1. Measuring the Spatial Structure of Traffic Congestion in the Internet Gábor Vattay Center for Communication Networks Data Analysis, Collegium Budapest Physics of Complex Systems, Eötvös University ELTE-Ericsson Research Communication Networks Laboratory

2. Spatial Structure of Internet Traffic The Blue Ocean Telecommunication Services and Computer Hardware Equipment is one of the most R&D intensive sectors (70 B$ R&D spending in 2005) Research spending traditionally goes into Electrical Engineering and Computer Science, Physics, Complexity is not on the horizon due to cultural problems While in biology, economy/finance there is traditional scientific competition, telecommunication is still a competition free Blue Ocean for complexity research Interdisciplinary research of Engineering and Complex Systems has a great perspective if log-logging is avoided

3. Inspiration from complex system side: What you need? Complex Network Selfsimilar Traffic Nonlinearity and Chaos

4. Spatial Structure of Internet Traffic Topology

5. Spatial Structure of Internet Traffic The Faloutsos Graph 1999

6. Spatial Structure of Internet Traffic Traffic

7. Spatial Structure of Internet Traffic Typical internet traffic traces W. E. Leland et al. SIGCOMM 93

8. Spatial Structure of Internet Traffic Chaos

9. Spatial Structure of Internet Traffic Chaos in Computer Networks

10. Spatial Structure of Internet Traffic Periodicity Veres & Boda INFOCOM 2000

11. Spatial Structure of Internet Traffic Chaos Veres & Boda INFOCOM 2000

12. Spatial Structure of Internet Traffic Ljapunov properties Veres & Boda INFOCOM 2000

13. Spatial Structure of Internet Traffic Strange attractor Veres & Boda INFOCOM 2000

14. Spatial Structure of Internet Traffic Active Internet measurements Internet: highly heterogeneous and decentralized why are we measuring state variables (e.g. loss-rates, delays, bandwith)? –to predict the quality of various services and applications over the Internet, –to construct more efficient transfer protocols, –to analyze the spatial structure of the traffic, etc. active probing : –injecting probe packets + analyzing the received probe stream –end-to-end information about the participating nodes –resolved information: only with the cooperation of routers

15. Spatial Structure of Internet Traffic Network Tomography Method: we send back-to-back packet pairs and measure their end-to-end delay at arrival with very high precision Goal : to resolve delay statistics on internal network segments too, where we do not have monitoring stations Key idea: delay correlation on the common segment for the packets in a pair

16. Spatial Structure of Internet Traffic Delay estimation for the Y-topology Definitions: N - number of successful pairs, where none of the probes is lost. and, the end-to-end delay experienced by the probes of the k-th pair Goal: Estimate the distribution of, and from the end-to-end delays. Quantization of the delay into B bins of uniform size q if,

17. Spatial Structure of Internet Traffic

18. EM-algorithm

19. Spatial Structure of Internet Traffic

20. Real and virtual measurement points

21. The etomic active probing infrastructure

22. Spatial Structure of Internet Traffic Best Testbed Award The European Traffic Observatory Measurement InfrastruCture (etomic) was created in 2004-05 within the Evergrow Integrated Project launched by the Future and Emergent Technologies Programme of the European Union. Its goals: – to provide an open access, public test bed for researchers investigating the Internet with active measurement methods –to serve as a Virtual Observatory active measurement data on the European part of the Internet History

23. Spatial Structure of Internet Traffic Founders Its Central Management System (CMS) has been developed by the Grupo de Redes, Sistemas y Servicios Telemáticos Departamento de Automática y Computación Universidad Pública de Navarra. Its hardware infrastructure has been designed and built by the Cooperative Center for Communication Network Data Analysis in Collegium Budapest Institute for Advanced Study. The measurement stations are hosted by European research groups collaborating in the Evergrow project.

24. Spatial Structure of Internet Traffic Measurement sites

25. Spatial Structure of Internet Traffic Visualization 2005.07.01. 3:30AM

26. Spatial Structure of Internet Traffic Visualization 2005.07.01. 3:30AM

27. Spatial Structure of Internet Traffic Topology of routers etomic stations routers

28. Spatial Structure of Internet Traffic Snapshot of queueing dealys in Europe

29. Spatial Structure of Internet Traffic Daily change of mean queuing delays

30. Spatial Structure of Internet Traffic Distribution of the mean queuing delay (night 3:30)

31. Spatial Structure of Internet Traffic Distribution of the mean queuing delay (afternoon 16:00)

32. Spatial Structure of Internet Traffic Distribution of the mean queuing delay (day 14:00)

33. Variance vs. mean Day Night Afternoon

34. Spatial Structure of Internet Traffic Main results Log-normal distribution of the delayVariance and delay are proportional

35. Future measuremnets

36. Spatial Structure of Internet Traffic Growing number of monitored links

37. Spatial Structure of Internet Traffic The DIMES project

38. Spatial Structure of Internet Traffic DIMES Agents in Europe

39. Spatial Structure of Internet Traffic Measurement sites Properly located Dimes agents (red) Branching routers (blue)

40. Spatial Structure of Internet Traffic Expectations 2. Number of Dimes agents Number of discovered segments/branching routers Newly discovered internal segments Newly discovered branching routers Traceroute between 257 Dimes agents and 15 Etomic nodes

41. Spatial Structure of Internet Traffic Thanks! IST Future and Emerging Technologies