is initialised to the configurable quantum; each time a queue gets a dequeue opportunity, it gets to dequeue packets, decreasing the deficit by the packet size for each packet, until the deficit runs into the negative, at which point it is increased by one quantum, and the dequeue opportunity ends.
This means that if one queue contains packets of, for instance, size quantum/3, and another contains quantum-sized packets, the first queue will dequeue three packets each time it gets a turn, whereas the second only dequeues one. This means that flows that send small packets are not penalised by the difference in packet sizes; rather, the DRR scheme approximates a (single-)byte-based fairness queueing. The size of the quantum determines the scheduling granularity, with the tradeoff from too small a quantum being scheduling overhead. For small bandwidths, lowering the quantum from the default MTU size can be advantageous.
Unlike plain DRR there are two sets of flows - a “new” list for flows that have not built a queue recently, and an “old” list for flow-building queues. This distinction is an integral part of the FQ-CoDel scheduler and is described in more detail in Section 5.
This section goes into the parameters and data structures in FQ-CoDel.
The interval parameter has the same semantics as CoDel and is used to ensure that the measured minimum delay does not become too stale. The minimum delay MUST be experienced in the last epoch of length interval. It SHOULD be set on the order of the worst-case RTT through the bottleneck to give end-points sufficient time to react.
The default interval value is 100 ms.
The target parameter has the same semantics as CoDel. It is the acceptable minimum standing/persistent queue delay for each FQ-CoDel Queue. This minimum delay is identified by tracking the local minimum queue delay that packets experience.
The default target value is 5 ms, but this value should be tuned to be at least the transmission time of a single MTU-sized packet at the prevalent egress link speed (which for e.g. 1Mbps and MTU 1500 is ~15ms), to prevent CoDel from being too aggressive at low bandwidths. It should otherwise be set to on the order of 5-10% of the configured interval.
Routers do not have infinite memory, so some packet limit MUST be enforced.
The limit parameter is the hard limit on the real queue size, measured in number of packets. This limit is a global limit on the number of packets in all queues; each individual queue does not have an upper limit. When the limit is reached and a new packet arrives for enqueue, a packet is dropped from the head of the largest queue (measured in bytes) to make room for the new packet.
In Linux, the default packet limit is 10240 packets, which is suitable for up to 10GigE speeds. In practice, the hard limit is rarely, if ever, hit, as drops are performed by the CoDel algorithm long before the limit is hit. For platforms that are severely memory constrained, a lower limit can be used.
The quantum parameter is the number of bytes each queue gets to dequeue on each round of the scheduling algorithm. The default is set to 1514 bytes which corresponds to the Ethernet MTU plus the hardware header length of 14 bytes.
In TSO-enabled systems, where a “packet” consists of an offloaded packet train, it can presently be as large as 64K bytes. In GRO-enabled systems, up to 17 times the TCP max segment size (or 25K bytes). These mega-packets severely impact FQ-CoDel’s ability to schedule traffic, and hurt latency needlessly. There is ongoing work in Linux to make smarter use of offload engines.
The flows parameter sets the number of queues into which the incoming packets are classified. Due to the stochastic nature of hashing, multiple flows may end up being hashed into the same slot.
This parameter can be set only at load time since memory has to be allocated for the hash table in the current implementation.
The default value is 1024 in the current Linux implementation.
ECN is enabled by default. Rather than do anything special with misbehaved ECN flows, FQ-CoDel relies on the packet scheduling system to minimise their impact, thus unresponsive packets in a flow being marked with ECN can grow to the overall packet limit, but will not otherwise affect the performance of the system.
It can be disabled by specifying the noecn parameter.
This parameter enables DCTCP-like processing to enable CE marking ECT packets at a lower setpoint than the default codel target.
ce_threshold is disabled by default and can be set to a number of usec to enable.
The main data structure of FQ-CoDel is the array of queues, which is instantiated to the number of queues specified by the flows parameter at instantiation time. Each queue consists simply of an ordered list of packets with FIFO semantics, two state variables tracking the queue deficit and total number of bytes enqueued, and the set of CoDel state variables. Other state variables to track queue statistics can also be included: for instance, the Linux implementation keeps a count of dropped packets.
Queue space is shared: there’s a global limit on the number of packets the queues can hold, but not one per queue.
FQ-CoDel maintains two lists of active queues, called “new” and “old” queues. Each list is an ordered list containing references to the array of queues. When a packet is added to a queue that is not currently active, that queue becomes active by being added to the list of new queues. Later on, it is moved to the list of old queues, from which it is removed when it is no longer active. This behaviour is the source of some subtlety in the packet scheduling at dequeue time, explained below.
This section describes the operation of the FQ-CoDel scheduler and AQM. It is split into two parts explaining the enqueue and dequeue operations.
The packet enqueue mechanism consists of three stages: classification into a queue, timestamping and bookkeeping, and optionally dropping a packet when the total number of enqueued packets goes over the maximum.
When a packet is enqueued, it is first classified into the appropriate queue. By default, this is done by hashing (using a Jenkins hash function) on the 5-tuple of IP protocol, and source and destination IP and port numbers, permuted by a random value selected at initialisation time, and taking the hash value modulo the number of queues.
Once the packet has been successfully classified into a queue, it is handed over to the CoDel algorithm for timestamping. It is then added to the tail of the selected queue, and the queue’s byte count is updated by the packet size. Then, if the queue is not currently active (i.e. if it is not in either the list of new or the list of old queues), it is added to the end of the list of new queues, and its deficit is initiated to the configured quantum. Otherwise it is added to the old queue list.
Finally, the total number of enqueued packets is compared with the configured limit, and if it is above this value (which can happen since a packet was just enqueued), a packet is dropped from the head of the queue with the largest current byte count. Note that this in most cases means that the packet that gets dropped is different from the one that was just enqueued, and may even be from a different queue.
As mentioned previously, it is possible to modify the classification scheme to provide a different notion of a ‘flow’. The Linux implementation provides this option in the form of the tc filter command. While this can add capabilities (for instance, matching on other possible parameters such as mac address, diffserv, firewall and flow specific markings, etc.), care should be taken to preserve the notion of ‘flow’ as much of the benefit of the FQ-CoDel scheduler comes from keeping flows in separate queues. We are not aware of any deployments utilising the custom classification feature.
An alternative to changing the classification scheme is to perform decapsulation prior to hashing. The Linux implementation does this for common encapsulations known to the kernel, such as 6in4, IPIP and GRE tunnels. This helps to distinguish between flows that share the same (outer) 5-tuple, but of course is limited to unencrypted tunnels (see Section 7.2).
Most of FQ-CoDel’s work is done at packet dequeue time. It consists of three parts: selecting a queue from which to dequeue a packet, actually dequeuing it (employing the CoDel algorithm in the process), and some final bookkeeping.
For the first part, the scheduler first looks at the list of new queues; for each queue in that list, if that queue has a negative deficit (i.e. it has already dequeued at least a quantum of bytes), its deficit is increased by one quantum, and the queue is put onto the end of the list of old queues, and the routine selects the next queue and starts again.
Otherwise, that queue is selected for dequeue. If the list of new queues is empty, the scheduler proceeds down the list of old queues in the same fashion (checking the deficit, and either selecting the queue for dequeuing, or increasing the deficit and putting the queue back at the end of the list).
After having selected a queue from which to dequeue a packet, the CoDel algorithm is invoked on that queue. This applies the CoDel control law, and may discard one or more packets from the head of that queue, before returning the packet that should be dequeued (or nothing if the queue is or becomes empty while being handled by the CoDel algorithm).
Finally, if the CoDel algorithm did not return a packet, the queue is empty, and the scheduler does one of two things: if the queue selected for dequeue came from the list of new queues, it is moved to the end of the list of old queues. If instead it came from the list of old queues, that queue is removed from the list, to be added back (as a new queue) the next time a packet arrives that hashes to that queue. Then (since no packet was available for dequeue), the whole dequeue process is restarted from the beginning.
If, instead, the scheduler did get a packet back from the CoDel algorithm, it updates the byte deficit for the selected queue before returning the packet as the result of the dequeue operation.
The step that moves an empty queue from the list of new queues to the end of the list of old queues before it is removed is crucial to prevent starvation. Otherwise the queue could reappear (the next time a packet arrives for it) before the list of old queues is visited; this can go on indefinitely even with a small number of active flows, if the flow providing packets to the queue in question transmits at just the right rate. This is prevented by first moving the queue to the end of the list of old queues, forcing a pass through that, and thus preventing starvation. Moving it to the end of the list, rather than the front, is crucial for this to work.
The resulting migration of queues between the different states is summarised in the following state diagram:
+-----------------+ +------------------+
| | Empty | |
| Empty |<---------------+ Old +-----+
| | | | |
+-------+---------+ +------------------+ |
| ^ ^ |Quantum
|Arrival | | |Exceeded
v | | |
+-----------------+ | | |
| | Empty or | | |
| New +-------------------+ +--------+
| | Quantum exceeded
+-----------------+
Since the Linux FQ-CoDel implementation by default uses 1024 hash buckets, the probability that (say) 100 VoIP sessions will all hash to the same bucket is something like ten to the power of minus 300. Thus, the probability that at least one of the VoIP sessions will hash to some other queue is very high indeed.
Conversely, the probability that each of the 100 VoIP sessions will get its own queue is given by (1023!/(924!*1024^99)) or about 0.007; so not all that probable. The probability rises sharply, however, if we are willing to accept a few collisions. For example, there is about an 86% probability that no more than two of the 100 VoIP sessions will be involved in any given collision, and about a 99% probability that no more than three of the VoIP sessions will be involved in any given collision. These last two results were computed using Monte Carlo simulations: Oddly enough, the mathematics for VoIP-session collision exactly matches that of hardware cache overflow.
FQ-CoDel can be implemented with a very low memory footprint (less than 64 bytes per queue on 64 bit systems). These are the data structures used in the Linux implementation:
struct codel_vars {
u32 count;
u32 lastcount;
bool dropping;
u16 rec_inv_sqrt;
codel_time_t first_above_time;
codel_time_t drop_next;
codel_time_t ldelay;
};
struct fq_codel_flow {
struct sk_buff *head;
struct sk_buff *tail;
struct list_head flowchain;
int deficit;
u32 dropped; /* # of drops (or ECN marks) on flow */
struct codel_vars cvars;
};
The master table managing all queues looks like this:
struct fq_codel_sched_data {
struct tcf_proto *filter_list; /* optional external classifier */
struct fq_codel_flow *flows; /* Flows table [flows_cnt] */
u32 *backlogs; /* backlog table [flows_cnt] */
u32 flows_cnt; /* number of flows */
u32 perturbation; /* hash perturbation */
u32 quantum; /* psched_mtu(qdisc_dev(sch)); */
struct codel_params cparams;
struct codel_stats cstats;
u32 drop_overlimit;
u32 new_flow_count;
struct list_head new_flows; /* list of new flows */
struct list_head old_flows; /* list of old flows */
};
The CoDel portion of the algorithm requires per-packet timestamps be stored along with the packet. While this approach works well for software-based routers, it may be impossible to retrofit devices that do most of their processing in silicon and lack space or mechanism for timestamping.
Also, while perfect resolution is not needed, timestamp resolution below the target is necessary. Furthermore, timestamping functions in the core OS need to be efficient as they are called at least once on each packet enqueue and dequeue.
Much of the scheduling portion of FQ-CoDel is derived from DRR and is substantially similar to DRR++. SFQ-based versions have also been produced and tested in ns2. Other forms of Fair Queueing, such as WFQ or QFQ, have not been thoroughly explored.
CoDel can be applied to a single queue system as a straight AQM, where it converges towards an “ideal” drop rate (i.e. one that minimises delay while keeping a high link utilisation), and then optimises around that control point.
The scheduling of FQ-CoDel mixes packets of competing flows, which acts to pace bursty flows to better fill the pipe. Additionally, a new flow gets substantial “credit” over other flows until CoDel finds an ideal drop rate for it. However, for a new flow that exceeds the configured quantum, more time passes before all of its data is delivered (as packets from it, too, are mixed across the other existing queue-building flows). Thus, FQ-CoDel takes longer (as measured in time) to converge towards an ideal drop rate for a given new flow, but does so within fewer delivered packets from that flow.
Finally, the flow isolation FQ-CoDel provides means that the CoDel drop mechanism operates on the flows actually building queues, which results in packets being dropped more accurately from the largest flows than CoDel alone manages. Additionally, flow isolation radically improves the transient behaviour of the network when traffic or link characteristics change (e.g. when new flows start up or the link bandwidth changes); while CoDel itself can take a while to respond, fq_codel doesn’t miss a beat.
While FQ-CoDel has been shown in many scenarios to offer significant performance gains, there are some scenarios where the scheduling algorithm in particular is not a good fit. This section documents some of the known cases which either may require tweaking the default behaviour, or where alternatives to flow queueing should be considered.
In some parts of the network, enforcing flow-level fairness may not be desirable, or some other form of fairness may be more important. An example of this can be an Internet Service Provider that may be more interested in ensuring fairness between customers than between flows. Or a hosting or transit provider that wishes to ensure fairness between connecting Autonomous Systems or networks. Another issue can be that the number of simultaneous flows experienced at a particular link can be too high for flow-based fairness queueing to be effective.
Whatever the reason, in a scenario where fairness between flows is not desirable, reconfiguring FQ-CoDel to match on a different characteristic can be a way forward. The implementation in Linux can leverage the packet matching mechanism of the tc subsystem to use any available packet field to partition packets into virtual queues, to for instance match on address or subnet source/destination pairs, application layer characteristics, etc.
Furthermore, as commonly deployed today, FQ-CoDel is used with three or more tiers of classification: priority, best effort and background, based on diffserv markings. Some products do more detailed classification, including deep packet inspection and destination-specific filters to achieve their desired result.
Where possible, FQ-CoDel will attempt to decapsulate packets before matching on the header fields for the flow hashing. However, for some encapsulation techniques, most notably encrypted VPNs, this is not possible. If several flows are bunched into one such encapsulated tunnel, they will be seen as one flow by the FQ-CoDel algorithm. This means that they will share a queue, and drop behaviour, and so flows inside the encapsulation will not benefit from the implicit prioritisation of FQ-CoDel, but will continue to benefit from the reduced overall queue length from the CoDel algorithm operating on the queue. In addition, when such an encapsulated bunch competes against other flows, it will count as one flow, and not assigned a share of the bandwidth based on how many flows are inside the encapsulation.
Depending on the application, this may or may not be desirable behaviour. In cases where it is not, changing FQ-CoDel’s matching to not be flow-based (as detailed in the previous subsection above) can be a mitigation. Going forward, having some mechanism for opaque encapsulations to express to the outer layer which flow a packet belongs to, could be a way to mitigate this.
In the presence of queue management schemes that contain latency under load, low-priority congestion control algorithms such as LEDBAT [RFC6817] (or, in general, algorithms that try to voluntarily use up less than their fair share of bandwidth) experiences very little added latency when the link is congested. Thus, they lack the signal to back off that added latency previously afforded them. This effect is seen with FQ-CoDel as well as with any effective AQM [GONG2014].
As such, these delay-based algorithms tend to revert to loss-based congestion control, and will consume the fair share of bandwidth afforded to them by the FQ-CoDel scheduler. However, low-priority congestion control mechanisms may be able to take steps to continue to be low priority, for instance by taking into account the vastly reduced level of delay afforded by an AQM, or by using a coupled approach to observing the behaviour of multiple flows.
The FQ-CoDel algorithm as described in this document has been shipped as part of the Linux kernel since version 3.5, released on the 21st of July, 2012. The CE_THRESHOLD was added in version 4.0. It has seen widespread testing in a variety of contexts and is configured as the default queueing discipline in a number of mainline Linux distributions (as of this writing at least OpenWRT, Arch Linux and Fedora). We believe it to be a safe default and encourage people running Linux to turn it on: It is a massive improvement over the previous default FIFO queue.
Of course there is always room for improvement, and this document has listed some of the know limitations of the algorithm. As such, we encourage further research into algorithm refinements and addressing of limitations. One such effort is undertaken by the bufferbloat community in the form of the Cake queue management scheme. In addition to this we believe the following (non-exhaustive) list of issues to be worthy of further enquiry:
There are no specific security exposures associated with FQ-CoDel. Some exposures present in current FIFO systems are in fact reduced (e.g. simple minded packet floods).
This document has no actions for IANA.
Our deepest thanks to Kathie Nichols, Van Jacobson, and all the members of the bufferbloat.net effort.
FQ-CoDel is a very general, efficient, nearly parameterless queue management approach combining flow queueing with CoDel. It is a very powerful tool for solving bufferbloat, and we believe it to be safe to turn on by default, as has already happened in a number of Linux distributions. In this document we have documented the Linux implementation in sufficient detail for an independent implementation, and we encourage such implementations be widely deployed.
| [CODELDRAFT] | Nichols, K., Jacobson, V., McGregor, A. and J. Iyengar, "Controlled Delay Active Queue Management", October 2014. |
| [RFC6817] | Shalunov, S., Hazel, G., Iyengar, J. and M. Kuehlewind, "Low Extra Delay Background Transport (LEDBAT)", RFC 6817, December 2012. |
| [RTCWEB-QOS] | Dhesikan, S., Jennings, C., Druta, D., Jones, P. and J. Polk, "DSCP and other packet markings for RTCWeb QoS", December 2014. |
| [CODEL2012] | Nichols, K. and V. Jacobson, "Controlling Queue Delay", July 2012. |
| [DRR] | Shreedhar, M. and G. Varghese, "Efficient Fair Queueing Using Deficit Round Robin", June 1996. |
| [DRRPP] | MacGregor, M. and W. Shi, "Deficits for Bursty Latency-critical Flows: DRR++", 2000. |
| [GONG2014] | Gong, Y., Rossi, D., Testa, C., Valenti, S. and D. Taht, "Fighting the bufferbloat: on the coexistence of AQM and low priority congestion control", July 2014. |
| [SQF2012] | Bonald, T., Muscariello, L. and N. Ostallo, "On the impact of TCP and per-flow scheduling on Internet Performance - IEEE/ACM transactions on Networking", April 2012. |