ETOMIC measurementsin EVERGROW

Gábor VattayEötvös University/Collegium Budapest

Evergrow Traffic Observatory Measurement InfrastruCture

www.etomic.org

Brief history• 2002 Nov/Dec: UCSD, Caida, NLANR, NIMI … .

”build something which goes beyond present efforts” D. Veitch: fixed precise hardware + cloud of light weight agents

• 2003 Feb: S. Kirkpatrick, Y. Shavitt, J. Aracil, EVERGROW measurements (DIMES & ETOMIC)

• 2004 Spring: deployment (collaboration attempt with PlanetLab/Intel/C. Diot)

• 2004 Autumn: first measurements, Best European Testbed (TRIDENTCOM)

• 2005 March: IPS-MoMe (collaboration on databases/public data, GEANT) • 2005 further deployments: first large scale measurements, DIMES ETOMIC

measurements

• 2005 September: Cooperative Center for Communication Network Data Analysis Eötvös University, Collegium Budapest, Public Univ. Navarra, Tel Aviv, Notre Dame (Barabasi), TU Dresden (Helbing), UCSD INLS (Kocarev), Columbia, MS Research, Ericsson R&D, T-Com.hu ~ EUR 3 million

Iron

Parts of the infrastructure

WAN

WAN

IBM Blade Center

SWITCH/LAN

RS 422 max. 100 meters cable

1000BaseTX for DAG

1000BaseTX LAN

1000BaseTX LAN

PCPC with DAG with DAG

Precision: 100 ns – 1s in Global Time

GPS

The Endace card with patterned traffic generator• Single port full packet capture at 10/100/1000 Mbps

• precise time stamping with GPS global synchronization• sending out any pattern of configurable packets

DAG 3.6GE

Speed of light in cable

ETOMIC stations in Europe

Soul

Evergrow Traffic Observatory Management System (ETOMS)

designed by the group of Prof. J. Aracil at Public University of Navarra, Pamplona

Current measurements: 1. One way delay

• High precision propagation delay of IP packets

Change of end-to-end queuing delay in a 10 min. experiment

13

Current measurements: 2 Network Tomography

Getting delay statistics also from the interior of the network, where we don’t have monitoring stations

Shoot back-to-back packet pairs …and measure their delay at arrival with very high precision

msX 1832 msX 2283

msX 1751

15

16

17

18

19

20

21

22

23

24

25

26

27

28

29

30

31

32

33

34

35

Science

Daily change of Mean of queuing delays

38

Daily change of Variance of queuing delays

Distribution of the mean queuing delay (night 3:30)

40

Distribution of the mean queuing delay (afternoon 16:00)

Distribution of the mean queuing delay (day 14:00)

Red line is the best fit log-normal distribution

42

Variance vs. mean

Day

Night

Afternoon

Simulations

Future

Increasing ETOMIC (expensive, precise hardware)

It turns out, that only ”Receiver” should be precise …

Projection: with 300 standard nodes (DIMES, PlanetLab …) we can monitor perhaps 12.000 links

Special thanks to

• Javier Aracil and the Pamplona team• The DIMES team• The EVERGROW partners

• István Csabai (putting all together)• Péter Hága (Precise measurements)• Tamás Hettinger (Java simulations)• Péter Mátray (Google map visualization)• Gábor Simon (Tomography)• Norbert Solymosi (Spatial visualization)• József Stéger (DIMES-ETOMIC)