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
CNL - Network Performance Measurement Group3
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)
CNL - Network Performance Measurement Group11
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
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