1. Packet train experiments in DIMES and ETOMIC Ohad Serfaty Joszef Steger May 2006

2. Preview PacketTrain Measurements Results and Difficulties Solutions Future work

3. PacketTrain measurement scheme UDP Packets Dimes Server Dimes Agents Port 7777 Etomic Agents Results are compressed and uploaded

4. Measurement automation Agents receive a script with Traceroutes commands and PacketTrain commands Etomic Agents receive a script with a listen command At the end of the listening period – The Etomic agents compress the results and send it to DIMES Results are inserted into the databases, spanning trees are created Tomography

5. PacketTrain experiment design Agents are picked, one from each user Etomic nodes are picked Each agent sends 10000 packet trains, in intervals of 50ms-100ms

6. PacketTrain experiments We conducted 4 full experiments 2 Partial experiments 10/5/2006 - 11/5/2006 140 Dimes Agents, 4 Etomic nodes 2 Large scale experiments 28/5/2006 30/5/2006 241 Dimes Agents, 9 Etomic nodes

7. Results - Agent 4827

9. Spanning tree – Agent 5245

10. Messy Time series

12. Messy Spanning Tree

13. Geographic span

14. Tomography requirements Well behaved time series Well behaved Traceroute spanning tree Exact match between Agent and IP

15. Analysis obstacles Indefinite slope in time series Too many packets from the same IP Traceroute data is corrupt No accurate matching between Agent and IP address Solution : Traceroute back to the client

16. Java Network Stack Encapsulated Packet send / receive Cross platform : windows, Linux, Mac and Etomic Java - Write once run anywhere Will be the base of future DIMES measurements Traceroute back to the Agent

17. IP to agent matching

21. Future work Add Agent id to Packet train module Tomography analysis Install a measurement infrastructure similar to DIMES on colbud cluster