1. Things You Can Do in Budapest During Summer Time Aleksandar Kuzmanovic Rice University & Ericsson Traffic Lab October 2001

2. Rice University & Ericsson Traffic Lab Budapest Buda-Pest –History –Architecture –Decadency… Ericsson Traffic Lab –Unix –Young people –Security

3. Rice University & Ericsson Traffic Lab People Ericsson Traffic Lab, Budapest –Andras Veres EMULab, The University of Melbourne –Attila Pasztor, Darryl Veitch Budapest University, Department of Physics –Gabor Simon, Gabor Vattay

4. Rice University & Ericsson Traffic Lab My Goals Modeling and reality?

5. Rice University & Ericsson Traffic Lab Active Probing Internal network inaccessible Poor understanding of origins of complex network dynamics Statistics is like the bikini… Goal: Estimate the sample path of cross-traffic

6. Rice University & Ericsson Traffic Lab Background Precise measurement infrastructure One way delay (sec) -> Packet departure time (sec) ->

7. Rice University & Ericsson Traffic Lab Probing Uncertainty Principle Should not allow queue to empty between probe packets Small T for accurate measurements –but probe traffic would disturb cross-traffic (and overflow bottleneck buffer!) Larger T leads to measurement uncertainties –queue could empty between probes

8. Rice University & Ericsson Traffic Lab Theory Lindley’s equation CT information imbedded in delay Ideal case: minimally backlogging condition [QK99]

9. Rice University & Ericsson Traffic Lab Design Space No time synchronization between end points $ 2.000.000.000 Delay difference Non-intrusiveness Stability Time (sec) -> One way delay (sec) ->

10. Rice University & Ericsson Traffic Lab Probing scheme

11. Rice University & Ericsson Traffic Lab Aside… Experiments on LAN Time-sharing in Linux Time (sec) -> Inter-arrival time (sec) ->

12. Rice University & Ericsson Traffic Lab Traffic Lab – Experiment Setup Tcpdump, iperf (HTTP, TCP), sender, receiver…

13. Rice University & Ericsson Traffic Lab Routes Tech. University Budapest 6 nec2.ttt.bme.hu (152.66.247.2) 14.980 ms 14.212 ms 14.252 ms Columbia University, NY 16 bongo.comet.columbia.edu (128.59. 64.210) 150.725 ms * 127.967 ms University of Melbourne 23 potoroo.ee.mu.OZ.AU (128.250.76.186) 384.271 ms 383.408 ms 382.977 ms Houston, we have a problem… -> Time (sec) -> One way delay (sec) ->

14. Rice University & Ericsson Traffic Lab Wide Area vs. Metropolitan Area Network

15. Rice University & Ericsson Traffic Lab Cross Traffic Estimation Sample Path Differentiate delay, know C Cross traffic: from: Budapest to: NY iperf - 1 TCP Probing traffic from: Budapest to: Melbourne

16. Rice University & Ericsson Traffic Lab Cross Traffic Estimation Moving Average

17. Rice University & Ericsson Traffic Lab Signs Delay difference => two queues => two cases

18. Rice University & Ericsson Traffic Lab Wide Area Network revisited Differentiation btw. primary (256K) & secondary (transatlantic) bottlenecks Secondary traffic underestimated for Csec./256K

19. Rice University & Ericsson Traffic Lab Primary & Secondary Bottlenecks LAN traffic controllable Separation between primary (256K) & secondary (LAN) cross traffic

20. Rice University & Ericsson Traffic Lab TCP Cross Traffic Iperf (number of TCP connections >=3) => delay decreases yet we see clusters of packet losses (queue size ~ delay~pck. loss?)

21. Rice University & Ericsson Traffic Lab Role of packet sizes => change packet size

22. Rice University & Ericsson Traffic Lab Bit/sec. vs. Packet/sec. Up: 540 Bytes Down: 60 Bytes 540/60 = 9 –256Kbps*9= 2.3Mbps UDP: 1500/30=50 –256K*50= 12.8Mbps - 1.5M*50= 75Mbps

23. Rice University & Ericsson Traffic Lab Secondary Bottleneck Difference of CT estimate and tcpdump CT followed by clusters of packet losses

24. Rice University & Ericsson Traffic Lab Role of TCP Secondary CT (necessary for losses*) picks up the periodicity of probe traffic! –Through losses –Through delay When phases match –Long burst of small packets causes losses on secondary bottleneck

25. Rice University & Ericsson Traffic Lab Ongoing work Short and long lived TCP connections Heterogeneous TCP traffic…

26. Rice University & Ericsson Traffic Lab Conclusions Scalable, edge-based tool for on-line network analysis, modeling, and measurement Scheme for estimating sample path of adaptive cross-traffic Differentiation between primary and secondary bottlenecks: two queue model Role of TCP (delay variation) and variable packet sizes –Low bit rate denial of service attack? –QoS in access networks (xDSL…)

27. Rice University & Ericsson Traffic Lab The End

28. Rice University & Ericsson Traffic Lab One more picture