Transport Area Working Group B. Briscoe
Internet-Draft BT & UCL
Intended status: Informational T. Moncaster
Expires: May 15, 2008 L. Burness
BT
November 12, 2007
Problem Statement: We Don't Have To Do Fairness Ourselves
draft-briscoe-tsvwg-relax-fairness-00
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Abstract
Nowadays resource sharing on the Internet is largely a result of what
applications, users and operators do at run-time, rather than what
the IETF designs into transport protocols at design-time. The IETF
now needs to recognise this trend and consider how to allow resource
sharing to be properly controlled at run-time.
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Requirements Language
The key words "MUST", "MUST NOT", "REQUIRED", "SHALL", "SHALL NOT",
"SHOULD", "SHOULD NOT", "RECOMMENDED", "MAY", and "OPTIONAL" in this
document are to be interpreted as described in [RFC2119].
Table of Contents
1. Introduction . . . . . . . . . . . . . . . . . . . . . . . . . 3
2. What Problem? . . . . . . . . . . . . . . . . . . . . . . . . 4
2.1. Two Incompatible Partial Worldviews . . . . . . . . . . . 4
2.1.1. Overlooked Degrees of Freedom . . . . . . . . . . . . 7
2.2. Average Rates are a Run-Time Issue . . . . . . . . . . . . 8
2.3. Protocol Dynamics is the Design-Time Issue . . . . . . . . 9
3. Concrete Consequences of Unfairness . . . . . . . . . . . . . 10
3.1. Higher Investment Risk . . . . . . . . . . . . . . . . . . 11
3.2. Losing Voluntarism . . . . . . . . . . . . . . . . . . . . 12
3.3. Networks using DPI to make Choices for Users . . . . . . . 13
3.4. Starvation during Anomalies and Emergencies . . . . . . . 14
4. Security Considerations . . . . . . . . . . . . . . . . . . . 15
5. Conclusions . . . . . . . . . . . . . . . . . . . . . . . . . 15
6. Acknowledgements . . . . . . . . . . . . . . . . . . . . . . . 15
7. Comments Solicited . . . . . . . . . . . . . . . . . . . . . . 15
8. References . . . . . . . . . . . . . . . . . . . . . . . . . . 15
8.1. Normative References . . . . . . . . . . . . . . . . . . . 15
8.2. Informative References . . . . . . . . . . . . . . . . . . 16
Editorial Comments . . . . . . . . . . . . . . . . . . . . . . . .
Appendix A. Example Scenario . . . . . . . . . . . . . . . . . . 19
A.1. Base Scenario . . . . . . . . . . . . . . . . . . . . . . 19
A.2. Compounding Overlooked Degrees of Freedom . . . . . . . . 20
A.3. Hybrid Users . . . . . . . . . . . . . . . . . . . . . . . 21
A.4. Upgrading Makes Most Users Worse Off . . . . . . . . . . . 21
Authors' Addresses . . . . . . . . . . . . . . . . . . . . . . . . 23
Intellectual Property and Copyright Statements . . . . . . . . . . 25
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1. Introduction
The strength of the Internet is that any of the thousand million or
so hosts may use nearly any network resource on the whole public
Internet without asking, whether in access or core networks, wireless
or fixed, local or remote. The question of how each resource is
shared is generally delegated to the congestion control algorithms
available on each endpoint, most often TCP.
We (the IETF) aim to ensure reasonably fair sharing of the congested
resources of the Internet [RFC2914]. Specifically, the TCP algorithm
aims to ensure every flow gets a roughly equal share of each
bottleneck, measured in packets per round trip time [RFC2581]. But
our efforts have become distorted by unfair use of protocols we
intended to be fair, and further by the attempts of operators to
correct the situation. The problem is we aim to control fairness at
protocol design-time, but resource shares are now primarily
determined at run-time--as the outcome of a tussle between users, app
developers and operators.
For instance, about 35% of total traffic currently seen (Sep'07) at a
core node on the public wireline Internet is p2p file-sharing {ToDo:
Add ref}. Even though file-sharing generally uses TCP, it uses the
well-known trick of opening multiple connections--currently around
100 actively transferring over different paths is not uncommon. A
competing Web application might open a couple of flows at a time, but
perhaps only actively transfer data 1-10% of the time (its activity
factor). Combining 50x less flows and 10-100x lower activity factor
means the traffic intensity from the Web app can be 500-5,000x less.
However, despite being so much lighter on the network, it gets 50x
less bit rate through the bottleneck.
The design-time approach worked well enough during the early days of
the Internet, because most users' activity factors and numbers of
flows were in proportion to their access link rate. But, now the
Internet has to support a jostling mix of different attitudes to
resource sharing: carelessness, unwitting self-interest, active self-
interest, malice and sometimes even a little consideration for
others. So although TCP sets an important baseline, it is no longer
the main determinant of how resources are shared between users at
run-time.
Just because we can no longer control resource sharing at design
time, we aren't saying it isn't important. In Section 3, we show
that badly skewed resource sharing has serious concrete knock-on
effects that are of great concern to the health of the Internet.
And we are not saying the IETF is powerless to do anything to help.
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However, our role must now be to create the run-time _policy
framework_ within which users and operators can control relative
resource shares. So the debate is not about the IETF choosing
between TCP-friendliness, max-min fairness, cost fairness or any
other sort of fairness, because whatever we decide at design-time
won't be strong enough to change what happens at run-time. We need
to focus on giving principled and enforceable control to users and
operators, so they can agree between themselves which fair use policy
they want locally [Rate_fair_Dis].
The requirements for this resource sharing framework will be the
subject of a future document, but the most important role of the IETF
is to promote _understanding_ of the sorts of resource sharing that
users and operators will want to use at run-time and to resolve the
misconceptions and differences between them (Section 2.1).
We are in an era where new congestion control requirements often
involve starting more aggressively than TCP or going faster than TCP,
or not responding to congestion as quickly as TCP. By shifting
control of fairness from design to run-time, we will free up all our
new congestion control design work, so that it can first and foremost
meet the objectives of these more demanding applications. But we can
still quantify, minimise and constrain the effect on others due to
faster average rate and different dynamics (Section 2.3). We can say
now that the framework will have to encompass and endorse the
practice of opening multiple flows, for instance. But alongside
recognition of such freedoms will come constraints, in order to
balance the side-effects on other users over time.
2. What Problem?
2.1. Two Incompatible Partial Worldviews
When looking at the current Internet, some people see a massive
fairness problem, while others think there's hardly a problem at all.
This is because two divergent ways of reasoning about resource
sharing have developed in the industry:
o IETF guidelines on fair sharing of congested resources
[RFC2357],[RFC2309],[RFC2914] have recommended that flows
experiencing the same congested path should aim to achieve broadly
equal window sizes, as TCP does [RFC2581]. We will characterise
this as the "flow rate equality" worldview, shared by the IETF and
large parts of the networking research community.[Note_Window]
o Network operators and Internet users tend to reason about the
problem of resources sharing very differently. Nowadays they do
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not generally concern themselves with the rates of individual
flows. Instead they think in terms of the volume of data that
different users transfer over a period [Res_p2p]. We will term
this the "volume accounting" worldview. They do not believe
volume over a period (traffic intensity) is a measure of
unfairness in itself, but they believe it should be _taken into
account_ when deciding whether relative bit rates are fair.
The most obvious distinction between the two worldviews is that flow
rate equality is between _flows_, whereas volume accounting shares
resources between _users_. The IETF understands well that fairness
is actually between users, but generally considers flow fairness to
be a reasonable approximation as long as users aren't opening too
many flows.
However, there is a second much more subtle distinction. The flow
rate equality worldview discusses fair resource sharing in terms of
bit rates, but operators and users reason about fair bit rates in the
context of byte volume over a period. Given bit rate is an
instantaneous metric, it may aid understanding to convert 'volume
over a period' into an instantaneous metric too. The relevant metric
is traffic intensity, which like traffic rate is an instantaneous
metric, but it takes account of likely activity _over time_. The
traffic intensity from one user is the product of two metrics: i) the
user's desired bit rate when active and ii) how often they are active
over a period (their activity factor).
Operators have to provision capacity based on the aggregate traffic
intensity from all users over the busy period. And many users think
in terms of how much volume they can transfer over a period. So,
because traffic intensity is equivalent to 'volume over a period',
both operators and users often effectively share the same worldview.
To further aid understanding, Appendix A presents an example scenario
where heavy users compete for a bottleneck with light users. It has
enough similarities to the current Internet to be relevant, but it
has been stripped to its bare essentials to allow the main issues to
be grasped.
The base scenario in Appendix A.1 starts with the light users having
TCP connections open for less of the time than heavy users (a lower
activity factor). But, when they are active, they open as many
connections as heavy users. It shows that users with a lower
activity factor transfer less volume of traffic through the
bottleneck over a period because, even though TCP gives roughly equal
rate to each flow, the heavy users' flows are present more of the
time.
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The volume accounting view is _not_ that it is unfair for some users
to transfer more volume than others--afterall the lighter users have
less traffic that they want to send. However, they believe it is
reasonable for users who put a heavier load on the system to be given
less bottleneck bit rate than lighter users.
Appendix A.2 continues the example, giving the heavy users the added
advantage of using 50x multiple flows, just as they do on the current
Internet. When multiple flows are compounded with their higher
activity factors, they can get 500-2,000x greater traffic intensity
through the bottleneck.
Certainly, the flow rate equality worldview recognises that opening
50x more flows than other users starts to become a serious fairness
problem, because some users get 50x more bit rate through a
bottleneck than others. But the volume accounting worldview sees
this as a much bigger problem. They first see 2,000x heavier use of
the bottleneck over time, then they judge that _also_ getting 50x
greater bit rate seems seriously unfair.
But are these numbers realistic? Attended use of something like the
Web might typically have an activity factor of 1-10%, while
unattended apps approach 100%. A Web browser might typically open
two TCPs when active [RFC2616], while a p2p file-sharing app on a
512kbps upstream DSL line actively uses anything from 40-500
connections [az-calc]. Heavy users generally compound the two
factors together (10-100x greater activity factor and 20-250x more
connections), achieving anything from 200x to 25,000x greater traffic
intensity through a bottleneck than light users.
The above question of what size the different worldviews think
resource shares _should_ be is separate from the question of whether
to _enforce_ them and how to (see Section 3.2). Within the volume
accounting worldview, many operators (particularly in Europe) already
limit the bit rate of their heaviest users at peak times in order to
protect the experience of the majority of their
customers.[Note_Neutral] But, enforcement is a separate question.
Although prevalent use of TCP seems to be continuing without any
enforcement, even the flow rate equality worldview generally accepts
that opening excessive multiple connections can't be solved
voluntarily. Quoting RFC2914, "...instead of a spiral of
increasingly aggressive transport protocols, we ... have a spiral of
increasingly ... aggressive applications").
To summarise so far, one industry worldview aims for equal flow
rates, while the other prefers an outcome with very unequal flow
rates. Even though they both share the same intentions of fairer
resource sharing, the two worldviews have developed subgoals that are
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fundamentally at odds.
2.1.1. Overlooked Degrees of Freedom
So which worldview is correct? Actually, our reason for pointing out
these divergent worldviews is to show that both contain valuable
insights, but that each also highlights weaknesses in the other.
Given our audience is the IETF, we have tried to explain the volume
accounting worldview in terms of flow rate equality, but volume
accounting is by no means rigorous or complete itself. Table 1
identifies the three degrees of freedom of resource sharing that are
missing in one or the other of the two worldviews.
+----------------------+--------------------+-------------------+
| Degree of Freedom | Flow Rate Equality | Volume Accounting |
+----------------------+--------------------+-------------------+
| Activity factor | X | Y |
| Multiple flows | X | Y |
| Congestion variation | Y | X |
+----------------------+--------------------+-------------------+
Table 1: Resource Sharing Degrees of Freedom Encompassed by Different
Worldviews; Y = yes and X = no.
Activity factor: We have already pointed out how flow rate equality
does not take different activity factors into account. On the
other hand, volume accounting naturally takes the on-off activity
of flows into account, because in the process of counting volume
over time, the off periods are naturally excluded.
Multiple flows: Similarly, it is well-known [RFC2309] [RFC2914] that
flow rate equality does not make allowance for multiple flows,
whereas counting volume naturally includes all flows from a user,
whether they terminate at the same remote endpoint or many
different ones.
Congestion variation: Flow rate equality, of course, takes full
account of how congested different bottlenecks are at different
times, ensuring that the same volume must be squeezed out over a
longer duration, the more flows it competes with. However, volume
accounting doesn't recognise that congestion can vary by orders of
magnitude, making it fairly useless for encouraging congestion
control. The best it can do is only count volume during a 'peak
period', effectively considering congestion as either 1 everywhere
during this time or 0 everywhere otherwise.
These clearly aren't just problems of detail. Having each overlooked
whole dimensions of the problem, both worldviews seem to require a
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fundamental rethink. In a future document defining the requirements
for a new resource sharing framework, we plan to unify both
worldviews. But, in the present problem statement, it is sufficient
to register that we need to reconcile the fundamentally contradictory
worldviews that the industry has developed about resource sharing.
2.2. Average Rates are a Run-Time Issue
A less obvious difference between the two worldviews is that flow
rate equality tries to control resource shares at design-time, while
volume accounting controls resource shares once the run-time
situation is known. Also the volume accounting worldview actually
involves two separate functions: passive monitoring and active
intervention. So, importantly, the run-time questions of whether to
and how to intervene can depend on policy.
The "spiral of increasingly aggressive applications" [RFC2914] has
shifted the resource sharing problem out of the IETF's design-time
space, making flow rate equality insufficient (or perhaps even
inappropriate) in technical and in policy terms:
Technical: At design time, it is impossible to know whether a
congestion control will be fair at run-time without knowing more
about the run-time situation it will be used in--how long flow
durations will be and whether users will open multiple flows.
Policy: At design time, we cannot (and should not) prejudge the
'fair use' policy that has been agreed between users and their
network operators.
A transport protocol can no longer be made 'fair' at design time--it
all now depends how 'unfairly' it is used at run-time, and what has
been agreed as 'unfair'.
However, we are not saying that volume accounting is the answer. It
just gives us the insight that resource sharing has to be controlled
at run-time by policy, not at design-time by the IETF. Volume
accounting would be more useful if it took a more precise approach to
congestion than either 'everything is congested' or 'nothing is
congested'.
What operators and users need from the IETF is a framework to judge
and to control resource sharing at run-time. It needs to work across
all a user's flows (like volume accounting). It needs to take
account of idle periods over time (like volume accounting). And it
needs to take account of congestion variation (like flow rate
equality).
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2.3. Protocol Dynamics is the Design-Time Issue
Although fairness is a run-time issue, at protocol design-time it
requires more from the IETF than just a policy control framework.
Policy can control the _average_ amount of congestion that a
particular application causes, but the Internet also needs the
collective expertise of the IETF and the IRTF to standardise best
practice in the _dynamics_ of transport protocols. The IETF has a
duty to provide standard transports with a response to congestion
that is always safe and robust. But the hard part is to keep the
network safe while still meeting the needs of more demanding
applications (e.g. high speed transfer of data objects or media
streaming that can adapt its rate but not too abruptly).
If we assume for a moment that we will have a framework to judge and
control _average_ rates, we will still need a framework to assess
which proposed congestion controls make the trade-off between
achieving the task effectively and minimising congestion caused to
others, during _dynamics_:
o The faster a new flow accelerates the more packets it will have in
flight when it detects its first loss, potentially leading many
other flows to experience a long burst of losses as queues
overrun. When is a fast start fast enough? Or too fast
[RFC3742]?
o One way for a small number of high speed flows to better utilise a
high speed link is to respond more smoothly to congestion events
than TCP's rate-halving saw-tooth does [proprietary fast TCPs]
[FAST],[RFC3649]. But then new flows will take much longer to
'push-in' and reach a high rate themselves.
o Transports like TCP-friendly rate control [proprietary media
players], [RFC3448], [RFC4828] are designed to respond more
smoothly to congestion than TCP. But even if a TFRC flow has the
same average bit rate as a TCP flow, the more sluggish it is, the
more congestion it will cause [Rate_fair_Dis]. How do we decide
how much smoother we should go? How large a proportion of
Internet traffic could we allow to be unresponsive to congestion
over long durations, before we were at risk of causing growing
periods of congestion collapse [RFC2914]?[Note_Collapse]
o TFRC has been proposed as a possible way for aggregates of flows
crossing the public Internet to respond to congestion (pseudo-wire
emulations may contain flows that cannot, or do not want to
respond quickly to congestion themselves)
[I-D.rosen-pwe3-congestion],
[I-D.ietf-capwap-protocol-specification], [TSV_CAPWAP_issues].
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But it doesn't make any sense to insist that, wherever flows are
aggregated together into one identifiable bundle, the whole bundle
of perhaps hundreds of flows must keep to the same mean rate as a
single TCP flow.
In view of the continual demand for alternate congestion controls,
the IETF has recently agreed a new process for standardising them
[ion-tsv-alt-cc]. The IETF will use the expertise of the IRTF
Internet congestion control research group, governed by agreed
general guidelines for the design of new congestion controls
[RFC5033]. However, in writing those guidelines it proved very
difficult to give any specific guidance on where a line could be
drawn between fair and unfair protocols. The best we could do were
phrases like, "Alternate congestion controllers that have a
significantly negative impact on traffic using standard congestion
control may be suspect..." and "In environments with multiple
competing flows all using the same alternate congestion control
algorithm, the proposal should explore how bandwidth is shared among
the competing flows."
Once we have agreed that average behaviour should be a policy issue,
we can focus on the dynamic behaviour of congestion controls, which
is where the important standards issues lie, such as preventing
congestion collapse or preventing new flows causing bursts of
congestion by unnecessarily overrunning as they seek out the
operating point of their path.
As always, the IETF will not want to standardise aspects where
implementers can gain an edge over their competitors, but we must set
standards to prevent serious harm to the stability and usefulness of
the Internet, and to make transports available that avoid causing
_unnecessary_ congestion in the course of achieving any particular
application objective.
3. Concrete Consequences of Unfairness
People have different levels of tolerance for unfairness. Even when
we agree how to measure fairness, there are a range of views on how
unfair the situation needs to get before the IETF should do anything
about it. Nonetheless, lack of fairness can lead to more concretely
pathological knock-on effects. Even if we don't particularly care if
some users get more than their fair share and others less, we should
care about the more concrete knock-on effects below.
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3.1. Higher Investment Risk
Some users want more Internet capacity to transfer large volumes of
data, while others want more capacity to be able to interact more
quickly with other sites and other users. We have called these heavy
and light users, although of course, many users are mix of the two in
differing proportions.
We have shown that heavy users can use applications that open
multiple connections, so that TCP gives the light users very little
of a bottleneck. But unfortunately, upgrading capacity does little
for the light users unless the heavy users run out of data to send
(which doesn't tend to happen often). In the reasonably realistic
example in Appendix A.4, the light users start off only being able to
use 10kbps of their 2Mbps line because heavy users are skewing the
sharing of the bottleneck by using multiple flows. But a 4x upgrade
to the bottleneck, which should add 500kbps per user if shared
equally, only gives the light users 30kbps extra.
But, the upgrade has to be paid for. A commercial ISP will generally
pass on the cost equally to all its customers through its monthly
fees. So, to rub salt in the wound, the light users end up paying
the cost of this 500kbps upgrade but we have seen they only get
30kbps. Ultimately, extreme unfairness in the sharing of capacity
tends to drive operators to stop investing in capacity. Because all
the light users, who experience so little of the benefit, won't be
prepared to pay an equal share to recover the costs--the ISP risks
losing them to a 'fairer' competitor.
But there seems to be plenty of evidence that operators around the
world are still investing in capacity growth despite the prevalence
of TCP. How can this be, if flow rate equality makes investment so
risky? One explanation, particularly in parts of Asia, is that some
investments are Governernment subsidised. In the US, the explanation
is probably more down to weak competition. In Europe, the main
explanation is that many commercial operators haven't allowed their
networks to become as unfair as the above example--they have made
resource sharing fairer by _overriding_ TCP's flow rate equality.
Competitive operators in many countries limit the volume transferred
by heavy users, particularly at peak times. They have effectively
overriden flow rate equality to achieve a different allocation of
resources that they believe is better for the majority of their
customers (and consequently better for their competitive position).
Typically these operators use a combination of tiered pricing of
volume caps and throttling of the heaviest so-called 'unlimited'
users at peak times. In this way they have removed some of the
investment risk that would otherwise have resulted if flow rate
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equality had been relied on to share congested resources.
3.2. Losing Voluntarism
Throughout the early years of the Internet, flow rate equality
resulted in approximate fairness that most people considered
sufficient. This was because most users' traffic during peak hours
tended to correlate with their access rate. Those who bought high
capacity access also generally sent more traffic at peak times (e.g.
heavy users or server farms).
As higher access rates have become more affordable, this happy
coincidence has been eroded. Some people only require their higher
access rate occasionally, while others require it more continuously.
But once they all have more access capacity, even those who don't
really require it all the time often fill it anyway--as long as
there's nothing to dissuade them. People tend to use what they
desire, not just what they require.
Of course, more access traffic requires more shared capacity at
relevant network bottlenecks. But if we rely on TCP to share out
these bottlenecks, we have seen how those who just desire more can
swamp those who require more (Section 3.1).
Some operators have continued to provision sufficiently excessive
shared capacity and just passed the cost on to all their customers.
But many operators have found that those customers who don't actually
require all that shared infrastructure would rather not have to pay
towards its cost. So, to avoid losing customers, they have
introduced tiered volume limits (this hasn't happened in the US yet
though). It is well known that many users are averse to
unpredictable charges [PMP] (S.5), so many now choose ISPs who limit
their volume (with suitable override facilities) rather than charge
more when they use more.
Thus, we are seeing a move away from voluntary restraint (within peak
access rates) towards a preference for enforced fairness, as long as
the user stays in overall control. This has implications on the
Internet infrastructure that the IETF needs to recognise and address.
Effectively, parts of the best effort Internet are becoming like the
other Diffserv classes, with traffic policers and traffic
conditioning agreements (TCAs [RFC2475]), albeit volume-based rather
than rate and burst-based TCAs. (In fact, the addition of congestion
accounting or policing need not be confined to just the best effort
class.)
We are not saying that the Internet _requires_ fairness enforcement,
merely that it has become prevalent. We need to acknowledge the
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trend towards enforcement to ensure that it does not introduce
unnecessary complexity into the basic functioning of the Internet,
and that our current approach to fairness (embedded in endpoint
congestion control) remains compatible with this changing world. For
instance, when a rate policer introduces drops, are they equivalent
to drops due to congestion? are they equivalent to drops when you
exceed your own access rate? do we need to tell the difference?
3.3. Networks using DPI to make Choices for Users
We have seen how network operators might well believe it is in their
customers' interests to override the resource sharing decisions of
TCP. They seem to have sound reasons for throttling their heaviest
users at peak times. But this is leading to a far more controversial
side-effect: network operators have started making performance
choices between _applications_ on behalf of their customers.
Once operators start throttling heavy users, they hit a problem.
Most heavy volume users are actually a mix of the two types
characterised in our example scenario (Appendix A). Some of their
traffic is attended and some is unattended. If the operator
throttles all traffic from a heavy user indiscriminately, it will
severely degrade the customer's attended applications, but it
actually only needs to throttle the unattended applications to
protect the traffic of others.
Ideally, the threat of heavy throttling of all a user's traffic would
encourage the user to self-throttle the traffic she least valued, in
order to avoid the operator's indiscriminate throttling. But many
users these days have neither the expertise nor the software to do
this. Instead, operators have generally decided to infer what they
think the user would do, using readily available deep packet
inspection (DPI) equipment.
An operator may infer customer priorities with honourable intentions,
but such activity is easily confusible with attempts to discriminate
against certain applications that the operator happens not to like.
Also customers get understandably upset every time the operator
guesses their priorities wrongly.
It is well documented (but less well-known) that user priorities are
task-specific, not application-specific [AppVsTask]. P2p filesharing
can be used for downloading music with some vague intent to listen to
it some day soon, or to download a critical security patch. User
intent cannot be inferred at the network layer just by working out
what the application is. The end-to-end design principle [RFC1958]
warns that a function should only be implemented at a lower layer
after trying really hard to implement it at a higher layer.
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Otherwise, the network layer gradually becomes specialised around the
functions and priorities of the moment--the middlebox problem
[RFC3234].
To address this problem of feature creep into the network layer, we
need to understand whether there are valid reasons why this DPI is
being deployed to override TCP's decisions. We shouldn't deny the
existence of a problem just because one solution to it breaks a
fundamental Internet design principle. We should instead find a
better solution.
3.4. Starvation during Anomalies and Emergencies
The problems due to unfairness that we have outlined so far all arise
when the Internet is working normally. However, fairness concerns
become far more acute when a part of the Internet infrastructure
becomes extremely stressed, either because there's much more traffic
than expected (e.g. flash crowds), or much less capacity than
expected (e.g. physical attack, accident, disaster).
Under non-disaster conditions, we have already said that fair sharing
of congested resources is a matter that should be decided between
users and their providers at run-time. Often that will mean "you get
what you've paid for" becomes the rule, at least in commercial parts
of the Internet. But during really acute emergencies many people
would expect such commercial concerns to be set aside
[I-D.floyd-tsvwg-besteffort].
We agree that users shouldn't be able to squeeze out others during
emergencies. But the mechanisms we have in place at the moment don't
allow anyone to control whether this happens or not, because they can
be overriden at run-time by using the extra degress of freedom
available to get round TCP. It could equally be argued that each
user (not each flow) should get an equal share of remaining capacity
in an emergency. Indeed, it would seem wrong for one user to expect
100 continuously running flows downloading music & videos to take 100
times more capacity than other users sending brief flows containing
messages trying to contact loved ones or the emergency services
[Hengchun_quake].[Note_Earthquake]
We argue that fairness during emergencies is, more than anything
else, a policy matter to be decided at run-time (either before or
during an anomaly) by users, operators, regulators and governments--
not at design time by the IETF. The IETF should however provide the
framework within which typical policies can be enforced. And the
IETF should ensure that the Internet is still likely to utilise
resources _efficiently_ under extreme stress, assuming a reasonable
mix of likely policies, including none.
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The main take-away point from this section is that the IETF should
not, and need not, make such life-and-death decisions. It should
provide protocols that allow any of these policy options to be chosen
at the time of need or by making contingencies beforehand. The
congestion accountability framework in {ToDo: ref sister doc}
provides such control, while also allowing different controls
(including no control at all) in normal circumstances. For instance
an ISP might normally allow its customers to pay to override any
usage limits. But during a disaster it might suspend this right.
Then users would get only the shares they had established before the
disaster broke out (the ISP would thus also avoid accusations of
profiteering from people's misery). Whatever, it is not for the IETF
to embed answers to questions like these in our protocols.
4. Security Considerations
{ToDo:}
5. Conclusions
{ToDo:}
6. Acknowledgements
Arnaud Jacquet, Phil Eardley.
7. Comments Solicited
Comments and questions are encouraged and very welcome. They can be
addressed to the IETF Transport Area working group mailing list
<tsvwg@ietf.org>, and/or to the authors.
8. References
8.1. Normative References
[RFC2119] Bradner, S., "Key words for use in RFCs to Indicate
Requirement Levels", BCP 14, RFC 2119, March 1997.
[RFC2309] Braden, B., Clark, D., Crowcroft, J., Davie, B., Deering,
S., Estrin, D., Floyd, S., Jacobson, V., Minshall, G.,
Partridge, C., Peterson, L., Ramakrishnan, K., Shenker,
S., Wroclawski, J., and L. Zhang, "Recommendations on
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Queue Management and Congestion Avoidance in the
Internet", RFC 2309, April 1998.
[RFC2581] Allman, M., Paxson, V., and W. Stevens, "TCP Congestion
Control", RFC 2581, April 1999.
[RFC2914] Floyd, S., "Congestion Control Principles", BCP 41,
RFC 2914, September 2000.
8.2. Informative References
[AppVsTask]
Bouch, A., Sasse, M., and H. DeMeer, "Of packets and
people: A user-centred approach to Quality of Service",
Proc. IEEE/IFIP Proc. International Workshop on QoS
(IWQoS'00) , May 2000,
<http://www.cs.ucl.ac.uk/staff/A.Bouch/42-171796908.ps>.
[FAST] Jin, C., Wei, D., and S. Low, "FAST TCP: Motivation,
Architecture, Algorithms, and Performance", Proc. IEEE
Conference on Computer Communications (Infocom'04) ,
March 2004,
<http://www.ieee-infocom.org/2004/Papers/52_2.PDF>.
[Hengchun_quake]
Wikipedia, "2006 Hengchun earthquake", Wikipedia Web page
(accessed Oct'07) , 2006,
<http://en.wikipedia.org/wiki/2006_Hengchun_earthquake>.
[I-D.floyd-tsvwg-besteffort]
Floyd, S. and M. Allman, "Comments on the Usefulness of
Simple Best-Effort Traffic",
draft-floyd-tsvwg-besteffort-01 (work in progress),
August 2007.
[I-D.ietf-capwap-protocol-specification]
Calhoun, P., "CAPWAP Protocol Specification",
draft-ietf-capwap-protocol-specification-07 (work in
progress), June 2007.
[I-D.rosen-pwe3-congestion]
Rosen, E., "Pseudowire Congestion Control Framework",
draft-rosen-pwe3-congestion-04 (work in progress),
October 2006.
[PMP] Odlyzko, A., "A modest proposal for preventing Internet
congestion", AT&T technical report TR 97.35.1,
September 1997,
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<http://www.dtc.umn.edu/~odlyzko/doc/modest.proposal.pdf>.
[RFC1958] Carpenter, B., "Architectural Principles of the Internet",
RFC 1958, June 1996.
[RFC2357] Mankin, A., Romanov, A., Bradner, S., and V. Paxson, "IETF
Criteria for Evaluating Reliable Multicast Transport and
Application Protocols", RFC 2357, June 1998.
[RFC2475] Blake, S., Black, D., Carlson, M., Davies, E., Wang, Z.,
and W. Weiss, "An Architecture for Differentiated
Services", RFC 2475, December 1998.
[RFC2616] Fielding, R., Gettys, J., Mogul, J., Frystyk, H.,
Masinter, L., Leach, P., and T. Berners-Lee, "Hypertext
Transfer Protocol -- HTTP/1.1", RFC 2616, June 1999.
[RFC3234] Carpenter, B. and S. Brim, "Middleboxes: Taxonomy and
Issues", RFC 3234, February 2002.
[RFC3448] Handley, M., Floyd, S., Padhye, J., and J. Widmer, "TCP
Friendly Rate Control (TFRC): Protocol Specification",
RFC 3448, January 2003.
[RFC3649] Floyd, S., "HighSpeed TCP for Large Congestion Windows",
RFC 3649, December 2003.
[RFC3742] Floyd, S., "Limited Slow-Start for TCP with Large
Congestion Windows", RFC 3742, March 2004.
[RFC4828] Floyd, S. and E. Kohler, "TCP Friendly Rate Control
(TFRC): The Small-Packet (SP) Variant", RFC 4828,
April 2007.
[RFC5033] Floyd, S. and M. Allman, "Specifying New Congestion
Control Algorithms", BCP 133, RFC 5033, August 2007.
[Rate_fair_Dis]
Briscoe, B., "Flow Rate Fairness: Dismantling a Religion",
ACM CCR 37(2)63--74, April 2007,
<http://portal.acm.org/citation.cfm?id=1232926>.
[Res_p2p] Cho, K., Fukuda, K., Esaki, H., and A. Kato, "The Impact
and Implications of the Growth in Residential User-to-User
Traffic", ACM SIGCOMM CCR 36(4)207--218, October 2006,
<http://doi.acm.org/10.1145/1151659.1159938>.
[TSV_CAPWAP_issues]
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Borman, D. and IESG, "Transport Issues in CAPWAP", In
Proc. IETF-69 CAPWAP w-g, July 2007, <http://
www3.ietf.org/proceedings/07jul/slides/capwap-1.pdf>.
[az-calc] Infinite-Source, "Azureus U/L settings calculator", Web
page (accessed Oct'07) , 2007,
<http://infinite-source.de/az/az-calc.html>.
[ion-tsv-alt-cc]
"Experimental Specification of New Congestion Control
Algorithms", July 2007,
<http://www.ietf.org/IESG/content/ions/
ion-tsv-alt-cc.txt>.
Editorial Comments
[Note_Collapse] Some would say that it is not a congestion
collapse if congestion control automatically
recovers the situation after a while. However,
even though lack of autorecovery would be truly
devastating, it isn't part of the definition
[RFC2914].
[Note_Earthquake] On 26 Dec 2006, the Hengchun earthquake caused
faults on 12 of the 18 undersea cables passing
between Taiwan and the Philippines. The Internet
was virtually unusable for those trying to make
their emergency arrangements over these cables (as
well as for much of Asia generally). Each of these
flows was still having to compete with the
multiple flows of video downloads for remote users
who were presumably oblivious to the fact they
were consuming much of the surviving capacity.
When the Singaporean ISP, SingNet, announced
restoration of service before the cables were
repaired, it revealed that it had achieved this at
the expense of video downloads and gaming traffic
.
[Note_Neutral] Enforcement of /overall/ traffic limits within an
agreed acceptable use policy is a completely
different question to that of whether operators
should disciminate against /specific/ applications
or service providers (but they are confusible&
mdash;see the section on DPI.
[Note_Window] Within the flow rate equality worldview, there are
differences in views over whether window sizes
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should be compared in packets or bytes, and
whether a longer round trip time (RTT) should
reduce the target rate or merely slow down how
quickly the rate changes in order to reach a
target rate that is independent of RTT [FAST].
However, although these details are important,
they are merely minor internal differences within
the flow rate equality worldview when compared
against the differences with volume accounting.
Appendix A. Example Scenario
A.1. Base Scenario
We will consider 100 users all sharing a link from the Internet with
2Mbps downstream access capacity. Eighty bought their line for
occasional flurries of activity like browsing the Web, booking their
travel arrangements or reading their email. The other twenty bought
it mainly for unattended volume transfer of large files. We will
call these two types of use attended (or light) and unattended (or
heavy). Ignoring the odd UDP packet, we will assume all these
applications use TCP congestion control, and that all flows have
approximately equal round trip times.
Imagine the network operator has provisioned the shared link for a
contention ratio of 20:1, ie 100x2Mbps/20 = 10Mbps. For simplicity,
we assume a 16hr 'day' and that the attended use is only in the
'day', while unattended use is always present, having the night to
itself.
During the 'day', flows from the sixty attended users come and go
with about 1 in 10 actively downloading flows at any one time (a
downstream activity factor of 10%). To start with, we will further
assume that, when active, every user has approximately the same
number of flows open, whether attended or unattended. So, once all
flows have stabilised, at any instant TCP will ensure every user
(when active) gets about 10Mbps/(80*10% + 20*100%) = 357kbps of the
bottleneck.
Table 2 tabulates the salient features of this scenario. Also the
rightmost column shows the volume transferred per user during the
day, and for completeness the bottom row shows the aggregate.
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+------------+----------+------------+--------------+---------------+
| Type of | No. of | Activ- ity | Day rate | Day volume |
| use | users | factor | /user (16hr) | /user (16hr) |
+------------+----------+------------+--------------+---------------+
| Attended | 80 | 10% | 357kbps | 257MB |
| Unattended | 20 | 100% | 357kbps | 2570MB |
| | | | | |
| Aggregate | 100 | | 10Mbps | 72GB |
+------------+----------+------------+--------------+---------------+
Table 2: Base Scenario assuming 100% utilisation of 10Mbps bottleneck
and each user runs approx. equal numbers of flows with equal RTTs.
This scenario is not meant to be an accurate model of the current
Internet, for instance:
o Utilisation is never 100%.
o Upstream not downstream constrains most p2p apps on DSL (but not
all fixed & wireless access technologies).
o The activity factor of 10% in our base example scenario is perhaps
an optimistic estimate for attended use over a 16hr peak period.
1% is just as likely for many users (before file-sharing became
popular, DSL networks were provisioned for a contention ratio of
about 25:1, aiming to handle a peak average activity factor of 4%
across all user types).
o And rather than falling into two neat categories, users sit on a
wide spectrum that extends to far more extreme types in both
directions, while in between there are users who mix both types in
different proportions [Res_p2p].
But the scenario has merely been chosen because it makes it simple to
grasp the main issues while still retaining some similarity to the
real Internet. We will also develop the scenario as we go, to add
more realism (e.g. adding mixed user types).
A.2. Compounding Overlooked Degrees of Freedom
Table 3 extends the base scenario of Appendix A to compound
differences in average activity factor with differences in average
numbers of active flows.
During the 'day' at any instant we assume on average that attended
use results in 2 flows per user (which are still only open 10% of the
time), while unattended use results in 100 flows per user open
continuously. So at any one time 2016 flows are active, 16 from
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attended use (10%*80=8 users at any one time * 2 flows) and 2000 from
unattended use (20 users * 100 flows). TCP will ensure each of the 8
users who are active at any one time gets about 2*10Mbps/2016 =
9.9kbps of the bottleneck, while each of the 20 unattended users gets
about 100*10Mbps/2016 = 496kbps. This ignores flow start up effects,
which will tend to make matters even worse for attended use, given
briefer flows start more often.
+------------+-------+--------+---------------+----------+----------+
| Type of | No. | Activ- | Ave | Day rate | Day |
| use | of | ity | simultaneous | /user | volume |
| | users | factor | flows /user | (16hr) | /user |
| | | | | | (16hr) |
+------------+-------+--------+---------------+----------+----------+
| Attended | 80 | 10% | 2 | 9.9kbps | 7.1MB |
| Unattended | 20 | 100% | 100 | 496kbps | 3.6GB |
| | | | | | |
| Aggregate | 100 | | 2016 | 10Mbps | 72GB |
+------------+-------+--------+---------------+----------+----------+
Table 3: Compounded scenario with attentive users less frequently
active and running less flows than unattentive users, assuming 100%
utilisation of 10Mbps bottleneck and all equal RTTs.
A.3. Hybrid Users
{ToDo:}
A.4. Upgrading Makes Most Users Worse Off
Now that the light users are only getting 9.9kbps from their 2Mbps
lines, the operator needs to consider upgrading their bottleneck (and
all the other access bottlenecks for its other customers), so it does
a market survey. The operator finds that fifty of the eighty light
users and ten of the twenty heavy users are willing to pay more to
get an extra 500kbps each at the bottleneck. (Note that by making a
smaller proportion of the heavy users willing to pay more we haven't
weighted the argument in our favour--in fact our argument would have
been even stronger the other way round.)
To satisfy the sixty users who are willing to pay for a 500kbps
upgrade will require a 60*500kbps = 30Mbps upgrade to the bottleneck
and proportionate upgrades deeper into the network, which will cost
the ISP an extra $120 per month (say). The outcome is shown in
Table 4. Because the bottleneck has grown from 10Mbps to 40Mbps, the
bit rates in the whole scenario essentially scale up by 4x. However,
also notice that the total volume sent by the light users has not
grown by 4x. Although they can send at 4x the bit rate, which means
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they get more done and therefore transfer more volume, they don't
have 4x more volume to transfer--they let their machines idle for
longer between transfers reflected in their activity factor having
reduced from 10% to 4%. More bit rate was what they wanted, not more
volume particularly.
Let's assume the operator increases the monthly fee of all 100
customers by $1.20 to pay for the $120 upgrade. The light users had
a 9.9kbps share of the bottleneck. They've all paid their share of
the upgrade, but they've only got 30kbps more than they had--nothing
like the 500kbps upgrade most of them wanted and thought they were
paying for. TCP has caused each heavy user to increase the bit rate
of its flows by 4x too, and each has 50x more flows for 25x more of
the time, so they use up most of the newly provisioned capacity even
though only half of them were willing to pay for it.
But the operator knew from its marketing that 30 of the light users
and 10 of the heavy ones didn't want to pay any more anyway. Over
time, the extra $1.20/month is likely to make them drift away to a
competitor who runs a similar network but who decided not to upgrade
its 10Mbps bottlenecks. Then the cost of the upgrade on our example
network will have to be shared over 60 not 100 customers, requiring
each to pay $2/month extra, rather than $1.20.
+------------+-------+--------+---------------+----------+----------+
| Type of | No. | Activ- | Ave | Day rate | Day |
| use | of | ity | simultaneous | /user | volume |
| | users | factor | flows /user | (16hr) | /user |
| | | | | | (16hr) |
+------------+-------+--------+---------------+----------+----------+
| Attended | 80 | 4% | 2 | 40kbps | 11MB |
| Unattended | 20 | 100% | 100 | 2.0Mbps | 14GB |
| | | | | | |
| Aggregate | 100 | | 2006.4 | 40Mbps | 288GB |
+------------+-------+--------+---------------+----------+----------+
Table 4: Scenario with bottleneck upgraded to 40Mbps, but otherwise
unchanged from compounded scenario.
But perhaps losing a greater proportion of the heavy users will help?
Table 5 shows the resulting shares of the bottleneck once all the
cost sensitive customers have drifted away. Bit rates have increased
by another 2x, mainly because there are 2x fewer heavy users. But
that still only gives the light users 80kbps when they wanted
500kbps--and, to rub salt in their wounds, their monthly fees have
increased by $2 in all. The remaining 10 heavy users are probably
happy enough though. For the extra $2/month they get to transfer 8x
more volume each (and they still have the night to themselves).
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We have shown how the operator might lose those customers who didn't
want to pay. But it also risks losing all fifty of those valuable
light customers who were willing to pay, and who did pay, but who
hardly got any benefit. In this situation, a rational operator will
eventually have no choice but to stop investing in capacity,
otherwise it will only be left with ten customers.
+------------+-------+--------+---------------+----------+----------+
| Type of | No. | Activ- | Ave | Day rate | Day |
| use | of | ity | simultaneous | /user | volume |
| | users | factor | flows /user | (16hr) | /user |
| | | | | | (16hr) |
+------------+-------+--------+---------------+----------+----------+
| Attended | 50 | 2.5% | 2 | 80kbps | 14MB |
| Unattended | 10 | 100% | 100 | 4.0Mbps | 29GB |
| | | | | | |
| Aggregate | 60 | | 1002.5 | 40Mbps | 288GB |
+------------+-------+--------+---------------+----------+----------+
Table 5: Scenario with bottleneck upgraded to 40Mbps, but having lost
customers due to extra cost; otherwise unchanged from compounded
scenario.
We hope the above examples have clearly illustrated two main points:
o Rate equality at design time doesn't prevent extreme unfairness at
run time;
o If extreme unfairness is not corrected, capacity investment tends
to stop--a concrete consequence of unfairness that affects
everyone.
Finally, note that configuration guidelines for typical p2p
applications (e.g. BitTorrent calculator [az-calc]), advise a
maximum number of open connections that increases roughly linearly
with upstream capacity.
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Authors' Addresses
Bob Briscoe
BT & UCL
B54/77, Adastral Park
Martlesham Heath
Ipswich IP5 3RE
UK
Phone: +44 1473 645196
Email: bob.briscoe@bt.com
URI: http://www.cs.ucl.ac.uk/staff/B.Briscoe/
Toby Moncaster
BT
B54/70, Adastral Park
Martlesham Heath, Ipswich IP5 3RE
UK
Phone: +44 1473 645196
Email: toby.moncaster@bt.com
URI: http://research.bt.com/networks/TobyMoncaster.html
Louise Burness
BT
B54/77, Adastral Park
Martlesham Heath
Ipswich IP5 3RE
UK
Phone: +44 1473 646504
Email: Louise.Burness@bt.com
URI: http://research.bt.com/networks/LouiseBurness.html
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