Mario,
putting aside LoLa for a second,
I'm not quite sure that the theorem you cite is valid.
According to the model R_i is the sending rate.
The sum across all flows bottlenecked at the link does not need to be
equal to the link capacity.
The input rate can be instantaneously below or above the link capacity.
Even If the link is never idle and the output rate is always C for all t.
If the sum_i R_i = C is false because of what I said, than p_i which is
nothing more than
the shadow price of the link capacity constraint, can be a function of a
constant delay d, i.e. p_i = cost * d for all i.
This theorem can be valid only if the input rate of a queue is
instantaneously equal to the output queue.
We all know that a queue exists just because there is an instantaneous
difference of input and output rates
at the link. So to conclude, this theorem if valid iff input == output
rate then the queue is always zero, i.e. d=0.
The theorem is either an artefact of the model or just wrong. Or I'm
missing something...
On Thu, Nov 29, 2018 at 6:07 PM Mario Hock <mario.h...@kit.edu
<mailto:mario.h...@kit.edu>> wrote:
Hi Luca,
I'm answering on behalf of Roland, since I am a co-author of the paper.
This is an excellent question, since it goes right at the heart of how
LoLa works.
Indeed, the paper is a first of a series. A second one, looking deeper
into the fair flow balancing mechanism, is currently under submission.
Similar as other delay based congestion controls, LoLa tries to achieve
fairness by allowing each flow to buffer the same amount of data at the
bottleneck. We have this, e.g., in TCP Vegas, and (in a way) also in
Copa (a recently proposed congestion control) and many others. If this
is achieved, we get flow rate fairness independent of a flow's RTT.
Usually (in other congestion controls) this "allowed amount of data" is
fixed per flow. We presume that this approach does not scale well to
high speed networks. Since the queuing delay resulting from this amount
of data is reduced with increasing bottleneck rate. Thus, it becomes
harder to measure it right. This can easily be seen (and proven) for
TCP
Vegas.
Note: Just using higher fixed values is not an option, since it would
not work at lower speeds anymore and also not with a large number of
flows.
Therefore, LoLa tries to find a suitable value for the "allowed amount
of data" dynamically. This is X(t).
Our approach is to grow X(t) over time during the Fair Flow Balancing
phase. This phase ends when the queuing delay reaches 5ms. Thus, (in
the
ideal case) at the end of Fair Flow Balancing, X(t) is just as large
that all flows at bottleneck create a queuing delay of 5ms, and all
flows contribute equally to this queue. Hence, flow rate fairness is
achieved. (Note that LoLa is designed in a way that t is (almost)
synchronized among the competing flows.)
Generally, other ways of determining a suitable X(t) are
conceivable. In
our approach X(t) is a monotonically increasing function, but it is
regularly reset as LoLa cycles between its states; i.e., after a
queuing
delay of 5ms is reached, the queue is drained and everything starts
again. (Thus, the timespan where X(t) is monotonically increased is
called a "round of fair flow balancing".)
This way we can overcome the constraint given in [1]:
"""
THEOREM 6 (FAIRNESS/DELAY TRADEOFF). For congestion control mechanisms
that have steady state throughput of the kind R = f(d, p), for some
function f, delay d and feedback p, if the feedback is based on purely
end to end delay measurements, you can either have fairness or a fixed
delay, but not both simultaneously
"""
[1] "ECN or Delay: Lessons Learnt from Analysis of DCQCN and TIMELY"
Yibo Zhu et al., https://dl.acm.org/citation.cfm?id=2999593
Best, Mario
Am 29.11.18 um 17:09 schrieb Luca Muscariello:
> Hi Roland,
>
> It took me quite a lot of time to find this message in the thread...
> I read the paper you sent and I guess this is the first of a
series as
> many things stay uncovered.
>
> Just a quick question: why is X(t) always increasing with t?
>
>
> On Tue, Nov 27, 2018 at 11:26 AM Bless, Roland (TM)
> <roland.bl...@kit.edu <mailto:roland.bl...@kit.edu>
<mailto:roland.bl...@kit.edu <mailto:roland.bl...@kit.edu>>> wrote:
>
> Hi Luca,
>
> Am 27.11.18 um 10:24 schrieb Luca Muscariello:
> > A congestion controlled protocol such as TCP or others,
including
> QUIC,
> > LEDBAT and so on
> > need at least the BDP in the transmission queue to get
full link
> > efficiency, i.e. the queue never empties out.
>
> This is not true. There are congestion control algorithms
> (e.g., TCP LoLa [1] or BBRv2) that can fully utilize the
bottleneck link
> capacity without filling the buffer to its maximum capacity.
The BDP
> rule of thumb basically stems from the older loss-based
congestion
> control variants that profit from the standing queue that
they built
> over time when they detect a loss:
> while they back-off and stop sending, the queue keeps the
bottleneck
> output busy and you'll not see underutilization of the link.
Moreover,
> once you get good loss de-synchronization, the buffer size
requirement
> for multiple long-lived flows decreases.
>
> > This gives rule of thumbs to size buffers which is also very
> practical
> > and thanks to flow isolation becomes very accurate.
>
> The positive effect of buffers is merely their role to absorb
> short-term bursts (i.e., mismatch in arrival and departure rates)
> instead of dropping packets. One does not need a big buffer to
> fully utilize a link (with perfect knowledge you can keep the
link
> saturated even without a single packet waiting in the buffer).
> Furthermore, large buffers (e.g., using the BDP rule of thumb)
> are not useful/practical anymore at very high speed such as
100 Gbit/s:
> memory is also quite costly at such high speeds...
>
> Regards,
> Roland
>
> [1] M. Hock, F. Neumeister, M. Zitterbart, R. Bless.
> TCP LoLa: Congestion Control for Low Latencies and High
Throughput.
> Local Computer Networks (LCN), 2017 IEEE 42nd Conference on, pp.
> 215-218, Singapore, Singapore, October 2017
> http://doc.tm.kit.edu/2017-LCN-lola-paper-authors-copy.pdf
>
> > Which is:
> >
> > 1) find a way to keep the number of backlogged flows at a
> reasonable value.
> > This largely depends on the minimum fair rate an
application may
> need in
> > the long term.
> > We discussed a little bit of available mechanisms to
achieve that
> in the
> > literature.
> >
> > 2) fix the largest RTT you want to serve at full
utilization and size
> > the buffer using BDP * N_backlogged.
> > Or the other way round: check how much memory you can use
> > in the router/line card/device and for a fixed N, compute
the largest
> > RTT you can serve at full utilization.
> >
> > 3) there is still some memory to dimension for sparse flows in
> addition
> > to that, but this is not based on BDP.
> > It is just enough to compute the total utilization of sparse
> flows and
> > use the same simple model Toke has used
> > to compute the (de)prioritization probability.
> >
> > This procedure would allow to size FQ_codel but also SFQ.
> > It would be interesting to compare the two under this
buffer sizing.
> > It would also be interesting to compare another mechanism
that we
> have
> > mentioned during the defense
> > which is AFD + a sparse flow queue. Which is, BTW, already
> available in
> > Cisco nexus switches for data centres.
> >
> > I think that the the codel part would still provide the
ECN feature,
> > that all the others cannot have.
> > However the others, the last one especially can be
implemented in
> > silicon with reasonable cost.
>
>
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