Internet DRAFT - draft-morton-tsvwg-cheap-nasty-queueing
draft-morton-tsvwg-cheap-nasty-queueing
Transport Working Group J. Morton
Internet-Draft P. Heist
Intended status: Informational 4 November 2019
Expires: 7 May 2020
Cheap Nasty Queueing
draft-morton-tsvwg-cheap-nasty-queueing-01
Abstract
This note presents Cheap Nasty Queueing (CNQ), a queueing algorithm
intended as a bare-minimum functionality standard for hardware
implementations. It provides stateless or single-instance AQM and
basic sparse-flow prioritisation.
Status of This Memo
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Table of Contents
1. Introduction . . . . . . . . . . . . . . . . . . . . . . . . 2
2. Background . . . . . . . . . . . . . . . . . . . . . . . . . 2
3. The Algorithm . . . . . . . . . . . . . . . . . . . . . . . . 3
3.1. Overview . . . . . . . . . . . . . . . . . . . . . . . . 3
3.2. Declarations . . . . . . . . . . . . . . . . . . . . . . 4
3.3. Pseudo-code . . . . . . . . . . . . . . . . . . . . . . . 5
4. Security Considerations . . . . . . . . . . . . . . . . . . . 8
5. IANA Considerations . . . . . . . . . . . . . . . . . . . . . 8
6. Informative References . . . . . . . . . . . . . . . . . . . 8
Authors' Addresses . . . . . . . . . . . . . . . . . . . . . . . 9
1. Introduction
Flow isolation is a powerful tool for congestion management in
today's Internet. Unfortunately, the relatively complex algorithms
and considerable dynamic state of a DRR++ queue set with individual
AQM (Active Queue Management) [RFC7567] instances has proved
disheartening to hardware implementors, and thus to deployment on
high-capacity links and in consumer-grade hardware.
This note therefore presents CNQ, a queueing algorithm suitable for
implementation in low-cost hardware, providing the absolute minimum
functionality to improve perceived network performance over that of a
dumb FIFO.
2. Background
CNQ is inspired by DRR++'s facility for identifying "sparse" flows
and giving them strict priority over "saturating" flows. DRR++ does
this by maintaining separate lists of queues (each queue containing
one flow) meeting "sparseness" criteria or not.
Queues are first placed into the sparse list when they become non-
empty, then moved to the saturating list when their deficit exceeds a
threshold called "quantum". Every queue's deficit is incremented by
the packet size when packets are delivered from it, and decremented
by the quantum when they come up in the list rotation. Queues are
removed from the saturating list only when they are found empty for a
full rotation.
This "sparseness" heuristic over observed per-flow queue occupancy
characteristics is relatively robust, compared to relying on the
correct behaviour of each source's congestion control algorithms and/
or explicit traffic marking. This is especially relevant with the
recent development of high-fidelity congestion signalling schemes,
such as DCTCP [RFC8257] and SCE (Some Congestion Experienced), whose
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expected congestion-signal response is markedly different from
previous standards.
In fq_codel [RFC8290] and Cake [CAKE], AQM is applied individually to
each DRR++ flow, thus avoiding unnecessary leakage of AQM action from
flows requiring it to well-behaved traffic which does not. This
arrangement has been shown to work well in practice, and is widely
deployed as part of the Linux kernel, including in many CPE devices.
However the per-queue AQM state dominates the memory requirements of
DRR++.
CNQ attempts to retain some of these characteristics while
simplifying implementation requirements considerably. This still
requires identifying individual traffic flows and keeping some per-
flow state, but there is no longer an individual queue per state nor
any lists of such queues. Instead there are only two queues and at
most one set of AQM state. The operations required are believed to
be amenable to low-cost hardware implementation.
3. The Algorithm
3.1. Overview
Unlike conventional fair queueing, with Cheap Nasty Queueing, packets
are not distributed to queues by a flow mapping, but by a sparseness
metric associated with that mapping. Thus, the number of queues is
reduced to two.
The number of flows which can be handled is far greater, however,
being limited by the number of flow buckets indexed by the flow hash.
An implementation might define a flow as traffic to one subscriber,
and provide a perfect mapping between subscribers and buckets.
Alternatively it might provide a stochastic mapping based on the
traditional 5-tuple of addresses, port numbers, and protocol number.
The latter would be appropriate for low-cost consumer hardware, in
which the notion of a "subscriber" is neither well-defined nor
useful.
The per-flow state is just one unsigned integer, in contrast to DRR++
which requires a whole queue and a set of AQM state per flow. This
integer is B, tracking the backlog of the flow in packets. This
small per-flow state makes tracking a large number of flows
practical.
The two queues provided are SQ and BQ:
SQ is the "sparse queue" which handles flows classed as sparse,
including the first packets in newly active flows. This queue tends
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to remain short and drain quickly, which are ideal characteristics
for latency-sensitive traffic, and young flows still establishing
connections or probing for capacity. This queue does not maintain
AQM state nor apply AQM signals, and will contain at most one packet
from each flow at any one time.
BQ is the "bulk queue" which handles all traffic not classed as
sparse, including at least the second and subsequent packets in a
burst. An AQM algorithm is applied to all traffic delivered from it.
To prevent well-paced traffic from dominating the queue by keeping
exactly one packet in SQ at all times, a dummy packet is sent into BQ
in parallel with every packet enqueued in SQ, and the B value for the
flow effectively tracks the number of packets (including dummies) in
BQ. A flow is therefore considered sparse IFF the interval between
its packets is longer than the sojourn time of packets in BQ. This
can be a much stricter criterion than for true derivatives of DRR++
such as LFQ.
The maximum throughput of a sparse flow is thus defined by the size
of the packets composing that flow, divided by the sojourn time of
BQ, under the assumption that the flow is well paced. For a typical
example where the packet size is 1500 bytes and the sojourn time of
BQ is controlled to 5ms by Codel AQM action, flows of up to about
2.5Mbps throughput may be treated as sparse.
In case of queue overflow, packets are removed from the "head" of BQ
to make room for the new arrivals; this head-dropping behaviour
minimises the delay before the lost packets can be retransmitted.
This simplification of state and algorithm has some drawbacks in
terms of resultant behaviour compared to DRR++. The sharing of link
capacity between flows is dependent mainly on the RTT-fair properties
of the flows' own congestion control, in response to congestion
signalling from the single AQM. However, this should be seen as an
improvement in performance for sparse flows as compared to a plain
FIFO queue.
3.2. Declarations
The following queues are defined:
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-------------------------------
--> | | | | -->
-------------------------------
SQ: the Sparse Queue, containing packets from flows with no more
than one packet in the queue at a time (no AQM for this queue).
-------------------------------
--> | | | | | | | | | | | -->
-------------------------------
BQ: the Bulk Queue, containing packets from flows that build up a
multi-packet backlog (AQM managed queue).
The following constants and variables are defined:
* B: the flow backlog, in packets
* N: the number of flow buckets (each bucket containing a value of
B)
* S: the size of a packet
* T: the packet's timestamp, for later use by AQM
* H: the packet's flow hash, cached
* MAXSIZE: the maximum size for all packets in the queue
* NOW: the current timestamp
Finally, the hash function FH() maps a packet to a flow bucket:
+---+
/--- | B |
/ +---+
/
+------+ / +---+
----- Packet -----> | FH() | ------- | B |
+------+ \ +---+
\
\
\--- ... N
3.3. Pseudo-code
In the following pseudo-code:
* Lowercase is used for internal variables, and uppercase for
constants, variables and queues defined in Section 3.2.
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* The send() function transmits the packet.
* The aqm_action() function updates the AQM state (if any) based on
the current sojourn time, and returns an action code indicating
whether a CE or SCE mark (or no mark) should be applied. This
function may be stateless and merely return results from a
threshold function or probability ramp, or it may implement Codel
or similar stateful AQMs, or a hybrid of the two for separate CE
and SCE marking strategies.
The following functions and variables are defined for both the sparse
and bulk queues:
* The push() function adds a packet to the tail of the specified
queue.
* The pop() function removes and returns the packet from the head of
the specified queue.
* The .size variable (BQ.size and SQ.size) refers to the sum of the
sizes of all packets in the queue, and may be maintained during
push(), pop().
* The .head variable is the current head pointer for the queue.
The logic for the enqueue operation is as follows:
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enqueue(packet p) {
while (SQ.size + BQ.size + S > MAXSIZE) {
; Queue overflow - drop from BQ head, then from SQ
dp := pop(BQ)
if (!dp)
dp := pop(SQ)
bkt := dp.H
bkt.B -= 1
}
bkt := FH(p)
p.T = NOW
p.H = bkt
if (bkt.B == 0) {
push(SQ, p)
dp := zero-length dummy packet
dp.T = NOW
dp.H = bkt
push(BQ, dp)
bkt.B += 2
} else {
push(BQ, p)
bkt.B += 1
}
}
The logic for the dequeue operation is as follows:
dequeue() {
; SQ gets strict priority
p := pop(SQ)
if (p) {
send(p)
bkt := p.H
bkt.B -= 1
return
}
; Process BQ if SQ was empty
repeat {
p := pop(BQ)
if (!p) {
; Queue is empty
return
}
bkt := p.H
bkt.B -= 1
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if (p.S == 0) {
; Dummy packet for sparseness metric - drop
continue
}
; Apply AQM logic based on sojourn time
t := NOW - p.T
; drop unresponsive traffic
if (t > 500ms)
continue
switch(aqm_action(t)) {
case MARK_CE:
; legacy congestion signalling
if (t.ECN == Not-ECT)
continue
; RFC-3168
if (t.ECN == ECT || t.ECN == SCE)
t.ECN = CE ; and update IP header checksum
break
case MARK_SCE:
; Some Congestion Experienced
if (t.ECN == ECT)
t.ECN = SCE ; and update IP header checksum
break
default:
; no marking request
break
}
send(p)
return
}
}
4. Security Considerations
This is a very weak FQ algorithm, not much better than a dumb FIFO -
but still better.
5. IANA Considerations
There are no IANA considerations.
6. Informative References
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[CAKE] Hoiland-Jorgensen, T., Taht, D., and J. Morton, "Piece of
CAKE: A Comprehensive Queue Management Solution for Home
Gateways", May 2018, <https://arxiv.org/abs/1804.07617>.
[RFC7567] Baker, F., Ed. and G. Fairhurst, Ed., "IETF
Recommendations Regarding Active Queue Management",
BCP 197, RFC 7567, DOI 10.17487/RFC7567, July 2015,
<https://www.rfc-editor.org/info/rfc7567>.
[RFC8257] 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/RFC8257,
October 2017, <https://www.rfc-editor.org/info/rfc8257>.
[RFC8290] Hoeiland-Joergensen, T., McKenney, P., Taht, D., Gettys,
J., and E. Dumazet, "The Flow Queue CoDel Packet Scheduler
and Active Queue Management Algorithm", RFC 8290,
DOI 10.17487/RFC8290, January 2018,
<https://www.rfc-editor.org/info/rfc8290>.
Authors' Addresses
Jonathan Morton
Kokkonranta 21
FI-31520 Pitkajarvi
Finland
Phone: +358 44 927 2377
Email: chromatix99@gmail.com
Peter G. Heist
Redacted
463 11 Liberec 30
Czech Republic
Email: pete@heistp.net
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