When there is a tri-opoly, with no opportunity of competition, its easily possible to set prices which are very different than market conditions.
additionally, the three don't purchase enough to cover demand for their own network.
Most of the performance hit is because of commercial actions, not censorship.When there is a tri-opoly, with no opportunity of competition, its easily possible to set prices which are very different than market conditions. This is what is happening here.
Prices are set artificially high, so their interconnection partners wont purchase enough capacity. additionally, the three don't purchase enough to cover demand for their own network. Results in congestion.On Mon, Mar 2, 2020 at 2:49 PM Pengxiong Zhu <pzhu011@ucr.edu> wrote:You seem to be implying that you don't believe/can't see the GFWNo, that's not what I meant. I thought mandatory content filtering at the border means traffic throttling at the border, deliberately or accidentally rate-limiting the traffic, nowI think he was referring to GFW and the side effect of deep packet inspection.In fact, we designed a small experiment to locate the hops with GFW presence, and then try to match them with the bottleneck hops. We found only in 34.45% of the cases, the GFW hops match the bottleneck hops.
Best,
Pengxiong Zhu
Department of Computer Science and Engineering
University of California, RiversideOn Mon, Mar 2, 2020 at 1:13 PM Matt Corallo <nanog@as397444.net> wrote:> find out direct evidence of mandatory content filtering at the border
You seem to be implying that you don't believe/can't see the GFW, which
seems surprising. I've personally had issues with traffic crossing it
getting RST'd (luckily I was fortunate enough to cross through a GFW
instance which was easy to avoid with a simple iptables DROP), but its
also one of the most well-studied bits of opaque internet censorship
gear in the world. I'm not sure how you could possibly miss it.
Matt
On 3/2/20 2:55 PM, Pengxiong Zhu wrote:
> Yes, we agree. The poor transnational Internet performance effectively
> puts any foreign business that does not have a physical presence (i.e.,
> servers) in China at a disadvantage.
> The challenge is to find out direct evidence to prove mandatory content
> filtering at the border, if the government is actually doing it.
>
> Best,
> Pengxiong Zhu
> Department of Computer Science and Engineering
> University of California, Riverside
>
>
> On Mon, Mar 2, 2020 at 8:38 AM Matt Corallo <nanog@as397444.net
> <mailto:nanog@as397444.net>> wrote:
>
> It also gives local competitors a leg up by helping domestic apps
> perform better simply by being hosted domestically (or making
> foreign players host inside China).
>
>> On Mar 2, 2020, at 11:27, Ben Cannon <ben@6by7.net
>> <mailto:ben@6by7.net>> wrote:
>>
>>
>> It’s the Government doing mandatory content filtering at the
>> border. Their hardware is either deliberately or accidentally
>> poor-performing.
>>
>> I believe providing limited and throttled external connectivity
>> may be deliberate; think of how that curtails for one thing;
>> streaming video?
>>
>> -Ben.
>>
>> -Ben Cannon
>> CEO 6x7 Networks & 6x7 Telecom, LLC
>> ben@6by7.net <mailto:ben@6by7.net>
>>
>>
>>
>>> On Mar 1, 2020, at 9:00 PM, Pengxiong Zhu <pzhu011@ucr.edu
>>> <mailto:pzhu011@ucr.edu>> wrote:
>>>
>>> Hi all,
>>>
>>> We are a group of researchers at University of California,
>>> Riverside who have been working on measuring the transnational
>>> network performance (and have previously asked questions on the
>>> mailing list). Our work has now led to a publication in
>>> Sigmetrics 2020 and we are eager to share some
>>> interesting findings.
>>>
>>> We find China's transnational networks have extremely poor
>>> performance when accessing foreign sites, where the throughput is
>>> often persistently
>>> low (e.g., for the majority of the daytime). Compared to other
>>> countries we measured including both developed and developing,
>>> China's transnational network performance is among the worst
>>> (comparable and even worse than some African countries).
>>>
>>> Measuring from more than 400 pairs of mainland China and foreign
>>> nodes over more than 53 days, our result shows when data
>>> transferring from foreign nodes to China, 79% of measured
>>> connections has throughput lower than the 1Mbps, sometimes it is
>>> even much lower. The slow speed occurs only during certain times
>>> and forms a diurnal pattern that resembles congestion
>>> (irrespective of network protocol and content), please see the
>>> following figure. The diurnal pattern is fairly stable, 80% to
>>> 95% of the transnational connections have a less than 3 hours
>>> standard deviation of the slowdown hours each day over the entire
>>> duration. However, the speed rises up from 1Mbps to 4Mbps in
>>> about half an hour.
>>>
>>>
>>> We are able to confirm that high packet loss rates and delays are
>>> incurred in the foreign-to-China direction only. Moreover, the
>>> end-to-end loss rate could rise up to 40% during the slow period,
>>> with ~15% on average.
>>>
>>> There are a few things noteworthy regarding the phenomenon. First
>>> of all, all traffic types are treated equally, HTTP(S), VPN,
>>> etc., which means it is discriminating or differentiating any
>>> specific kinds of traffic. Second, we found for 71% of
>>> connections, the bottleneck is located inside China (the second
>>> hop after entering China or further), which means that it is
>>> mostly unrelated to the transnational link itself (e.g.,
>>> submarine cable). Yet we never observed any such domestic traffic
>>> slowdowns within China.
>>> Assuming this is due to congestion, it is unclear why the
>>> infrastructures within China that handles transnational traffic
>>> is not even capable to handle the capacity of transnational
>>> links, e.g., submarine cable, which maybe the most expensive
>>> investment themselves.
>>>
>>> Here is the link to our paper:
>>> https://www.cs.ucr.edu/~zhiyunq/pub/sigmetrics20_slowdown.pdf
>>>
>>> We appreciate any comments or feedback.
>>> --
>>>
>>> Best,
>>> Pengxiong Zhu
>>> Department of Computer Science and Engineering
>>> University of California, Riverside
>>