Self-generated Self-similar Traffic

Péter Hága

Péter Pollner

Gábor Simon

István Csabai

Gábor Vattay

CNL - Network Performance Measurement Group2

Outline

• Motivations • Self-similarity• Karn’s Algorithm • Backoff mechanism & Self-similar traffic• Virtual loss• Simulation• Measurement• Discussion

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Motivations

Goal:

• network dynamics: self-similar

• new explanation: RTT fluctuations & self-organization

• self-similarity without the former known reasons:

file size distribution, user interaction, chaos, high packet loss

• separation of the real & virtual losses

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Self-similarity

Hurst exponent: degree of self-similarity

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Self-similarity

• known sources:• file size distribution• user interaction• chaos due to small buffers• high loss rate

heavytailed file size distribution

self-similar TCP flowM.Crovella, A.Bestravos 1997

heavytailed modem duration time

self-similar TCP flowA.Feldmann, A.C.Gilbert, W.Willinger, T.G.Kurtz 1997

Buffer/No of TCPs < Rcrit => forces TCPs into backoff states

self-similar TCP flowA.Fekete, G.Vattay 2001

high packet loss => backoff states

Self-similar TCP flowL.Guo, M.Crovella, I.Matta 2000

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Karn’s Algorithm

• Route: very congested• TCP: exponential backoff state:

• If packets are lost many times cwnd=1 is reached, halving is not an option• TCP waits an TRTT and tries again• If fails, waits 2 TRTT, 4 TRTT, 8 TRTT,... • k = 1,…,6 denote backoff states of increasing depth

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Backoff mechanism & Self-similar traffic

Backoff probability distrribution Effective packet loss ratio

A.Fekete, G.Vattay 2001

Pk: probability of kth backoff state

Pk peffective

where p: packet loss rate felt by the TCP

Pk+1 = (2p-p2) Pk, k=0,…,4

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Backoff mechanism & Self-similar traffic

Backoff probability distrribution Hurst exponent

packet sending process: ON/OFF process OFF periods: inter arrival times of packets

Hurst parameter of such an aggregated traffic:

when 1 < < 2, or 12.5% < p < 25% =>=> 0.5 < H < 1

H = (3-)/2, if > 2 = log2(1/2p)

L.Guo, M.Crovella, I.Matta 2000

» t-(+1)

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Virtual losses

Packet losses

virtual loss: ACK arrives, but after the RTO period, so the packet is retransmitted

real loss: dropped packets

Source of packet loss:• real: at high congested buffers, or at low quality lines (e.g. radio lines) - solution: simple, by improving hardware conditions• virtual: it comes from the heavily fluctuating background traffic - solution: ??

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bursty background traffic

heavily fluctuating round-trip time

heavily fluctuating queuing time

Virtual losses

If queuing time jumps to a high value due to increased traffic

RTTreal > RTOTCP => virtual loss occurs (the TCP doesn’t get ACK until RTO expires)

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Simulations

• Network Simulator v2 (NS)• Small network, but general operation:

• random connections between nodes• fixed file size (NOT heavytailed distribution)• big buffers (no real packet loss)

Link bandwidth 1 Mbps

Link delay 1 ms

Buffer size 1000 pkts

File size 1000 pkts

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Simulations

We found self-similarity in the flow:

Hvariance=0.86

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the KNOWN SOURCES:• file size distribution• user interaction• chaos due to small buffers• high loss rate

were NOT ENOUGH:• fixed file size• ~ contunious transfer• big buffers• no packet loss

Simulations

the traffic is self-similar, BUT:

What is the cause of self-similarity in our case?

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Simulations

Backoff statistics the cause of the self-similarity

( Hvariance = 0.86 )

Hbackoff = 0.89

peffective = 21% =><==><= preal = 0%(felt by the TCP)

H = (3-)/2, if > 2 = log2(1/2p)

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Measurement

• modified linux kernel (2.2.x series)

• tcpdump

• congested transcontinental line

• packet inter arrival time and backoff statistics

• separate of real and virtual loss

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Measurement

Self-similarity of the flow, Hurst exponent

Packet inter arrival distribution

H=0.70

Variance-time plot

H=0.69

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Measurement

backoff values - time backoff probability distribution

k=1,…,15 ploss=16.5%, Hbackoff=0.70

Backoff statistics

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Measurement

Packet loss detection and separation:

tcpdump

Real packet loss Virtual loss

p ¼ 6.5% congested route

p ¼ 10 –12%

peffective ¼ 16 – 18%

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Measurement

• loss ratio from backoff statistics, p=16.5%• loss ratio calculated from tcpdump output: real, effective (real+virtual) losses

TCP is backed off, by: • real loss (dropped)• virtual loss (only delayed and timed out)

pbackoff = peffective preal + pvirtual preal

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Conclusions

Main results:• new source of the self-similar traffic: RTT fluctuations• RTT fluctuations generates virtual packet losses, which induce backoff states with high probability, and the backoff states cause self-similar traffic• former sources are avoidable by dimensioning:

file or user quotas, big buffers, high quality lines• the RTT fluctuations: comes from the confluent random flows and network dynamics. Solution: dimensioning, protocol modification, etc.?• self-organizing self-similarity: RTT fluctuations feeds back into the background traffic