Network Simulation and Testing

1. Network Simulation and Testing Polly Huang EE NTU http://cc.ee.ntu.edu.tw/~phuang phuang@cc.ee.ntu.edu.tw

2. Dynamics Papers • Hongsuda Tangmunarunkit, Ramesh Govindan, and Scott Shenker. Internet path inflation due to policy routing. In Proceedings of the SPIE ITCom, pages 188-195, Denver, CO, USA, August 2001. SPIE • Lixin Gao. On inferring automonous system relationships in the internet. ACM/IEEE Transactions on Networking, 9(6):733-745, December 2001 • Vern Paxson. End-to-end internet packet dynamics. ACM/IEEE Transactions on Networking, 7(3):277-292, June 1999 • Craig Labovitz, G. Robert Malan, Farnam Jahanian. Internet Routing Instability. ACM/IEEE Transactions on Networking, 6(5):515-528, October 1998

3. Doing Your Own Analysis • Having a problem • Need to simulate or to test • Define experiments • Base scenarios • Scaling factors • Metrics of investigation

4. Base Scenarios • The source models • To generate traffic • The topology models • To generate the network • Then?

5. Policy routing Packet/Route dynamics Internet Dynamics • How traffic flow across the network • Routing • Shortest path? • How failures occur • Packets dropped • Routes failed • i.i.d?

6. Identifying Internet Dynamics Routing Policy Packet Dynamics Routing Dynamics

7. To the best of our knowledge, we could now generate: AS-level topology Hierarchical router-level topology

8. The Problem • Does it matter what routing computation we use? • Equivalent of • Can I just do shortest path computation?

9. Topology with Policy • Internet Path Inflation Due to Policy Routing • Hongsuda Tangmunarunkit, Ramesh Govindan, Scott Shenker • In Proceedings of the SPIE ITCom, pages 188-195, Denver, CO, USA, August 2001. SPIE

10. Paper of Choice • Methodological value • A simple ‘re-examine’ type of study • To strengthen technical value of prior work • Technical value • Actual paths are not the shortest due to routing policy. • The routing policy is business-driven and can be quite hard to obtain. • Shown in this paper, for simulation study concerning large-scale route path characteristics, a simple shortest-AS policy routing may be sufficient.

11. shortest Inter-AS Routing AS 2 AS 3 source destination AS 1 AS 5 AS 4

12. Intra-AS shortest Inter-AS shortest Hierarchical Routing destination source

13. shortest Flat Routing destination source

14. 5:3 Hierarchical Routing is not optimal Or Routes are inflated

15. How sub-optimal?

16. Prior Work • Based on • An actual router-level graph • An actual AS-level graph at the same time • Overlay the AS-level graph on the router-level graph • Compute • For each source-destination pair • Shortest path using hierarchical routing • Shortest path using flat routing • Compare route length • In number of router hops

17. Prior Conclusions • 80% of the paths are inflated • 20% of the paths are inflated > 50% • There exists a better detour for 50% of the source-destination pairs • There exists an intermediate node i such that Length(s-i-d) < Length(s-d)

18. This Work • To address 2 shortcomings • There’s now a newer router-level graph • There’s now a more sophisticated policy model • Paper #4 • Inter-AS routing is not quite ‘shortest-AS routing’

19. Newer vs. Older Graph • Inflation difference not the same • Difference is larger in the newer graph • Due to the newer graph being larger • Inflation ratio remains the same

20. Shortest-AS vs. Policy-AS Routing • Shortest-AS • Simplified model • Every AS is equal • Policy-AS • Realistic model • Not all ASs are the same • Some are provider ASs • Some are customer ASs • Customer ASs do not transit traffic

21. Provider Customer Consider TANET CHT UUNET Through UUNET? TANET CHT NTU Through NTU?

22. Routing with Constraints • Routes could be • Going up • Going down • Going up and then down • Routes can never be • Going down and then up

23. Inferring the Constraints • On Inferring Autonomous System Relationships in the Internet • Lixin Gao • ACM/IEEE Transactions on Networking, 9(6):733-745, December 2001

24. Not All ASs the Same • 2 types of ASs • Customer • Provider • 3 types of Relationships • Customer-provider • Provider-provider • Peer-peer • Sibling-sibling

25. Customer-Provider • Formal definition • A provider transits for its customer • A customer does no transit for its provider • Informal • Provider: I’ll take any traffic • Customer: I’ll take only the traffic to me (or my customers)

26. Peer-Peer • Formal Definition • A provider does not transit for another provider • Informal • I’ll take only the traffic to me (or my customers) • You’ll take only the traffic to you (or your customers)

27. Sibling-Sibling • Formal Definition • A provider transits for another provider • Informal • I’ll take any traffic • You’ll take any traffic

28. Never “Going Down and then Up” • A provider-customer link can be followed by only • Provider-customer link • (Or sibling-sibling link) • A peer-peer link can be followed by only • Provider-customer link • (Or sibling-sibling link)

29. Heuristics • Compute out-degrees • For each AS path in routing tables • 1st AS with the max degree the root of hierarchy • From the root, drawing providercustomer relationship down 2 ends of the AS path

30. Determining Siblings • After gone through all AS paths • Any AS pair being both provider and customer to each other are siblings

31. Determining Peers • Do another pass on the AS paths in routing tables • For each AS path • Top AS who does not have sibling relationships with the neighboring ASs • Could have peering relationship with the higher out-degree neighbor • Given the Top AS and the higher out-degree neighbor are comparable in out-degree

32. Back to Path Inflation • Draw the customer-provider, peer-peer, and sibling-sibling relationships on the overlay AS graph • Compute the best routes under the ‘never going down and then up’ constraint • Compare the inflation difference and ratio again with these running at the inter-AS level • Shortest • Policy

33. Shortest vs. Policy Routing • Pretty much the same both in terms of • Inflation difference • Inflation ratio

34. Therefore • The observations from the prior work holds • With a newer graph • With the more realistic inter-AS policy routing

35. Now forget path inflation How far away is the shortest to the policy inter-AS routing?

36. Shortest vs. Policy • In AS hops • 95% paths have the same length • Policy routes always longer • In router hops • 84% paths have the same length • Some policy routes longer, some shorter

37. 95% and 84% are pretty good numbers Therefore shortest path at the inter-AS level might be OK…

38. To Answer the Question • Can we simply do shortest path computation? • A likely yes for AS-level graph • A firm no for hierarchical graph • Must separate inter-AS shortest and intra-AS shortest

39. Questions?

40. Identifying Internet Dynamics Routing Policy Packet Dynamics Routing Dynamics

41. It’s never a perfect world…

42. The Problem • But how perfect is the Internet? • The Internet • A network of computers with stored information • Some valuable, some relevant • You participate by putting information up or getting information down • From time to time, you can’t quite do some of these things you want to do

43. Why is that?

44. At the philosophical level… Humans are so bound to failures.And the Internet is human-made.

45. But, Seriously… Consider loading a Web page

46. Web Surfing Failures • The ‘window’ waving forever? • An error message saying network not reachable • An error message saying the server too busy • An error message saying the server is down • Anything else?

47. Network Specific Failures • The ‘window’ waving forever? • An error message saying network not reachable • An error message saying the server too busy • An error message saying the server is down • Anything else?

48. The Causes • The ‘window’ waving forever • Congestion in the network • Buffer overflow • Packet drops • An error message saying network not reachable • Network outage • Broken cables, Frozen routers • Route re-computation • Route instability

49. Back to the Problem • But how perfect is the Internet? • Equivalent of • Packets can be dropped • How frequent • How much • Routes may be unstable • How frequent • For how long

50. Significance • Knowing the characteristics of packet drops and route instability helps • Design for fault-tolerance • Test for fault-tolerance