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TCP/IP congestion control PK3C Kernel Module for video streaming/data servers. |
First, read "understanding": https://granulate.io/understanding-congestion-control/
Then, this project will help to:
- improve for free quality of network connections
- make upload data faster for your workstation
- make download data faster from your servers
Also read first Wiki page Cubic congestion control ( https://en.wikipedia.org/wiki/CUBIC_TCP ) and then about similar Google project BBR that has more in common with this PK3C project (than if comparing PK3C with default Cubic). However, comparing BBR and PK3C, BBR is kind of white-box (model-based) that developed by Google for its internal networks (before published). And PK3C is kind of a black-box (model-free), and PK3C based on older version of Vivace PCC.
These graphs shows upload test by speed.io for one connection (and you can see that both default Cubic congestion algorithm and new PK3C does it job):
- picture above, the PK3C makes decision about best upload speed faster (without trying too high);
- picture above, for the Cubic overall for one connection is a little bit faster.
- !Even for one connection PK3C could be a little bit slower, for many connections PK3C sending data more aggressively than Cubic, so if few Cubic connections and few PK3C connections share the same link, then PK3C wins (up to 5 times wins!)!
- However, this is both could be a problem that PK3C faster than Cubic and this problem discussed in this forum: https://news.ycombinator.com/item?id=8381801
- Both I think this is the answer to the question why Google uses BBR instead of Cubic (because they want their traffic to be downloadable faster than from other servers that are uses defaults that are non-BBR). The Google says that BRR about 20% faster, than Cubic.
Both it means that this PK3C project could be usefull not only for servers, but both for your workstation (because both connections initiation should be faster and both upload data from your workstation would be faster a little bit faster at least for short-time connections where no need "try-guess-initial-time" for PK3C comparing to Cubic).
Take in mind that this PK3C project has nothing in common with any other nowadays versions of PCC project. The new name PK3C (comparing to older PCC) suppose to show that even is based on original https://github.com/PCCproject/PCC-Kernel project that is under BSD/Gplv2 (and original PCC-Kernel included in subdir ./PCC-Kernel/* for history reasons), this PK3C is different.
You may find some other related to PCC projects like some userspace control utility (see https://github.com/PCCproject/PCC-Uspace, and some links to original papers there in PCC-Uspace that are relevant both for PCC-Kernel and for this PK3C). The original parts of code taken from PCC-Kernel for this PK3C described in papers there.
This PK3C project is independent and currently not compatible with this PCC-Uspace utility; see LICENSE and ask questions inside github or privately to ludwigschapiro@gmail.com , so I'm Ludww and I'm author of diff from PCC-Kernel to this PK3C.
Found one other similar project that is based on original PCC-Kernel: https://github.com/KaiwenZha/PCC-Vivace (but as far as I know PK3C gives better results than PCC-Vivace, even it is still uses Vivace utility function too).
This one is for TCP/IP, but there are other solutions of congestion problem for other protocols (ex. DCCP protocol that is suppose to be better, than TCP/IP or "UDP"; and with better congestion than any in TCP/IP). However, the DCCP is not yet common (not supported and not known), and TCP/IP is the today most used (apart from UDP that is being used everywhere too where UDP could be without congestion or could be congestion above raw UDP protocol), so the projects like this PK3C that are for TCP/IP are still actual today (so I recomend you to try using this PK3C instead of Cubic or to compare it with BBR from Google).
git clone https://github.com/Ludww/pk3c.git
For Red Hat 8, prerequirements:
sudo dnf install -y kernel-devel
(or for Red Hat 7:
yum install kernel-devel
)
Check your kernel version:
uname -a
, and make sure that sources exists:
ex. soft link from /lib/modules/3.10.0-1127.el7.x86_64/build
to dir /usr/src/kernels/3.10.0-1127.el7.x86_64
For compiling module, just run:
sudo make clean
sudo make
For testing if compiled well, this last cmd (that "install" the module until reboot):
insmod ./tcp_pk3c.ko
, and you should see next output as last line of dmesg: TCP: pk3c registered.
, and as root run these five commands (after module loaded and for making all uploading outside TCP/IP connections to use PK3C):
sudo sysctl -w net.core.wmem_max=8194300
sudo sysctl -w net.ipv4.tcp_wmem="4096 8194300 8194300"
sudo sysctl -w net.core.rmem_max=4258291
sudo sysctl -w net.ipv4.tcp_rmem="4096 8194300 8194300"
echo "pk3c" > /proc/sys/net/ipv4/tcp_congestion_control
Enjoy!
Now the speed of your internet and browsing should be much faster!
This module improves speed of uploading (like speed of sending data from your machine to somewhere, so it is more common for data-servers, because for WorkStations usually you do more downloading than uploading), but still it improves "feeling" of fast internet for local workstation too, because it improves slow-start and because then Internet connections of other users works slower than your connections (means it improves the speed of connection-initiation and both makes your connections more aggressively comparing to other regular user connections like could be situation when you use 4/5 of channel and other user only 1/5 of the same channel, because you are using PK3C algorithm that suppresses default Cubic algorithm being used by other Internet users);
Both PK3C gives higher overall speed of data upload from machine where you try it (or higher download speed for users who download data from your server and the good thing that users don't need to intall anything, so once you install this kernel module on your server, then every customer downloading data from your server would experience better quality of downloading speed!).
However, if you try one big file upload test, it could be both faster or a little bit slower comparing to default "Cubic" (see pic in top of this doc).
Take in mind that one file upload test is nothing and instead you should try 100 or 1000 files uploading simultaneously and then you would see the difference,
or for comparing with Cubic maybe try simpler 5 connections together running /bin/bash ./a.sh where cat ./a.sh below and server is remote server, ex. from your local workstation 5 uploads to the server in Google Cloud:
time scp ./IMG_7700.MOV user@server:~/1 &
time scp ./IMG_7700.MOV user@server:~/2 &
time scp ./IMG_7700.MOV user@server:~/3 &
time scp ./IMG_7700.MOV user@server:~/4 &
time scp ./IMG_7700.MOV user@server:~/5 &
- with PK3C this should work about %20 faster, than if with default Cubic.
If running together 5 uploads with PK3C and other similar 5 with Cubic (like run a.sh with Cubic and then imideatelly b.sh with PK3C), then PK3C should win about 5 times in speed comparing to Cubic!
Generally, there are different kernel modules for TCP/IP congestion already existed before PK3C (like see http://web.cs.wpi.edu/~claypool/papers/tcp-sat-pam-21/camera-draft.pdf for comparing behavior of one connection using Cubic, BBR, Hybla or PCC kernel module).
And BBR (from Google) is similar like PCC or like this PK3C (in two words the difference is that BBR rate based and Cubic is window based).
The difference of BBR from PK3C (or from PCC) is:
-
- BBR optimized for Google servers and non-universal (unlikely that would give better results for your servers until if you use it similar way like Google does).
-
- BBR not supported with kernels 3.x (and PK3C developed first for kernels 3.x and then for 4.x and works the same way for both, so it works similar for kernels 4.x or kernels 3.x, and this is the only rate based congestion TCP/IP that is good for kernels 3.x, so you may use it for Red Hat 7.x or other older Linux systems!).
-
- PK3C optimized both for high bandwidth (like provider of video streams for multi customers) and both for low-speeds lossy connections where many IP-packets loss happens (comparing with PCC that works good only for high speed connections). Saying generally, the PK3C optimized for corner cases (when very low-rate or special strange connection), and PCC doesn't.
-
- The PK3C is free (dual BSD/GPL license and based on https://github.com/PCCproject/PCC-Kernel by Nogah Frankel ). And the latest PCC became comercial (non available and not based on original PCC-Kernel anymore). And the BBR (that is other analogue of PK3C) is available with "Apache License 2.0", but only for latest 4.x or 5.x kernels. So the advantage of PK3C that is works good for Kernels 3.x too and enough universal. And both BBR is "less powerfull" comparing with PK3C, and PCC-Kernel is "less or similar powerfull" comparing with PK3C (at least if comparing with one from https://github.com/PCCproject/PCC-Kernel or from https://github.com/KaiwenZha/PCC-Vivace).
-
- For more info about PK3C advantages comparing with PCC , see top comments of the /tcp_pk3c_main.c (and the main advantage is that slow-start happens much faster for PK3C, than for PCC, and two years of science were for making this solution, so it means that PK3C guesses optimal rate of any new connection faster and better, than other). However, nobody knows what is inside latest versions of "commercial" PCC if any -- the overall reason why PK3C better, than original version of PCC-Kernel (or other original Vivace versions), is that the PCC-Kernel based on theory only and as result more like scientific work, and PK3C based both on similar theory and practice and a lot of different testing (for example, when it was obvious that sometimes utility function gives incorrect results for some specific connections, then some additional logic with max/min estimates and with do fast slow-start were added to PK3C and tested). In original PCC-Kernel there are no such improvements, because authors of original PCC tried to keep it based on utility function only (without such experimental guesses how to make it best, but instead original PCC based on few ideal experiments in ideal room with ideal conditions).
-
- Of course, the congestion algorithm need to meet advantage of auto-stabilization: if many connections share bottleneck, no one connection suppose to use all of the bandwidth, but instead all connections together should split these bottleneck in alsmost similar parts. The PK3C meets of this expectation (at least tested that many simultanious connections with PK3C does this), and the original version of PCC (from github) didn't meet this expectation. The main reason that for making overall multi-connections system being effective all connections needs to change in time randomly (trying higher and lower values even the connection is stable) and PCC instead keeping as stable as possible, but PK3C does some small variations even for stable links (ex. see at the top picture where PK3C for one stable connection goes not by straight line, but with small flactuations). So PK3C has enough randomeness for being similar or better, than cubic (and PCC likely not).
-
- PK3C has two algorithms together: both Vivace being used and some additional "handbrakes" being used (like if Vivace make incorrect decision, then other simpler "handbrake" algorithm improves this decision), so second algorithm fixes input signals mistakes of main algorirthm. Means if input RTT or input number of loss packets signals too weak, then still overall PK3C works Ok based on additional assumptions apart from these main input signals (and output result of PK3C algorithm is "current optimal rate is"). However, kept original ideas from PCC-Kernel and Vivace utility func as is without modification, and regarding these ideas watch presentation https://www.usenix.org/conference/nsdi18/presentation/dong
-
- Original PCC was too conservative (like designed for some ideal conditions), and this new PK3C is kind of opensource hippie. I believe that you would try it and if you find case when PK3C works much worser, than Cubic or other (like BBR), then post "Issue" here and then I can try to improve PK3C.
For local testing of multi-connections, there is special tool "mahimahi" (for emulation). Try to google for mahimahi.
Also this module tested with 10Gb+ networks with multi (tousants) connections. Results of these tests not included yet here, but overall results were fine (better than for Cubic).
Note that for kernel 3 need to run this configuration (shell script commands) before usage of the PK3C (where $1 is eth interface name), and because for kernel 3 the rate congestion control algorithms were not supported yet, there are many shell commands for configuration of tc qdisc (and for kernel 4 or higher most of these command not required anymore):
sudo ethtool -K $1 gso off
sudo ethtool -K $1 tso off
sudo ethtool -K $1 gro off
sudo sysctl -w net.core.default_qdisc=fq
sudo sysctl -w net.core.wmem_max=8194300
sudo sysctl -w net.ipv4.tcp_wmem="4096 8194300 8194300"
sudo sysctl -w net.core.rmem_max=4258291
sudo sysctl -w net.ipv4.tcp_rmem="4096 8194300 8194300"
tc qdisc replace dev $1 root fq pacing maxrate 32gbit
tc qdisc replace dev $1 root fq pacing maxrate 32gbit flow_limit 10000 refill_delay 2 limit 10000 buckets 3023 quantum 10000 initial_quantum 15140
, and for kernel 4 just mem sysctl command are enough:
sudo sysctl -w net.core.wmem_max=8194300
sudo sysctl -w net.ipv4.tcp_wmem="4096 8194300 8194300"
sudo sysctl -w net.core.rmem_max=4258291
sudo sysctl -w net.ipv4.tcp_rmem="4096 8194300 8194300"
(and probably not necessary).
Additional testing (comparing with Cubic for being sure that PK3C works at least the same good as Cubic for regular non-noisy and non-lossy connections)
for server use command
iperf3 -s -p 80
and for client
iperf3 -c server -p 80 -P 50
, means run 50 connections simultenyiously.
See results of testing: https://github.com/Ludww/pk3c/blob/main/testing.txt
The PK3C optimized for video streams. It is known that HD video streams are at least 5 Mbps each, so if PK3C gives better results for such streams, than Cubic, like ~5 Mbits/sec streams for 20 streams inside 100 MBits channel, then it works as expected (and faster, than Cubic).
However, PK3C could be used both for servers and for Linux workstations (it is a huge benefit for data providers servers and both for regular users).
The only disadvantage of PK3C is that it doesn't work good with very slow connections (like less than 250KBits/sec).
However, for data (or video) providers the benefit could be sensitive (say 40% cheaper hardware or 40% better customers experience).
The big advantage of PK3C that it can work good with very noisy (and high packets loss) connections, and Cubic not at all.
See results of testing: https://github.com/Ludww/pk3c/blob/main/testing.txt
