collapse in g5kyuba.stanford.edu/trainwreck/g5k_tcp_train_sent.pdf · 24 conclusion a large scale...

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1 TCP & Future very high speed networks demo Collapse in G5K ? Stanford Trainwreck Workshop April 1st , 2008 Romaric Guillier, Pascale Vicat-Blanc Primet LIP, Ecole Normale Supérieure de Lyon, INRIA, France

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Page 1: Collapse in G5Kyuba.stanford.edu/trainwreck/G5K_TCP_train_sent.pdf · 24 Conclusion A large scale deployment of very High Speed Network to the home may lead to a critical vicious

1

TCP &Future very high speed

networks demo

Collapse in G5K ?

Stanford Trainwreck Workshop April 1st , 2008

Romaric Guillier, Pascale Vicat-Blanc PrimetLIP, Ecole Normale Supérieure de Lyon, INRIA, France

Page 2: Collapse in G5Kyuba.stanford.edu/trainwreck/G5K_TCP_train_sent.pdf · 24 Conclusion A large scale deployment of very High Speed Network to the home may lead to a critical vicious

2

Outline•Context and challenges

•G5K experimental facility & NXE engine

•Demo principles

•Results analysis

•Conclusion and perspective

……100 Mbps - 1 Gbps +

//

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3

Network & traffic evolution

TCP : « one fit all » solution for ever ?

70’s 2000’s 2010’s

?

?

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Network infrastructure changes?

1) Aggregation factor (uplink capacity /downlink capacity : K )2) Multiplexing factor (number of contributing sources: M)3) Heterogeneity of access speeds (Kb/s - Gb/s: 6 order of magnitude)4) Heterogeneity of RTT (1ms - 300ms)

K= C/Ca ≈ 1Ca

C

Few big flows may congest the linksLong RTTs issue

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Structural change: problem of sharing

TCP Transport protocol not designedfor very high node degrees & low aggregation factor context.

Example of theG5K network

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Evolution of Traffic demand?

1) Increase of the traffic load wrt to offered access capacity2) Increase of the traffic heterogeneity: time sensitive and throughput

sensitive flows ratio in the mix3) Change in the ratio of collaborative nodes (TCP) and non-collaborative

nodes (UDP or multiple TCP streams) in the mix

4) File size distribution: poisson => heavy tail ( α ≈ 2 => α ≈ 1 )

5) Increase of the mean flow size : Kbytes => Gbytes (elephant) (6 orders)6) Increase of the symmetry of the traffic (P2P vs Client-Serveur)

Internet stability strongly relies on the cooperative behavior of all end hosts.Will this assumption hold in ten years ?

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7

Outline•Context and challenges

•G5K experimental facility & NXE engine

•Demo principles

•Results analysis

•Conclusion and perspective

?

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G5K: large scale experimental facility

9 sites gathering 5000 fully reservable & reconfigurable processors

Fully private & controllable 10Gb/s core network

Private link 10Gb/s to NL- DAS3Private 1Gb/s link to JP- Naregi

RENATER-4

2,5 Gbit/s

Fibre noire

CERN

Sophia

Collaboration withRENATER-4

2,5 Gbit/s

Fibre noire

CERN

10Gb/s Dedicated lambdas

Example of a site: Grid5000@Lyon

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Reservation and Batch Scheduler

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Experiment setupExperiment setup

100 independant sources 100 Independant sinks1 GbE

10 GbE

iperfiperfiperf iperfiperfiperfd

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Long RTT emulation : GNET10

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NXE engine: Experiment workflowNXE engine: Experiment workflow

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Outline•Context and challenges

•G5K experimental facility & NXE engine

•Demo principles

•Results analysis

•Conclusion and perspective

?

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Scenario description

Experiment 1: rtt_ref = 7 ms Experiment 2: rtt_ref= 87 ms

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Cross-Traffic generation

K = 10Number of sources = 100

Access link = 1 GbpsRTT = [10; 20] ms

Fows size (Pareto = 1:2; = 1000)Congestion factor = 0 to 2

Non cooperative flows ratio = 0 to 0.8

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Experiment schedule

Experiment 1 : normal RTT => T-reference’s delay = 7ms

Experiment 2 : long RTT => T_reference’s delay = 87ms

normal 0.5-congest 1-congest 2-congest 2-cg+udp 0.5-congest2-cg+udp+//

45s 105s 165s 225s 285s 345s

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Reference transfer behaviorTransfer delay: optimal value: no congestion in the network

Transfer delay: critical value: delay > 10x optimal delay

Real time progress of the transfer

data transfered %

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Demonstration is running….

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Sagittaire clusterModel

Sun Fire V20z70 nodesCPU: AMD Opteron 2502.4GHz / 1MB / 400MHz

* 70 nodes x 2 cpus per node = 140 cpus* 140 cpus x 1 core(s) per cpu = 140 cores

Memory: 2 GBNetwork:

* Gigabit Ethernet * Gigabit Ethernet (management)

Driver: tg3Storage: 73 GB / SCSIDriver: mptspiM

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Demonstration workflowDemonstration workflow

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Outline•Context and challenges

•G5K experimental facility & NXE engine

•Demo principles

•Results analysis

•Conclusion and perspective

?

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What we observed: Experiment 1

a) 940Mb/s (-0%)

b) 940Mb/s (-0%)

c) 800Mb/s (-10%)

d) 270Mb/s (-55%)

e) 270Mb/s (-55%)

f) 100Mbs (-80%)

g) 600Mb/s (-40%)

normal 0.5-cng 1-cng 2-cg 2-cg+udp

0.5-cng2-cg+udp+//

Comparison with oracle

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23

Outline•Context and challenges

•G5K experimental facility & NXE engine

•Demo principles

•Results analysis

•Conclusion and perspectives

?

Page 24: Collapse in G5Kyuba.stanford.edu/trainwreck/G5K_TCP_train_sent.pdf · 24 Conclusion A large scale deployment of very High Speed Network to the home may lead to a critical vicious

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Conclusion

A large scale deployment of very High Speed Network to the homemay lead to a critical vicious cycle where:

• long RTT flows are starving• interactive and streaming traffics are suffering prohibitive delays• users become less & less patient• flows become more and more aggressive• traffic increases• more and more bandwidth is wasted in retransmissions…

• Need to rethink the way we share the capacity (via TCP only):• global cooperative behavior assumption ?• fairness objective function ?• end to end principle ?

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Testbed & tools used during the demo

•G5K or Grid5000 : http://www.grid5000.fr

•NXE http://www.ens-lyon.fr/LIP/RESO/Software/NXE/index.html

•AIST-GtrcNET-10: http://projects.gtrc.aist.go.jp/gnet/gnet10p3e.html

•Iperf http://dast.nlanr.net/Projects/Iperf/

•CLPBar http://clpbar.sourceforge.net/

for any information, please contact: [email protected]