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IETF RFC 8290
Last modified on Saturday, January 6th, 2018
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Internet Engineering Task Force (IETF) T. Hoeiland-Joergensen
Request for Comments: 8290 Karlstad University
Category: Experimental P. McKenney
ISSN: 2070-1721 IBM Linux Technology Center
D. Taht
Teklibre
J. Gettys
E. Dumazet
Google, Inc.
January 2018
The Flow Queue CoDel Packet Scheduler and
Active Queue Management Algorithm
 Abstract
This memo presents the FQ-CoDel hybrid packet scheduler and Active
Queue Management (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.
Status of This Memo
This document is not an Internet Standards Track specification; it is
published for examination, experimental implementation, and
evaluation.
This document defines an Experimental Protocol for the Internet
community. This document is a product of the Internet Engineering
Task Force (IETF). It represents the consensus of the IETF
community. It has received public review and has been approved for
publication by the Internet Engineering Steering Group (IESG). Not
all documents approved by the IESG are a candidate for any level of
Internet Standard; see Section 2 of RFC 7841.
Information about the current status of this document, any errata,
and how to provide feedback on it may be obtained at
https://www.rfc-editor.org/info/RFC 8290.
Hoeiland-Joergensen, et al. Experimental PAGE 1 
RFC 8290 FQ-CoDel January 2018
Copyright Notice
Copyright (c) 2018 IETF Trust and the persons identified as the
document authors. All rights reserved.
This document is subject to BCP 78 and the IETF Trust's Legal
Provisions Relating to IETF Documents
(https://trustee.ietf.org/license-info) in effect on the date of
publication of this document. Please review these documents
carefully, as they describe your rights and restrictions with respect
to this document. Code Components extracted from this document must
include Simplified BSD License text as described in Section 4.e of
the Trust Legal Provisions and are provided without warranty as
described in the Simplified BSD License.
Hoeiland-Joergensen, et al. Experimental PAGE 2
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Table of Contents
1. Introduction . . . . . . . . . . . . . . . . . . . . . . . . 4
1.1. Conventions Used in This Document . . . . . . . . . . . . 4
1.2. Terminology and Concepts . . . . . . . . . . . . . . . . 5
1.3. Informal Summary of FQ-CoDel . . . . . . . . . . . . . . 5
2. CoDel . . . . . . . . . . . . . . . . . . . . . . . . . . . . 7
3. Flow Queueing . . . . . . . . . . . . . . . . . . . . . . . . 7
4. The FQ-CoDel Scheduler . . . . . . . . . . . . . . . . . . . 8
4.1. Enqueue . . . . . . . . . . . . . . . . . . . . . . . . . 8
4.1.1. Alternative Classification Schemes . . . . . . . . . 9
4.2. Dequeue . . . . . . . . . . . . . . . . . . . . . . . . . 10
5. Implementation Considerations . . . . . . . . . . . . . . . . 11
5.1. Data Structures . . . . . . . . . . . . . . . . . . . . . 11
5.2. Parameters . . . . . . . . . . . . . . . . . . . . . . . 12
5.2.1. Interval . . . . . . . . . . . . . . . . . . . . . . 12
5.2.2. Target . . . . . . . . . . . . . . . . . . . . . . . 12
5.2.3. Packet Limit . . . . . . . . . . . . . . . . . . . . 13
5.2.4. Quantum . . . . . . . . . . . . . . . . . . . . . . . 13
5.2.5. Flows . . . . . . . . . . . . . . . . . . . . . . . . 13
5.2.6. Explicit Congestion Notification (ECN) . . . . . . . 14
5.2.7. CE Threshold . . . . . . . . . . . . . . . . . . . . 14
5.3. Probability of Hash Collisions . . . . . . . . . . . . . 14
5.4. Memory Overhead . . . . . . . . . . . . . . . . . . . . . 15
5.5. Per-Packet Timestamping . . . . . . . . . . . . . . . . . 16
5.6. Limiting Queueing in Lower Layers . . . . . . . . . . . . 16
5.7. Other Forms of Fair Queueing . . . . . . . . . . . . . . 17
5.8. Differences between CoDel and FQ-CoDel Behaviour . . . . 17
6. Limitations of Flow Queueing . . . . . . . . . . . . . . . . 18
6.1. Fairness between Things Other Than Flows . . . . . . . . 18
6.2. Flow Bunching by Opaque Encapsulation . . . . . . . . . . 18
6.3. Low-Priority Congestion Control Algorithms . . . . . . . 19
7. Deployment Status and Future Work . . . . . . . . . . . . . . 19
8. Security Considerations . . . . . . . . . . . . . . . . . . . 20
9. IANA Considerations . . . . . . . . . . . . . . . . . . . . . 21
10. References . . . . . . . . . . . . . . . . . . . . . . . . . 21
10.1. Normative References . . . . . . . . . . . . . . . . . . 21
10.2. Informative References . . . . . . . . . . . . . . . . . 21
Acknowledgements . . . . . . . . . . . . . . . . . . . . . . . . 24
Authors' Addresses . . . . . . . . . . . . . . . . . . . . . . . 25
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1. Introduction
The Flow Queue CoDel (FQ-CoDel) algorithm is a combined packet
scheduler and Active Queue Management (AQM) [RFC 3168] algorithm
developed as part of the bufferbloat-fighting community effort
[BLOATWEB]. It is based on a modified Deficit Round Robin (DRR)
queue scheduler [DRR] [DRRPP] with the CoDel AQM [RFC 8289] algorithm
operating on each queue. This document describes the combined
algorithm; reference implementations are available for the ns-2 [NS2]
and ns-3 [NS3] network simulators, and the algorithm is included in
the mainline Linux kernel as the fq_codel queueing discipline
[LINUXSRC].
FQ-CoDel is a general, efficient, nearly parameterless queue
management approach combining flow queueing with CoDel. It is a
powerful tool for solving bufferbloat [BLOAT] and has already been
turned on by default in a number of Linux distributions. In this
document, we describe the Linux implementation in sufficient detail
for others to independently implement the algorithm for deployment
outside the Linux ecosystem.
Since the FQ-CoDel algorithm was originally developed in the Linux
kernel, that implementation is still considered canonical. This
document describes the algorithm in the abstract in Sections 1-4 and
separates out most implementation details in subsequent sections;
however, the Linux implementation is used as a reference for default
behaviour in the abstract algorithm description.
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 then describes the working of the
algorithm in detail, while Section 5 describes implementation details
and considerations. Section 6 lists some of the limitations of using
flow queueing. Section 7 outlines the current status of FQ-CoDel
deployment and lists some possible future areas of inquiry. Finally,
Section 8 reiterates some important security points that must be
observed in the implementation.
1.1. Conventions Used in This Document
The key words "MUST", "MUST NOT", "REQUIRED", "SHALL", "SHALL NOT",
"SHOULD", "SHOULD NOT", "RECOMMENDED", "NOT RECOMMENDED", "MAY", and
"OPTIONAL" in this document are to be interpreted as described in
BCP 14 [RFC 2119] [RFC 8174] when, and only when, they appear in all
capitals, as shown here.
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1.2. Terminology and Concepts
Flow: A flow is typically identified by a 5-tuple of source IP
address, destination IP address, source port number, destination
port number, and protocol number. It can also be identified by a
superset or subset of those parameters, by Media Access Control
(MAC) address, or by other means. FQ-CoDel hashes flows into a
configurable number of buckets to assign packets to internal
queues.
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" is used 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 as described in [RFC 8289].
DRR: Deficit Round Robin scheduling [DRR].
Quantum: The maximum amount of bytes to be dequeued from a queue at
once.
Interval: Characteristic time period used by the control loop of
CoDel to detect when a persistent queue is developing (see
Section 4.2 of [RFC 8289]).
Target: Setpoint value of the minimum sojourn time of packets in a
queue used as the target of the control loop in CoDel (see
Section 4.3 of [RFC 8289]).
1.3. Informal Summary of FQ-CoDel
FQ-CoDel is a hybrid of DRR [DRR] and CoDel [RFC 8289], with an
optimisation for sparse flows similar to Shortest Queue First (SQF)
[SQF] and DRR++ [DRRPP]. We call this "flow queueing" rather than
"fair queueing", as flows that build a queue are treated differently
from flows that do not.
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By default, FQ-CoDel stochastically classifies incoming packets into
different queues by hashing the 5-tuple of protocol number, source
and destination IP addresses, and source and destination port
numbers, perturbed with a random number selected at initiation time
(although other flow classification schemes can optionally be
configured instead; see Section 4.1.1). Each queue is managed by the
CoDel AQM algorithm [CODEL] [RFC 8289]. Packet ordering within a
queue is preserved, since queues have FIFO ordering.
The FQ-CoDel algorithm consists of two logical parts: (1) the
scheduler, which selects which queue to dequeue a packet from, and
(2) 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
straightforward.
At initialisation, each queue is set up to have a separate set of
CoDel state variables. By default, 1024 queues are created. The
Linux implementation at the time of writing supports anywhere from
one to 65535 separate queues, and each queue maintains the state
variables throughout its lifetime, and so acts the same as the non-FQ
variant of CoDel 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 are maintained as byte credits for the queue, which
serves to make the fairness scheme byte-based rather than packet-
based. The two-tier, round-robin mechanism distinguishes between
"new" queues (which don't build up a standing queue) and "old" queues
(which have queued enough data to be active 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 a queue will be removed from the list
after it empties and then re-added as a new queue the next time a
packet arrives for it. This means it will effectively get priority
over queues that do not empty out each round (a minor caveat is
required here to protect against starvation, see 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 Secure Shell
(SSH), HTTP requests, Voice over IP (VoIP)) _tend_ to fall in this
category, which is why FQ-CoDel performs so well for many practical
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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.
2. CoDel
CoDel is described in the Communications of the ACM paper [CODEL] and
the IETF document [RFC 8289]. 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 document [RFC 8289].
3. Flow Queueing
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, each of which has its own queue.
The number of buckets is 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 Sections 5.3 and 5.4 for a more in-depth discussion of this.
By default, the flow hashing is performed on the 5-tuple of source
and destination IP addresses, source and destination port numbers,
and 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 6.
FQ-CoDel's DRR scheduler is byte-based, employing a deficit round-
robin mechanism between queues. This works by keeping track of the
current number of "byte credits" of each queue. This number is
initialised to the configurable quantum; each time a queue gets a
dequeue opportunity, it gets to dequeue packets, thus decreasing the
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number of credits by the packet size for each packet. This continues
until the value of the byte credits counter becomes zero or less, at
which point the counter 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 byte-based fairness queueing scheme.
The size of the quantum determines the scheduling granularity, with
the trade-off 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 queues
that build a backlog. This distinction is an integral part of the
FQ-CoDel scheduler and is described in more detail in Section 4.
4. The FQ-CoDel Scheduler
To make its scheduling decisions, FQ-CoDel maintains two ordered
lists of active queues: new and old 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, as explained below.
4.1. Enqueue
The packet enqueue mechanism consists of three stages: classifying
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 [JENKINS]) on the 5-tuple of IP protocol,
source and destination IP addresses, and source and destination port
numbers (if they exist) and then taking the hash value modulo the
number of queues. The hash is salted by modulo addition of a random
value selected at initialisation time to prevent possible DoS attacks
if the hash is predictable ahead of time (see Section 8). The Linux
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kernel implements the Jenkins hash function by mixing three 32-bit
values into a single 32-bit output value. Inputs larger than 96 bits
are reduced by additional mixing steps, 96 bits at a time.
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 queues or the
list of old queues), it is added to the end of the list of new
queues, and its number of credits is initiated to the configured
quantum. Otherwise, the queue is left in its current queue list.
Finally, to protect against overload, the total number of enqueued
packets is compared with the configured limit. If the limit is
exceeded (which can happen since a packet was just enqueued), the
queue with the largest current byte count is selected and half the
number of packets from this queue (up to a maximum of 64 packets) are
dropped from the head of that queue. Dropping several packets at
once helps amortise the cost of finding the longest queue,
significantly lowering CPU usage in an overload situation.
4.1.1. Alternative Classification Schemes
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 code point
values, firewall rules, flow-specific markings, IPv6 flow label,
etc.), care should be taken to preserve the notion of flow because
much of the benefit of the FQ-CoDel scheduler comes from keeping
flows in separate queues.
For protocols that do not contain a port number (such as ICMP), the
Linux implementation simply sets the port numbers to zero and
performs the hashing as usual. In practice, this results in such
protocols each getting their own queue (except in the case of hash
collisions). An implementation can perform other classifications for
protocols that have their own notion of a flow but SHOULD fall back
to simply hashing on source and destination IP address and protocol
number in the absence of other information.
The default classification scheme can additionally be improved by
performing decapsulation of tunnelled packets prior to hashing on the
5-tuple in the encapsulated payload. The Linux implementation does
this for common encapsulations known to the kernel, such as 6in4
[RFC 4213], IP-in-IP [RFC 2003], and Generic Routing Encapsulation
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(GRE) [RFC 2890]. This helps to distinguish between flows that share
the same (outer) 5-tuple but, of course, is limited to unencrypted
tunnels (see Section 6.2 for a discussion of encrypted tunnels).
4.2. Dequeue
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 dequeueing 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 the queue at the head of that list, if that queue has a
negative number of credits (i.e., it has already dequeued at least a
quantum of bytes), it is given an additional quantum of credits, 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 credits and either selecting the
queue for dequeueing or adding credits 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, which is the mechanism CoDel uses to determine when to
drop packets (see [RFC 8289]). As a result of this, one or more
packets may be discarded from the head of the selected queue before
the packet that should be dequeued is returned (or nothing is
returned if the queue is or becomes empty while being handled by the
CoDel algorithm).
Finally, if the CoDel algorithm does not return a packet, then the
queue must be 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 subtracts the size of the packet from the byte credits
for the selected queue and returns the packet as the result of the
dequeue operation.
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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 the scheduler
to service all old queues before the empty queue is removed and thus
preventing starvation.
The resulting migration of queues between the different states is
summarised in the state diagram shown in Figure 1. Note that both
the new and old queue states can additionally have arrival and
dequeue events that do not change the state; these are omitted in the
figure.
+-----------------+ +------------------+
| | Empty | |
| Empty |<---------------+ Old +----+
| | | | |
+-------+---------+ +------------------+ |
| ^ ^ |Credits
|Arrival | | |Exhausted
v | | |
+-----------------+ | | |
| | Empty or | | |
| New +-------------------+ +-------+
| | Credits Exhausted
+-----------------+
Figure 1: Partial State Diagram for Queues between Different States
5. Implementation Considerations
This section contains implementation details for the FQ-CoDel
algorithm. This includes the data structures and parameters used in
the Linux implementation, as well as discussion of some required
features of the target platform and other considerations.
5.1. Data Structures
The main data structure of FQ-CoDel is the array of queues, which is
instantiated with 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 credits and total number of bytes enqueued, and
the set of CoDel state variables. Other state variables to track
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queue statistics can also be included; for instance, the Linux
implementation keeps a count of dropped packets.
In addition to the queue structures themselves, FQ-CoDel maintains
two ordered lists containing references to the subset of queues that
are currently active. These are the lists of new and old queues, as
explained in Section 4 above.
In the Linux implementation, queue space is shared: there's a global
limit on the number of packets the queues can hold, but not a limit
for each queue.
5.2. Parameters
The following are the user configuration parameters exposed by the
Linux implementation of FQ-CoDel.
5.2.1. Interval
The "interval" parameter has the same semantics as CoDel and is used
to ensure that the minimum sojourn time of packets in a queue used as
an estimator by the CoDel control algorithm is a relatively up-to-
date value. That is, CoDel only reacts to delay experienced in the
last epoch of length interval. It SHOULD be set to be 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.
5.2.2. Target
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 example, is ~15 ms for 1 Mbps
and MTU 1500). This prevents CoDel from being too aggressive at low
bandwidths. It should otherwise be set to 5-10% of the configured
interval.
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5.2.3. Packet Limit
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, packets are 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 10-Gigabit Ethernet 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.
5.2.4. Quantum
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 systems employing TCP Segmentation Offload (TSO), where a "packet"
consists of an offloaded packet train, it can presently be as large
as 64 kilobytes. In systems using Generic Receive Offload (GRO),
they can be up to 17 times the TCP max segment size (or 25
kilobytes). These mega-packets severely impact FQ-CoDel's ability to
schedule traffic, and they hurt latency needlessly. There is ongoing
work in Linux to make smarter use of offload engines.
5.2.5. Flows
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 initialisation time in the current
implementation, since memory has to be allocated for the hash table.
The default value is 1024 in the current Linux implementation.
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5.2.6. Explicit Congestion Notification (ECN)
ECN [RFC 3168] 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, the number of 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.
ECN can be disabled by specifying the "noecn" parameter.
5.2.7. CE Threshold
This parameter enables DCTCP-like processing resulting in Congestion
Encountered (CE) marking on ECN-Capable Transport (ECT) packets
[RFC 3168] starting at a lower sojourn delay setpoint than the default
CoDel target. Details of Data Center TCP (DCTCP) can be found in
[RFC 8257].
The "ce_threshold" parameter is disabled by default; it can be
enabled by setting it to a number of microseconds.
5.3. Probability of Hash Collisions
Since the Linux FQ-CoDel implementation by default uses 1024 hash
buckets, the probability that (say) 100 flows will all hash to the
same bucket is something like ten to the power of minus 300. Thus,
at least one of the flows will almost certainly hash to some other
queue.
Expanding on this, based on analytical equations for hash collision
probabilities, for 100 flows, the probability of no collision is
90.78%; the probability that no more than two of the 100 flows will
be involved in any given collision is 99.57%; and the probability
that no more than three of the 100 flows will be involved in any
given collision is 99.99%. These probabilities assume a hypothetical
perfect hashing function, so in practice, they may be a bit lower.
We have not found this difference to matter in practice.
These probabilities can be improved upon by using set-associative
hashing, a technique used in the Cake algorithm currently being
developed as a further refinement of the FQ-CoDel principles [CAKE].
For a 4-way associative hash with the same number of total queues,
the probability of no collisions for 100 flows is 99.93%, while for
an 8-way associative hash, it is ~100%.
Hoeiland-Joergensen, et al. Experimental PAGE 14
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5.4. Memory Overhead
FQ-CoDel can be implemented with a low memory footprint (less than 64
bytes per queue on 64-bit systems). These are the data structures
used in the Linux implementation:
<CODE BEGINS>
struct codel_vars {
u32 count; /* number of dropped packets */
u32 lastcount; /* count entry to dropping state */
bool dropping; /* currently dropping? */
u16 rec_inv_sqrt; /* reciprocal sqrt computation */
codel_time_t first_above_time; /* when delay above target */
codel_time_t drop_next; /* next time to drop */
codel_time_t ldelay; /* sojourn time of last dequeued packet */
};
struct fq_codel_flow {
struct sk_buff *head;
struct sk_buff *tail;
struct list_head flowchain;
int credits; /* current number of queue credits */
u32 dropped; /* # of drops (or ECN marks) on flow */
struct codel_vars cvars;
};
<CODE ENDS>
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The master table managing all queues looks like this:
<CODE BEGINS>
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 */
};
<CODE ENDS>
5.5. Per-Packet Timestamping
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 the space or
mechanism for timestamping.
Also, while perfect resolution is not needed, timestamp resolution
finer than the CoDel target setting 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.
5.6. Limiting Queueing in Lower Layers
When deploying a queue management algorithm such as FQ-CoDel, it is
important to ensure that the algorithm actually runs in the right
place to control the queue. In particular, lower layers of the
operating system networking stack can have queues of their own, as
can device drivers and hardware. Thus, it is desirable that the
queue management algorithm runs as close to the hardware as possible.
However, scheduling such complexity at interrupt time is difficult,
so a small standing queue between the algorithm and the wire is often
needed at higher transmit rates.
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In Linux, the mechanism to ensure these different needs are balanced
is called "Byte Queue Limits" [BQL]; it controls the device driver
ring buffer (for physical line rates). For cases where this
functionality is not available, the queue can be controlled by means
of a software rate limiter such as Hierarchical Token Bucket [HTB] or
Hierarchical Fair-Service Curve [HFSC]. The Cake algorithm [CAKE]
integrates a software rate limiter for this purpose.
Other issues with queues at lower layers are described in [CODEL].
5.7. Other Forms of Fair Queueing
Much of the scheduling portion of FQ-CoDel is derived from DRR and is
substantially similar to DRR++. Versions based on Stochastic Fair
Queueing [SFQ] have also been produced and tested in ns2. Other
forms of fair queueing, such as Weighted Fair Queueing [WFQ] or Quick
Fair Queueing [QFQ], have not been thoroughly explored, but there's
no a priori reason why the round-robin scheduling of FQ-CoDel
couldn't be replaced with something else.
For a comprehensive discussion of fairness queueing algorithms and
their combination with AQM, see [RFC 7806].
5.8. Differences between CoDel and FQ-CoDel Behaviour
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 leeway 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 provided by FQ-CoDel means that the CoDel
drop mechanism operates on the flows actually building queues; this
results in packets being dropped more accurately from the largest
flows than when only CoDel is used. 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 reacts almost immediately.
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6. Limitations of Flow Queueing
While FQ-CoDel has been shown in many scenarios to offer significant
performance gains compared to alternative queue management
strategies, there are some scenarios where the scheduling algorithm
in particular is not a good fit. This section documents some of the
known cases in which either the default behaviour may require
tweaking or alternatives to flow queueing should be considered.
6.1. Fairness between Things Other Than Flows
In some parts of the network, enforcing flow-level fairness may not
be desirable, or some other form of fairness may be more important.
Some examples of this include an ISP 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,
for instance, to 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 service classification, based on Diffserv markings:
priority, best effort, and background. Some products do more
detailed classification, including deep packet inspection and
destination-specific filters to achieve their desired result.
6.2. Flow Bunching by Opaque Encapsulation
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, 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
Hoeiland-Joergensen, et al. Experimental PAGE 18
RFC 8290 FQ-CoDel January 2018
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. Naturally, care needs to
be taken when designing such a mechanism to ensure no new privacy and
security issues are raised by exposing information from inside the
encapsulation to the outside world. Keeping the extra information
out of band and dropping it before it hits the network could be one
way to achieve this.
6.3. Low-Priority Congestion Control Algorithms
In the presence of queue management schemes that limit latency under
load, low-priority congestion control algorithms such as Low Extra
Delay Background Transport (LEDBAT) [RFC 6817] (or, in general,
algorithms that try to voluntarily use up less than their fair share
of bandwidth) experience 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.
7. Deployment Status and Future Work
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), with the ce_threshold being added in version 4.2.
The algorithm 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). In addition, a BSD implementation is
available. All data resulting from these trials have shown FQ-CoDel
to be a massive improvement over the previous default FIFO queue, and
people are encouraged to turn it on.
Hoeiland-Joergensen, et al. Experimental PAGE 19
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Of course, there is always room for improvement, and this document
has listed some of the known limitations of the algorithm. As such,
we encourage further research into algorithm refinements and
addressing of limitations. One such effort has been undertaken by
the bufferbloat community in the form of the Cake queue management
scheme [CAKE]. In addition to this, we believe the following
(non-exhaustive) list of issues to be worthy of further enquiry:
o Variations on the flow classification mechanism to fit different
notions of flows. For instance, an ISP might want to deploy per-
subscriber scheduling, while in other cases, several flows can
share a 5-tuple, as exemplified by the RTCWEB QoS recommendations
[WEBRTC-QOS].
o Interactions between flow queueing and delay-based congestion
control algorithms and scavenger protocols.
o Other scheduling mechanisms to replace the DRR portion of the
algorithm, e.g., QFQ or WFQ.
o Sensitivity of parameters, most notably, the number of queues and
the CoDel parameters.
8. Security Considerations
There are no specific security exposures associated with FQ-CoDel
that are not also present in current FIFO systems. On the contrary,
some vulnerabilities of FIFO systems are reduced with FQ-CoDel (e.g.,
simple minded packet floods). However, some care is needed in the
implementation to ensure this is the case. These are included in the
description above, but we reiterate them here:
o To prevent packets in the new queues from starving old queues, it
is important that when a queue on the list of new queues empties,
it is moved to _the end of_ the list of old queues. This is
described at the end of Section 4.2.
o To prevent an attacker targeting a specific flow for a denial-of-
service attack, the hash that maps packets to queues should not be
predictable. To achieve this, FQ-CoDel salts the hash, as
described in the beginning of Section 4.1. The size of the salt
and the strength of the hash function is obviously a trade-off
between performance and security. The Linux implementation uses a
32-bit random value as the salt and a Jenkins hash function. This
makes it possible to achieve high throughput, and we consider it
sufficient to ward off the most obvious attacks.
Hoeiland-Joergensen, et al. Experimental PAGE 20
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o Packet fragments without a Layer 4 header can be hashed into
different bins than the first fragment with the header intact.
This can cause reordering and/or adversely affect the performance
of the flow. Keeping state to match the fragments to the
beginning of the packet or simply putting all packet fragments
(including the first fragment of each fragmented packet) into the
same queue are two ways to alleviate this.
9. IANA Considerations
This document does not require any IANA actions.
10. References
10.1. Normative References
[RFC 2119] Bradner, S., "Key words for use in RFCs to Indicate
Requirement Levels", BCP 14, RFC 2119,
DOI 10.17487/RFC 2119, March 1997,
<https://www.rfc-editor.org/info/RFC 2119>.
[RFC 7806] Baker, F. and R. Pan, "On Queuing, Marking, and Dropping",
RFC 7806, DOI 10.17487/RFC 7806, April 2016,
<https://www.rfc-editor.org/info/RFC 7806>.
[RFC 8174] Leiba, B., "Ambiguity of Uppercase vs Lowercase in RFC
2119 Key Words", BCP 14, RFC 8174, DOI 10.17487/RFC 8174,
May 2017, <https://www.rfc-editor.org/info/RFC 8174>.
[RFC 8289] Nichols, K., Jacobson, V., McGregor, A., Ed., and J.
Iyengar, Ed., "Controlled Delay Active Queue Management",
RFC 8289, DOI 10.17487/RFC 8289, January 2018,
<https://www.rfc-editor.org/info/RFC 8289>.
10.2. Informative References
[BLOAT] Gettys, J. and K. Nichols, "Bufferbloat: Dark Buffers in
the Internet", Communications of the ACM, Volume 55, Issue
1, DOI 10.1145/2063176.2063196, January 2012.
[BLOATWEB] "Bufferbloat", <https://www.bufferbloat.net>.
[BQL] Herbert, T., "bql: Byte Queue Limits", August 2011,
<https://lwn.net/Articles/454378/>.
[CAKE] "Cake - Common Applications Kept Enhanced",
<http://www.bufferbloat.net/projects/codel/wiki/Cake>.
Hoeiland-Joergensen, et al. Experimental PAGE 21
RFC 8290 FQ-CoDel January 2018
[CODEL] Nichols, K. and V. Jacobson, "Controlling Queue Delay",
ACM Queue, Volume 10, Issue 5,
DOI 10.1145/2208917.2209336, May 2012,
<http://queue.acm.org/detail.cfm?id=2209336>.
[DRR] Shreedhar, M. and G. Varghese, "Efficient Fair Queueing
Using Deficit Round Robin", IEEE/ACM Transactions on
Networking, Volume 4, Issue 3, DOI 10.1109/90.502236, June
1996.
[DRRPP] MacGregor, M. and W. Shi, "Deficits for Bursty Latency-
Critical Flows: DRR++", Proceedings of the IEEE
International Conference on Networks 2000 (ICON 2000),
DOI 10.1109/ICON.2000.875803, September 2000,
<http://ieeexplore.ieee.org/xpls/
abs_all.jsp?arnumber=875803>.
[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", Elsevier Computer
Networks, Volume 65, DOI 10.1016/j.bjp.2014.01.009, June
2014, <https://www.sciencedirect.com/science/article/pii/
S1389128614000188>.
[HFSC] Stoica, I., Zhang, H., and T. Eugene Ng, "A Hierarchical
Fair Service Curve Algorithm for Link-Sharing, Real-Time
and Priority Services", Proceedings of ACM SIGCOMM,
DOI 10.1145/263105.263175, September 1997,
<http://conferences.sigcomm.org/sigcomm/1997/papers/
p011.pdf>.
[HTB] Wikipedia, "Token Bucket: Variations", October 2017,
<https://en.wikipedia.org/w/
index.php?title=Token_bucket&oldid=803574657>.
[JENKINS] Jenkins, B., "A Hash Function for Hash Table Lookup",
<http://www.burtleburtle.net/bob/hash/doobs.html>.
[LINUXSRC] "Linux Kernel Source Tree", <https://git.kernel.org/cgit/l
inux/kernel/git/torvalds/linux.git/tree/net/sched/
sch_fq_codel.c>.
[NS2] "ns-2", December 2014, <http://nsnam.sourceforge.net/wiki/
index.php?title=Main_Page&oldid=8076>.
[NS3] "ns-3", February 2016, <https://www.nsnam.org/mediawiki/
index.php?title=Main_Page&oldid=9883>.
Hoeiland-Joergensen, et al. Experimental PAGE 22
RFC 8290 FQ-CoDel January 2018
[QFQ] Checconi, F., Rizzo, L., and P. Valente, "QFQ: Efficient
Packet Scheduling with Tight Guarantees", IEEE/ACM
Transactions on Networking (TON), Volume 21, Issue 3, pp.
802-816, DOI 10.1109/TNET.2012.2215881, June 2013,
<http://dl.acm.org/citation.cfm?id=2525552>.
[RFC 2003] Perkins, C., "IP Encapsulation within IP", RFC 2003,
DOI 10.17487/RFC 2003, October 1996,
<https://www.rfc-editor.org/info/RFC 2003>.
[RFC 2890] Dommety, G., "Key and Sequence Number Extensions to GRE",
RFC 2890, DOI 10.17487/RFC 2890, September 2000,
<https://www.rfc-editor.org/info/RFC 2890>.
[RFC 3168] Ramakrishnan, K., Floyd, S., and D. Black, "The Addition
of Explicit Congestion Notification (ECN) to IP",
RFC 3168, DOI 10.17487/RFC 3168, September 2001,
<https://www.rfc-editor.org/info/RFC 3168>.
[RFC 4213] Nordmark, E. and R. Gilligan, "Basic Transition Mechanisms
for IPv6 Hosts and Routers", RFC 4213,
DOI 10.17487/RFC 4213, October 2005,
<https://www.rfc-editor.org/info/RFC 4213>.
[RFC 6817] Shalunov, S., Hazel, G., Iyengar, J., and M. Kuehlewind,
"Low Extra Delay Background Transport (LEDBAT)", RFC 6817,
DOI 10.17487/RFC 6817, December 2012,
<https://www.rfc-editor.org/info/RFC 6817>.
[RFC 8257] Bensley, S., Thaler, D., Balasubramanian, P., Eggert, L.,
and G. Judd, "Data Center TCP (DCTCP): TCP Congestion
Control for Data Centers", RFC 8257, DOI 10.17487/RFC 8257,
October 2017, <https://www.rfc-editor.org/info/RFC 8257>.
[SFQ] McKenney, P., "Stochastic Fairness Queueing", Proceedings
of IEEE INFOCOM, DOI 10.1109/INFCOM.1990.91316, June 1990,
<http://perso.telecom-
paristech.fr/~bonald/Publications_files/BMO2011.pdf>.
[SQF] Carofiglio, G. and L. Muscariello, "On the Impact of TCP
and Per-Flow Scheduling on Internet Performance", IEEE/ACM
Transactions on Networking, Volume 20, Issue 2,
DOI 10.1109/TNET.2011.2164553, August 2011.
[WEBRTC-QOS]
Jones, P., Dhesikan, S., Jennings, C., and D. Druta, "DSCP
Packet Markings for WebRTC QoS", Work in Progress,
draft-ietf-tsvwg-rtcweb-qos-18, August 2016.
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RFC 8290 FQ-CoDel January 2018
[WFQ] Demers, A., Keshav, S., and S. Shenker, "Analysis and
Simulation of a Fair Queueing Algorithm", ACM SIGCOMM
Computer Communication Review, Volume 19, Issue 4, pp.
1-12, DOI 10.1145/75247.75248, September 1989,
<http://doi.acm.org/10.1145/75247.75248>.
Acknowledgements
Our deepest thanks to Kathie Nichols, Van Jacobson, and all the
members of the bufferbloat.net effort for all the help on developing
and testing the algorithm. In addition, our thanks to Anil Agarwal
for his help with getting the hash collision probabilities in this
document right.
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Authors' Addresses
Toke Hoeiland-Joergensen
Karlstad University
Dept. of Computer Science
Karlstad 65188
Sweden
Email: toke@toke.dk
Paul McKenney
IBM Linux Technology Center
1385 NW Amberglen Parkway
Hillsboro, OR 97006
United States of America
Email: paulmck@linux.vnet.ibm.com
URI: http://www2.rdrop.com/~paulmck/
Dave Taht
Teklibre
2104 W First street
Apt 2002
FT Myers, FL 33901
United States of America
Email: dave.taht@gmail.com
URI: http://www.teklibre.com/
Jim Gettys
21 Oak Knoll Road
Carlisle, MA 993
United States of America
Email: jg@freedesktop.org
URI: https://en.wikipedia.org/wiki/Jim_Gettys
Eric Dumazet
Google, Inc.
1600 Amphitheatre Pkwy
Mountain View, CA 94043
United States of America
Email: edumazet@gmail.com
Hoeiland-Joergensen, et al. Experimental PAGE 25
RFC TOTAL SIZE: 57767 bytes
PUBLICATION DATE: Saturday, January 6th, 2018
LEGAL RIGHTS: The IETF Trust (see BCP 78)
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