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The Impact of Policy and Topology on Internet Routing Convergence NANOG 20 October 23, 2000 Abha Ahuja InterNap ahuja@umich.edu *In collaboration with Roger Wattenhofer, Srinivasan Venkatachary, Madan Musuvathi Craig Labovitz Microsoft Research labovit@microsoft.com

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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 ?

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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?

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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

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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

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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

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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

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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)

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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

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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:140.00 (min/max 120/142) Announce AS4 AS5 AS8 AS7 AS3 (27) Announce AS4 AS5AS9 AS8 AS7 AS3(86) Withdraw (140 seconds) 27% Other

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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

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12 Convergence in the Real World 1 customer peer 2 3 4 5 X Longest path: 3 4 5 2 1 Possible paths for node 3: 2 1 x 4 2 1 x (4 5 2 1 x) Possible paths for node 4: 2 1 x 3 2 1 x 5 2 1 x

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13 Convergence in the Real World 1 customer peer 2 3 4 5 X Longest path: 3 4 5 2 1 Possible paths for node 3: 2 1 x 4 5 2 1 x Possible paths for node 4: 3 2 1 x 5 2 1 x Hierarchy eliminates some states Tier 1?

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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…

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

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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

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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

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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, 2000. C. Labovitz, A. Ahuja, A. Bose, F. Jahanian, “ Internet Delayed Routing Convergence. ” To appear in Proceedings of ACM SIGCOMM. August, 2000. Send email to ipma-support@merit.edu for more information or to participate in the policy survey

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