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The Impact of Policy and Topology on Internet Routing Convergence NANOG 20 October 23, 2000 Abha Ahuja InterNap *In collaboration with.

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Presentation on theme: "The Impact of Policy and Topology on Internet Routing Convergence NANOG 20 October 23, 2000 Abha Ahuja InterNap *In collaboration with."— Presentation transcript:

1 The Impact of Policy and Topology on Internet Routing Convergence NANOG 20 October 23, 2000 Abha Ahuja InterNap *In collaboration with Roger Wattenhofer, Srinivasan Venkatachary, Madan Musuvathi Craig Labovitz Microsoft Research

2 2 Background In NANOG 19, we showed BGP exhibits poor convergence behavior: 1)Measured convergence times of up to 20 minutes for BGP path changes/failures 2)Factorial (N!) theoretic upper bound on BGP convergence complexity (explore all paths of all possible lengths) Open question: In practice, what topological and policy factors impact convergence delay ?

3 3 This Talk Goal: Understand BGP convergence behavior under real topologies/policies –Given a physical topology and ISP policies, can we estimate the time required for convergence? –Do convergence behaviors of ISPs differ? –How does steady-state topology compare to paths explored during failure? –Can we change policies/topology to improve BGP convergence times?

4 4 Experiments Analyzed secondary paths between between 20 source/destination AS pairs –Inject and monitor BGP faults –Survey providers to determine policies behind paths To provide intuition, we will focus on faults injected into three ISPs at Mae-West –Observed faults via fourth ISP (in Japan) –Three ISPs roughly map onto tier1, tier2, tier3 providers –Results from these three ISPs representative of all data

5 5 Comparing ISP Convergence Latencies CDF of faults injected into three Mae-West providers and observed at Japanese ISP Significant variations between providers Not related to geography

6 6 Observed Fault Injection Topologies In steady-state, topologies between ISP1, ISP2, ISP3 similar – all direct BGP peers of ISP4. Does not explain variation on previous slide… Steady State ISP 1 R1R1 FAULT ISP 4 ISP 2 R2R2 FAULT Steady State ISP 3 R3R3 FAULT Steady State MAE-WEST

7 7 Factors Impacting BGP Propagation Topology and policy impact graph (usually DAG) Each AS router adds between 0-45 seconds of MinRouteAdver Delay iBGP/Route Reflector MinRouteAdver and path race conditions affect which routes chosen as backup routes iBGP A B C D

8 8 ISP1-ISP4 Paths During Failure Only one back up path (length 3) Steady State ISP 1 ISP 5 P2 ISP 4 R1R1 FAULT 96%Average: 92 (min/max 63/140) seconds Announce AS4 AS5 AS1 (44 seconds) Withdraw(92 seconds) 4%Average: 32 (min/max 27/38) seconds Withdraw(32 seconds)

9 9 ISP2-ISP4 Paths During Failure Steady State ISP 2 ISP 4 P2 ISP 5 P3 ISP 6 R2R2 FAULT Vagabond P4 ISP 10 ISP 11 ISP 12 ISP 13 P4 63% Average: 79 (min/max 44/208) seconds AS4 AS5 AS2(35 seconds) Withdraw (79 seconds) 7% Average: 88 (min/max 80/94) seconds Announce AS4 AS5 AS2 (33 seconds) Announce AS4 AS6 AS5 AS2 (61 seconds) Withdraw (88 seconds) 7% Average: 54 (min/max 29/9) seconds Withdraw (54 seconds) 23% Other

10 10 ISP3-ISP4 Paths During Failure ISP 3 Steady State ISP 4 R3R3 P2 ISP 5 FAULT ISP 1 P3 P6 P7 P4 P5 P6 ISP 7 ISP 9 ISP 8 P7 P4 36% Average: 110 (min/max 78/135) seconds Announce AS4 AS5 AS (52 seconds) Withdraw (110 seconds) 35% Average: 107 (min/max 91/133) seconds Announce AS4 AS1 AS3 (39 seconds) Announce AS4 AS5 AS3 (68 seconds) Withdraw (107 seconds) 2% Average: (min/max 120/142) Announce AS4 AS5 AS8 AS7 AS3 (27) Announce AS4 AS5AS9 AS8 AS7 AS3(86) Withdraw (140 seconds) 27% Other

11 11 Why the Different Levels of Complexity? Provider relationship taxonomy –Transit relationships customer/provider customer sends their customer routes provider sends default-free routing info (or default) –Peer relationships Bilateral exchange of customer routes –Back-up transit peer relationship becomes transit relationship based on failure These relationships constrain topology (no N! states) and determine number of possible backup paths

12 12 Convergence in the Real World 1 customer peer X Longest path: Possible paths for node 3: 2 1 x x ( x) Possible paths for node 4: 2 1 x x x

13 13 Convergence in the Real World 1 customer peer X Longest path: Possible paths for node 3: 2 1 x x Possible paths for node 4: x x Hierarchy eliminates some states Tier 1?

14 14 Policy and Convergence Strict hierarchical relationships eliminate exploring some extra states –Policy controls the number of possible paths to explore. –But turns out the number of paths does not matter…

15 15 Relationship Between Backup Paths and Convergence Convergence related to length longest possible backup ASPath between two nodes Longest Observed ASPath Between AS Pair

16 16 So, what does all of this mean for convergence time? Convergence time is related to the length of the longest path that needs to be explored –Before fail-over, need to withdraw all alternative paths –This is bounded O(n) by length of the longest alternative path in the system –This longest path is related to policy

17 17 Towards Millisecond BGP Convergence Three possible solutions 1)Entirely new protocol 2)Turn off MinRouteAdver timer 3)“ Tag ” BGP updates –Provide hint so nodes can detect bogus state information

18 18 Further Information C. Labovitz, R. Wattenhofer, A. Ahuja, S. Venkatachary, “ The Impact of Topology and Policy on Delayed Internet Routing Convergence ”. MSR Technical Report (number pending). June, C. Labovitz, A. Ahuja, A. Bose, F. Jahanian, “ Internet Delayed Routing Convergence. ” To appear in Proceedings of ACM SIGCOMM. August, Send to for more information or to participate in the policy survey


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