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A Case Study in Understanding OSPFv2 and BGP4 Interactions Using Efficient Experiment Design

A Case Study in Understanding OSPFv2 and BGP4 Interactions Using Efficient Experiment Design. David Bauer † , Murat Yuksel ‡ , Christopher Carothers † and Shivkumar Kalyanaraman ‡ † Department of Computer Science ‡ Department of Electrical, Computer and Systems Engineering

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A Case Study in Understanding OSPFv2 and BGP4 Interactions Using Efficient Experiment Design

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  1. A Case Study in Understanding OSPFv2 and BGP4 Interactions Using Efficient Experiment Design David Bauer†, Murat Yuksel‡, Christopher Carothers† and Shivkumar Kalyanaraman‡ †Department of Computer Science ‡Department of Electrical, Computer and Systems Engineering Rensselaer Polytechnic Institute

  2. Problem Statement Design Complexity Parameter Space: fixed inputs, protocol timers, decision algorithm Highly Detailed Models Computational Complexity Models: BGP4, OSPFv2, TCP-Reno, IPv4 • ROSS.Net built and utilized to address both parts of the problem • Goal: “good results fast” leading to an understanding of the system under test (make sense of the results)

  3. Response Surface • Understand protocol interactions through UPDATE messages generated by and between protocols • OO: OSPF caused OSPF Updates • BO: BGP caused OSPF Updates • BB: BGP caused BGP Updates • OB: OSPF caused BGP Updates OSPFv2 INTERACTION BGP4 INTERACTION

  4. Why Are Feature Interactions Harmful? • Network protocol weaknesses are not fully understand until implemented / simulated in the large-scale • Are decisions made to efficiently route data within a domain adversely affecting our ability to efficiently route data across the domain? • Hot-potato routing: small degree of unstable information affects large portion of traffic • Cold potato routing AS 0 AS 1 AS 2 Local Policy: optimize routing within AS (OSPFv2) Local Policy: optimize routing between ASes (BGP4) Global Policy: optimize routing within and between ASes

  5. Large-scale Simulation EBONE: AS 1755 iBGP: 16,384 OSPFv2: Routers: 438 Links: 1,192 • Topology from Rocketfuel data • Network Hierarchy: • Level 0 routers: 9.92 Gb/sec and 1 ms delay • Level 1 routers: 2.48 Gb/sec and 2 ms delay • Level 2 routers: 620 Mb/sec and 3 ms delay • Level 3 routers: 155 Mb/sec and 50 ms delay • Level 4 routers: 45 Mb/sec and 50 ms delay • Level 5 routers and below: 1.55 Mb/sec and 50 ms delay 8 6 12 EXODUS: AS 3967 iBGP: 50,176 eBGP: 53 OSPFv2: Routers: 688 Links: 2,166 12 9 12 ABOVENET: AS 6461 iBGP: 2,500 eBGP: 199 OPSFv2: Routers: 843 Links: 2,667 Tiscali: AS 3257 iBGP: 441 eBGP: OSPFv2: Routers: 618 Links: 839 18 26 LEVEL 3: AS 3356 iBGP: 7,921 eBGP: 210 OSPFv2: Routers: 2,064 Links: 8,669 161 11

  6. Experiment Design and Analysis • Three classes of protocol parameters: • OSPF timers, BGP timers, BGP decision • RRS was allowed 200 trials to optimize (minimize) response surface • Heuristic search algorithm • Applied multiple linear regression analysis on the results

  7. Response Plane • Intra-domain routing decisions can effect inter-domain behavior, and vice versa. • All updates belong to either of four categories: • OSPF-caused OSPF (OO) update • OSPF-caused BGP (OB) update – interaction • BGP-caused OSPF (BO) update – interaction • BGP-caused BGP (BB) update OB Update Destination 10 8 Link failure or cost increase (e.g. maintenance)

  8. Response Plane • Intra-domain routing decisions can effect inter-domain behavior, and vice versa. • All updates belong to either of four categories: • OSPF-caused OSPF (OO) update • OSPF-caused BGP (OB) update • BGP-caused OSPF (BO) update • BGP-caused BGP (BB) update BO Update Destination eBGP connectivity becomes available These interactions cause route changes to thousands of IP prefixes, i.e. huge traffic shifts!!

  9. ~15% improvement when BGP timers included in search space High Level Characterization • Optimized with respect to OB+BO response surface. • BGP timers play the major role, i.e. ~15% improvement in the optimal response. • BGP KeepAlive timer seems to be the dominant parameter.. – in contrast to expectation of MRAI! • OSPF timers effect little, i.e. at most 5%. • low time-scale OSPF updates do not effect BGP.

  10. Important to optimize OSPF Important to optimize OSPF Important to optimize OSPF Important to optimize OSPF Global perspective 20-25% better than local perspectives Design 1: Mgt Perspectives Minimize total BO+OB 15-25% better than other metrics • Varied response surfaces -- equivalent to a particular management approach. • Importance of parameters differ for each metric. • For minimal total updates: • Local perspectives are 20-25% worse than the global. • For minimal total interactions: • 15-25% worse can happen with other metrics • OB updates are more important than BO updates (i.e. ~0.1% vs. ~50%) OB: ~50% of total updates BO: ~0.1% of total updates

  11. Design 2: Hot- v Cold-Potato Routing • Q: Can we use this approach to provide guidance for network routing policies? • Performed full factorial of RRS searches, turning Hot-, Cold-potato routing ON/OFF • Provide quantitative results from which qualitative stmts can be made • Verified AT&T and Sprint measurements No major impact regardless of search performed Majority of UPDATEs were generated by LOCAL-Pref and AS Path length Larger question: Which steps in the BGP decision making algorithm are most important? MED was << 1% of UPDATEs Hot Potato was 0.8%

  12. Design 3: Network Robustness Response tied to link stability BGP parameters had greatest impact • Q: Can we use this approach to provide network admins with guidance for network configurations? • Link status varied with uniform random probability over simulation runtime • Link weights varied with uniform random probability over simulation runtime • Response: BO + OB, Global Persp, and Default network settings • Search consistently provides better results By maximizing link failure detection times, UPDATEs most effectively minimized

  13. Conclusions • Number of experiments were reduced by many orders of magnitude in comparison to Full Factorial • Experiment design and statistical analysis enabled rapid elimination of insignificant parameters • Several qualitative statements and system characterizations could be obtained with few experiments. • Provided validation of network measurement community results, and called into question importance of premises • Search algorithms do not always find desired behaviour • Allowed me to complete my thesis and graduate!

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