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

CNL - Network Performance Measurement Group 2 Outline Motivations Self-similarity Karn’s Algorithm Backoff mechanism & Self-similar traffic Virtual loss Simulation Measurement Discussion

CNL - Network Performance Measurement Group 3 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

CNL - Network Performance Measurement Group 4 Self-similarity Hurst exponent: degree of self-similarity

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

CNL - Network Performance Measurement Group 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 T RTT and tries again If fails, waits 2 T RTT, 4 T RTT, 8 T RTT,... k = 1,…,6 denote backoff states of increasing depth

CNL - Network Performance Measurement Group 7 Backoff mechanism & Self-similar traffic Backoff probability distrributionEffective packet loss ratio A.Fekete, G.Vattay 2001 P k : probability of k th backoff state PkPk p effective where p: packet loss rate felt by the TCP P k+1 = (2p-p 2 ) P k, k=0,…,4

CNL - Network Performance Measurement Group 8 Backoff mechanism & Self-similar traffic Backoff probability distrributionHurst exponent packet sending process: ON/OFF process OFF periods: inter arrival times of packets Hurst parameter of such an aggregated traffic: => when < H < 1 H = (3-  )/2, if  > 2  = log 2 (1/2p) L.Guo, M.Crovella, I.Matta 2000 » t -(  +1)

CNL - Network Performance Measurement Group 9 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: ??

CNL - Network Performance Measurement Group 10 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 RTT real > RTO TCP => virtual loss occurs (the TCP doesn’t get ACK until RTO expires)

CNL - Network Performance Measurement Group 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) Link bandwidth1 Mbps Link delay1 ms Buffer size1000 pkts File size1000 pkts

CNL - Network Performance Measurement Group 12 Simulations We found self-similarity in the flow: H variance =0.86

CNL - Network Performance Measurement Group 13 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?

CNL - Network Performance Measurement Group 14 Simulations Backoff statistics the cause of the self-similarity ( H variance = 0.86 ) H backoff = 0.89 => <= p real = 0% (felt by the TCP) H = (3-  )/2, if  > 2  = log 2 (1/2p)

CNL - Network Performance Measurement Group 15 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

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

CNL - Network Performance Measurement Group 17 Measurement backoff values - time backoff probability distribution k=1,…,15 p loss =16.5%, H backoff =0.70 Backoff statistics

CNL - Network Performance Measurement Group 18 Measurement Packet loss detection and separation: tcpdump Real packet loss Virtual loss p ¼ 6.5% congested route p ¼ 10 –12% p effective ¼ 16 – 18%

CNL - Network Performance Measurement Group 19 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) p backoff = p effective  p real + p virtual  p real

CNL - Network Performance Measurement Group 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