[Bloat] Little's Law mea culpa, but not invalidating my main point
Bob McMahon
bob.mcmahon at broadcom.com
Thu Jul 22 12:30:47 EDT 2021
Thanks for this. I plan to purchase the second volume to go with my copy of
volume 1. There is (always) more to learn and your expertise is very
helpful.
Bob
PS. As a side note, I've added support for TCP_NOTSENT_LOWAT in iperf 2.1.4
<https://iperf2.sourceforge.io/iperf-manpage.html> and it's proving
interesting per WiFi/BT latency testing including helping to mitigate
sender side bloat.
*--tcp-write-prefetch **n*[kmKM]Set TCP_NOTSENT_LOWAT on the socket and use
event based writes per select() on the socket.I'll probably add measuring
the select() delays to see if that correlates to things like RF
arbitrations, etc.
On Wed, Jul 21, 2021 at 4:20 PM Leonard Kleinrock <lk at cs.ucla.edu> wrote:
> Just a few comments following David Reed's insightful comments re the
> history of the ARPANET and its approach to flow control. I have attached
> some pages from my Volume II which provide an understanding of how we
> addressed flow control and its implementation in the ARPANET.
>
> The early days of the ARPANET design and evaluation involved detailed
> design of what we did call “Flow Control”. In my "Queueing Systems, Volume
> II: Computer Applications”, John Wiley, 1976, I documented much of what we
> designed and evaluated for the ARPANET, and focused on performance,
> deadlocks, lockups and degradations due to flow control design. Aspects of
> congestion control were considered, but this 2-volume book was mostly about
> understanding congestion. Of interest are the many deadlocks that we
> discovered in those early days as we evaluated and measured the network
> behavior. Flow control was designed into that early network, but it had a
> certain ad-hoc flavor and I point out the danger of requiring flows to
> depend upon the acquisition of multiple tokens that were allocated from
> different portions of the network at the same time in a distributed
> fashion. The attached relevant sections of the book address these issues;
> I thought it would be of value to see what we were looking at back then.
>
> On a related topic regarding flow and congestion control (as triggered by
> David’s comment* "**at most one packet waiting for each egress link in
> the bottleneck path.”*), in 1978, I published a paper
> <https://www.lk.cs.ucla.edu/data/files/Kleinrock/On%20Flow%20Control%20in%20Computer%20Networks.pdf> in
> which I extended the notion of Power (the ratio of throughput to response
> time) that had been introduced by Giessler, et a
> <https://www.sciencedirect.com/science/article/abs/pii/0376507578900284>l
> and I pointed out the amazing properties that emerged when Power is
> optimized, e.g., that one should keep each hop in the pipe “just full”,
> i.e., one message per hop. As it turns out, and as has been discussed in
> this email chain, Jaffe
> <https://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=1095152> showed
> in 1981 that this optimization was not decentralizable and so no one
> pursued this optimal operating point (notwithstanding the fact that I
> published other papers on this issue, for example in 1979
> <https://www.lk.cs.ucla.edu/data/files/Kleinrock/Power%20and%20Deterministic%20Rules%20of%20Thumb%20for%20Probabilistic.pdf> and
> in 1981 <https://www.lk.cs.ucla.edu/data/files/Gail/power.pdf>). So this
> issue of Power lay dormant for decades until Van Jacobsen, et al,
> resurrected the idea with their BBR flow control design in 2016
> <https://queue.acm.org/detail.cfm?id=3022184> when they showed that
> indeed one could decentralize power. Considerable research has since
> followed their paper including another by me in 2018
> <https://www.lk.cs.ucla.edu/data/files/Kleinrock/Internet%20congestion%20control%20using%20the%20power%20metric%20LK%20Mod%20aug%202%202018.pdf>.
> (This was not the first time that a publication challenging the merits of a
> new idea negatively impacted that idea for decades - for example, the 1988
> book “Perceptrons”
> <https://www.amazon.com/Perceptrons-Introduction-Computational-Geometry-Expanded/dp/0262631113/ref=sr_1_2?dchild=1&keywords=perceptrons&qid=1626846378&sr=8-2> by
> Minsky and Papert discouraged research into neural networks for many years
> until that idea was proven to have merit.) But the story is not over as
> much work has yet to be done to develop the algorithms that can properly
> deal with congestion in the sense that this email chain continues to
> discuss it.
>
> Best,
> Len
>
>
>
>
>
>
>
> On Jul 13, 2021, at 10:49 AM, David P. Reed <dpreed at deepplum.com> wrote:
>
> Bob -
>
> On Tuesday, July 13, 2021 1:07pm, "Bob McMahon" <bob.mcmahon at broadcom.com>
> said:
>
> "Control at endpoints benefits greatly from even small amounts of
> information supplied by the network about the degree of congestion present
> on the path."
>
> Agreed. The ECN mechanism seems like a shared thermostat in a building.
> It's basically an on/off where everyone is trying to set the temperature.
> It does affect, in a non-linear manner, but still an effect. Better than a
> thermostat set at infinity or 0 Kelvin for sure.
>
> I find the assumption that congestion occurs "in network" as not always
> true. Taking OWD measurements with read side rate limiting suggests that
> equally important to mitigating bufferbloat driven latency using congestion
> signals is to make sure apps read "fast enough" whatever that means. I
> rarely hear about how important it is for apps to prioritize reads over
> open sockets. Not sure why that's overlooked and bufferbloat gets all the
> attention. I'm probably missing something.
>
>
> In the early days of the Internet protocol and also even ARPANET Host-Host
> protocol there were those who conflated host-level "flow control" (matching
> production rate of data into the network to the destination *process*
> consumption rate of data on a virtual circuit with a source capable of
> variable and unbounded bit rate) with "congestion control" in the network.
> The term "congestion control" wasn't even used in the Internetworking
> project when it was discussing design in the late 1970's. I tried to use it
> in our working group meetings, and every time I said "congestion" the
> response would be phrased as "flow".
>
> The classic example was printing a file's contents from disk to an ASR33
> terminal on an TIP (Terminal IMP). There was flow control in the end-to-end
> protocol to avoid overflowing the TTY's limited buffer. But those who grew
> up with ARPANET knew that thare was no way to accumulate queueing in the
> IMP network, because of RFNM's that required permission for each new packet
> to be sent. RFNM's implicitly prevented congestion from being caused by a
> virtual circuit. But a flow control problem remained, because at the higher
> level protocol, buffering would overflow at the TIP.
>
> TCP adopted a different end-to-end *flow* control, so it solved the flow
> control problem by creating a Windowing mechanism. But it did not by itself
> solve the *congestion* control problem, even congestion built up inside the
> network by a wide-open window and a lazy operating system at the receiving
> end that just said, I've got a lot of virtual memory so I'll open the
> window to maximum size.
>
> There was a lot of confusion, because the guys who came from the ARPANET
> environment, with all links being the same speed and RFNM limits on rate,
> couldn't see why the Internet stack was so collapse-prone. I think Multics,
> for example, as a giant virtual memory system caused congestion by opening
> up its window too much.
>
> This is where Van Jacobson discovered that dropped packets were a "good
> enough" congestion signal because of "fate sharing" among the packets that
> flowed on a bottleneck path, and that windowing (invented for flow control
> by the receiver to protect itself from overflow if the receiver couldn't
> receive fast enough) could be used to slow down the sender to match the
> rate of senders to the capacity of the internal bottleneck link. An elegant
> "hack" that actually worked really well in practice.
>
> Now we view it as a bug if the receiver opens its window too much, or
> otherwise doesn't translate dropped packets (or other incipient-congestion
> signals) to shut down the source transmission rate as quickly as possible.
> Fortunately, the proper state of the internet - the one it should seek as
> its ideal state - is that there is at most one packet waiting for each
> egress link in the bottleneck path. This stable state ensures that the
> window-reduction or slow-down signal encounters no congestion, with high
> probability. [Excursions from one-packet queue occur, but since only
> one-packet waiting is sufficient to fill the bottleneck link to capacity,
> they can't achieve higher throughput in steady state. In practice, noisy
> arrival distributions can reduce throughput, so allowing a small number of
> packets to be waiting on a bottleneck link's queue can slightly increase
> throughput. That's not asymptotically relevant, but as mentioned, the
> Internet is never near asymptotic behavior.]
>
>
>
> Bob
>
> On Tue, Jul 13, 2021 at 12:15 AM Amr Rizk <amr at rizk.com.de> wrote:
>
> Ben,
>
> it depends on what one tries to measure. Doing a rate scan using UDP (to
> measure latency distributions under load) is the best thing that we have
> but without actually knowing how resources are shared (fair share as in
> WiFi, FIFO as nearly everywhere else) it becomes very difficult to
> interpret the results or provide a proper argument on latency. You are
> right - TCP stats are a proxy for user experience but I believe they are
> difficult to reproduce (we are always talking about very short TCP flows -
> the infinite TCP flow that converges to a steady behavior is purely
> academic).
>
> By the way, Little's law is a strong tool when it comes to averages. To be
> able to say more (e.g. 1% of the delays is larger than x) one requires more
> information (e.g. the traffic - On-OFF pattern) see [1]. I am not sure
> when does such information readily exist.
>
> Best
> Amr
>
> [1] https://dl.acm.org/doi/10.1145/3341617.3326146 or if behind a paywall
> https://www.dcs.warwick.ac.uk/~florin/lib/sigmet19b.pdf
>
> --------------------------------
> Amr Rizk (amr.rizk at uni-due.de)
> University of Duisburg-Essen
>
> -----Ursprüngliche Nachricht-----
> Von: Bloat <bloat-bounces at lists.bufferbloat.net> Im Auftrag von Ben Greear
> Gesendet: Montag, 12. Juli 2021 22:32
> An: Bob McMahon <bob.mcmahon at broadcom.com>
> Cc: starlink at lists.bufferbloat.net; Make-Wifi-fast <
> make-wifi-fast at lists.bufferbloat.net>; Leonard Kleinrock <lk at cs.ucla.edu>;
> David P. Reed <dpreed at deepplum.com>; Cake List <cake at lists.bufferbloat.net
> >;
> codel at lists.bufferbloat.net; cerowrt-devel <
> cerowrt-devel at lists.bufferbloat.net>; bloat <bloat at lists.bufferbloat.net>
> Betreff: Re: [Bloat] Little's Law mea culpa, but not invalidating my main
> point
>
> UDP is better for getting actual packet latency, for sure. TCP is
> typical-user-experience-latency though, so it is also useful.
>
> I'm interested in the test and visualization side of this. If there were
> a way to give engineers a good real-time look at a complex real-world
> network, then they have something to go on while trying to tune various
> knobs in their network to improve it.
>
> I'll let others try to figure out how build and tune the knobs, but the
> data acquisition and visualization is something we might try to
> accomplish. I have a feeling I'm not the first person to think of this,
> however....probably someone already has done such a thing.
>
> Thanks,
> Ben
>
> On 7/12/21 1:04 PM, Bob McMahon wrote:
>
> I believe end host's TCP stats are insufficient as seen per the
> "failed" congested control mechanisms over the last decades. I think
> Jaffe pointed this out in
> 1979 though he was using what's been deemed on this thread as "spherical
>
> cow queueing theory."
>
>
> "Flow control in store-and-forward computer networks is appropriate
> for decentralized execution. A formal description of a class of
> "decentralized flow control algorithms" is given. The feasibility of
> maximizing power with such algorithms is investigated. On the
> assumption that communication links behave like M/M/1 servers it is
>
> shown that no "decentralized flow control algorithm" can maximize network
> power. Power has been suggested in the literature as a network performance
> objective. It is also shown that no objective based only on the users'
> throughputs and average delay is decentralizable. Finally, a restricted
> class of algorithms cannot even approximate power."
>
>
> https://ieeexplore.ieee.org/document/1095152
>
> Did Jaffe make a mistake?
>
> Also, it's been observed that latency is non-parametric in it's
> distributions and computing gaussians per the central limit theorem
> for OWD feedback loops aren't effective. How does one design a control
>
> loop around things that are non-parametric? It also begs the question, what
> are the feed forward knobs that can actually help?
>
>
> Bob
>
> On Mon, Jul 12, 2021 at 12:07 PM Ben Greear <greearb at candelatech.com
>
> <mailto:greearb at candelatech.com>> wrote:
>
>
> Measuring one or a few links provides a bit of data, but seems like
>
> if someone is trying to understand
>
> a large and real network, then the OWD between point A and B needs
>
> to just be input into something much
>
> more grand. Assuming real-time OWD data exists between 100 to 1000
>
> endpoint pairs, has anyone found a way
>
> to visualize this in a useful manner?
>
> Also, considering something better than ntp may not really scale to
>
> 1000+ endpoints, maybe round-trip
>
> time is only viable way to get this type of data. In that case,
>
> maybe clever logic could use things
>
> like trace-route to get some idea of how long it takes to get 'onto'
>
> the internet proper, and so estimate
>
> the last-mile latency. My assumption is that the last-mile latency
>
> is where most of the pervasive
>
> assymetric network latencies would exist (or just ping 8.8.8.8 which
>
> is 20ms from everywhere due to
>
> $magic).
>
> Endpoints could also triangulate a bit if needed, using some anchor
>
> points in the network
>
> under test.
>
> Thanks,
> Ben
>
> On 7/12/21 11:21 AM, Bob McMahon wrote:
>
> iperf 2 supports OWD and gives full histograms for TCP write to
>
> read, TCP connect times, latency of packets (with UDP), latency of "frames"
> with
>
> simulated video traffic (TCP and UDP), xfer times of bursts with
>
> low duty cycle traffic, and TCP RTT (sampling based.) It also has support
> for sampling (per
>
> interval reports) down to 100 usecs if configured with
>
> --enable-fastsampling, otherwise the fastest sampling is 5 ms. We've
> released all this as open source.
>
>
> OWD only works if the end realtime clocks are synchronized using
>
> a "machine level" protocol such as IEEE 1588 or PTP. Sadly, *most data
> centers don't
>
> provide
>
> sufficient level of clock accuracy and the GPS pulse per second *
>
> to colo and vm customers.
>
>
> https://iperf2.sourceforge.io/iperf-manpage.html
>
> Bob
>
> On Mon, Jul 12, 2021 at 10:40 AM David P. Reed <
>
> dpreed at deepplum.com <mailto:dpreed at deepplum.com> <mailto:
> dpreed at deepplum.com
>
> <mailto:dpreed at deepplum.com>>> wrote:
>
>
>
> On Monday, July 12, 2021 9:46am, "Livingood, Jason" <
>
> Jason_Livingood at comcast.com <mailto:Jason_Livingood at comcast.com>
>
> <mailto:Jason_Livingood at comcast.com <mailto:
>
> Jason_Livingood at comcast.com>>> said:
>
>
> I think latency/delay is becoming seen to be as important
>
> certainly, if not a more direct proxy for end user QoE. This is all still
> evolving and I
>
> have
>
> to say is a super interesting & fun thing to work on. :-)
>
> If I could manage to sell one idea to the management
>
> hierarchy of communications industry CEOs (operators, vendors, ...) it is
> this one:
>
>
> "It's the end-to-end latency, stupid!"
>
> And I mean, by end-to-end, latency to complete a task at a
>
> relevant layer of abstraction.
>
>
> At the link level, it's packet send to packet receive
>
> completion.
>
>
> But at the transport level including retransmission buffers,
>
> it's datagram (or message) origination until the acknowledgement arrives
> for that
>
> message being
>
> delivered after whatever number of retransmissions, freeing
>
> the retransmission buffer.
>
>
> At the WWW level, it's mouse click to display update
>
> corresponding to completion of the request.
>
>
> What should be noted is that lower level latencies don't
>
> directly predict the magnitude of higher-level latencies. But longer lower
> level latencies
>
> almost
>
> always amplfify higher level latencies. Often non-linearly.
>
> Throughput is very, very weakly related to these latencies,
>
> in contrast.
>
>
> The amplification process has to do with the presence of
>
> queueing. Queueing is ALWAYS bad for latency, and throughput only helps if
> it is in exactly the
>
> right place (the so-called input queue of the bottleneck
>
> process, which is often a link, but not always).
>
>
> Can we get that slogan into Harvard Business Review? Can we
>
> get it taught in Managerial Accounting at HBS? (which does address
> logistics/supply chain
>
> queueing).
>
>
>
>
>
>
>
>
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> --
> Ben Greear <greearb at candelatech.com <mailto:greearb at candelatech.com
>
>
> Candela Technologies Inc http://www.candelatech.com
>
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> --
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> Candela Technologies Inc http://www.candelatech.com
>
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