Self-generated Self-similar Traffic

1. Self-generated Self-similar Traffic Péter Hága Péter Pollner Gábor Simon István Csabai Gábor Vattay

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

3. Motivations • Goal: • network dynamics: self-similar • new explanation: RTT fluctuations & self-organization • self-similaritywithout the former known reasons: file size distribution, user interaction, chaos, high packet loss • separation of the real & virtual losses

4. Self-similarity Hurst exponent: degree of self-similarity

5. heavytailed file size distribution high packet loss => backoff states Buffer/No of TCPs < Rcrit => forces TCPs into backoff states heavytailed modem duration time self-similar TCP flow Self-similar TCP flow self-similar TCP flow self-similar TCP flow L.Guo, M.Crovella, I.Matta 2000 A.Fekete, G.Vattay 2001 M.Crovella, A.Bestravos 1997 A.Feldmann, A.C.Gilbert, W.Willinger, T.G.Kurtz 1997 Self-similarity • known sources: • file size distribution • user interaction • chaos due to small buffers • high loss rate

6. 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

7. Backoff mechanism & Self-similar traffic Backoff probability distrribution Effective packet loss ratio Pk: probability of kthbackoff state Pk+1 = (2p-p2) Pk, k=0,…,4 wherep: packet loss rate felt by the TCP Pk peffective A.Fekete, G.Vattay 2001

8. a = log2(1/2p) Backoff mechanism & Self-similar traffic Backoff probability distrribution Hurst exponent packet sending process: ON/OFF process OFF periods: inter arrival times of packets » t-(a+1) Hurst parameter of such an aggregated traffic: H = (3-a)/2, if a > 2 when 1 < a < 2, or 12.5% < p < 25%=>0.5 < H < 1 L.Guo, M.Crovella, I.Matta 2000

9. Virtual losses Packet losses real loss: dropped packets virtual loss: ACK arrives, but after the RTO period, so the packet is retransmitted • 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: ??

10. Virtual losses bursty background traffic heavily fluctuating queuing time heavily fluctuating round-trip time 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)

11. 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)

12. Simulations We found self-similarity in the flow: Hvariance=0.86

13. Simulations the traffic is self-similar, BUT: • 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 What is the cause of self-similarity in our case?

14. Simulations Backoff statistics the cause of the self-similarity a = log2(1/2p) H = (3-a)/2, if a > 2 Hbackoff = 0.89 ( Hvariance= 0.86 ) peffective = 21% =><= preal = 0% (felt by the TCP)

15. Measurement • modified linux kernel (2.2.x series) • tcpdump • congested transcontinental line • packet inter arrival timeand backoff statistics • separate of real and virtual loss

16. Measurement Self-similarity of the flow, Hurst exponent Packet inter arrival distribution Variance-time plot H=0.70 H=0.69

17. Measurement Backoff statistics backoff values - time backoff probability distribution k=1,…,15 ploss=16.5%, Hbackoff=0.70

18. Measurement Packet loss detection and separation: tcpdump Real packet loss Virtual loss p ¼ 6.5% congested route p ¼ 10 –12% peffective¼ 16 – 18%

19. Measurement TCP is backed off, by: • real loss (dropped) • virtual loss (only delayed and timed out) • loss ratio from backoff statistics, p=16.5% • loss ratio calculated from tcpdump output: real, effective (real+virtual) losses pbackoff = peffective = preal + pvirtual¹ preal

20. 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