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The Temporal and Topological Characteristics of BGP Path Changes

The Temporal and Topological Characteristics of BGP Path Changes. Di-Fa Chang Ramesh Govindan John Heidemann USC/Information Sciences Institute. Presented by Ram Sudhir Nandyala February 3, 2005. Goal: To understand the changes of inter-domain routing. ?. How to Know?.

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The Temporal and Topological Characteristics of BGP Path Changes

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  1. The Temporal and Topological Characteristics of BGP Path Changes Di-Fa Chang Ramesh Govindan John Heidemann USC/Information Sciences Institute Presented by Ram Sudhir Nandyala February 3, 2005

  2. Goal: To understand the changes of inter-domain routing ?

  3. How to Know? • Specifically, • How frequently routing events occur? • Where do they take place? • How many routes do they change? • However, we have only sparse monitoring infrastructure to answer these questions.

  4. Existing Public Monitoring Infrastructure • Looking glasses (provided by ISPs) • Active probing per user request. • Provide router-level routing information. • The monitored space is small. • BGP vantage points (connected to RouteViews and RIPE RRC) • Passive monitoring. • Provide AS-level routing information. • The monitored space is relatively broad. • We start with the analysis of RouteViews datasets.

  5. Challenges • To establish the relation between • Path changes observed by vantage points and • Routing events taking place in some AS peerings. • Constraints: • The routing events are unknown. • The routing messages don’t contain information about the events. • The propagation timing of routing messages is unknown.

  6. b c a x o e d y Example: Network Topology Vantage Points Origin ASfor prefix p1

  7. b c a x o e d y Example: Original Paths Vantage Points Origin ASfor prefix p1 • Path x -> o: (x, a, b, c, o) • Path y -> o: (y, b, c, o)

  8. b c a x o e d y Example: Routing Event Vantage Points Origin ASfor prefix p1 • Path x -> o: (x, a, d, e, c, o) • Path y -> o: (y, d, e, c, o)

  9. Example: Observed Path Changes b c a x o e d y Vantage Points Origin ASfor prefix p1 • VP in AS-x observes • Time: 0 Path: (x, a, b, c, o)  initial path

  10. b c a x o e d y Example: Observed Path Changes Vantage Points Origin ASfor prefix p1 • VP in AS-x observes • Time: 0 Path: (x, a, b, c, o) • Time: 10 Path: withdrawn  initial path

  11. b c a x o e d y Example: Observed Path Changes Vantage Points Origin ASfor prefix p1 • VP in AS-x observes • Time: 0 Path: (x, a, b, c, o) • Time: 10 Path: withdrawn • Time: 35 Path: (x, a, d, e, c, o)  initial path  converged path

  12. b c a x o e d y Example: Observed Path Changes Vantage Points Origin ASfor prefix p1 initial path  • VP in AS-y observes • Time: 0 Path: (y, b, c, o)

  13. b c a x o e d y Example: Observed Path Changes Vantage Points Origin ASfor prefix p1 initial path  transient path  • VP in AS-y observes • Time: 0 Path: (y, b, c, o) • Time: 11 Path: (y, d, b, c, o)

  14. b c a x o e d y Example: Observed Path Changes Vantage Points Origin ASfor prefix p1 initial path  transient path  converged path  • VP in AS-y observes • Time: 0 Path: (y, b, c, o) • Time: 11 Path: (y, d, b, c, o) • Time: 30 Path: (y, d, e, c, o)

  15. b c a x o e d y Example: Observed Path Changes Vantage Points Origin ASfor prefix p1 • VP in AS-x observes • Time: 0 Path: (x, a, b, c, o) • Time: 10 Path: withdrawn • Time: 35 Path: (x, a, d, e, c, o) • VP in AS-y observes • Time: 0 Path: (y, b, c, o) • Time: 11 Path: (y, d, b, c, o) • Time: 30 Path: (y, d, e, c, o)

  16. b c a x e d y Example: Original Paths Origin ASfor prefix p2 Vantage Points • Path x -> o: (x, a, b, c) • Path y -> o: (y, b, c)

  17. b c a x e d y Example: Routing Event Origin ASfor prefix p2 Vantage Points • Path x -> o: (x, a, d, e, c) • Path y -> o: (y, d, e, c)

  18. b c a x e d y Example: Observed Path Changes Origin ASfor prefix p2 Vantage Points • VP in AS-x observes • Time: 0 Path: (x, a, b, c) • Time: 30 Path: (x, a, d, e, c) • VP in AS-y observes • Time: 0 Path: (y, b, c) • Time: 11 Path: (y, d, b, c) • Time: 29 Path: withdrawn • Time: 50 Path: (y, d, e, c)

  19. Example: Observed Path Changes • VP in AS-x observes Time Prefix Path 10 p1 withdrawn 30 p2 (x, a, d, e, c) 35 p1 (x, a, d, e, c, o) • VP in AS-y observes Time Prefix Path 11 p1 (y, d, b, c, o) 11 p2 (y, d, b, c) 29 p2 withdrawn 30 p1 (y, d, e, c, o) 50 p2 (y, d, e, c)

  20. Example: Observed Path Changes • VP in AS-x observes Time Prefix Path 4 p3 (x, a) 10 p1 withdrawn 25 p3 withdrawn 25 p4 (x, a, d) 26 p3 (x, a) 27 p5 withdrawn 28 p6 (x, a, d) 30 p2 (x, a, d, e, c) 32 p7 (x, a, d, e) 33 p6 withdrawn 35 p1 (x, a, d, e, c, o) 42 p5 (x, a, b) 42 p8 (x, a, d) 45 p7 withdrawn 47 p8 (x, a, b, d) 50 p5 withdrawn • VP in AS-y observes Time Prefix Path 6 p8 withdrawn 8 p3 (y, b, a) 10 p4 withdrawn 11 p1 (y, d, b, c, o) 11 p2 (y, d, b, c) 25 p5 withdrawn 28 p6 (y, d) 29 p2 withdrawn 30 p1 (y, d, e, c, o) 31 p8 (y, b, d) 32 p3 (y, d, a) 48 p4 (y, d) 48 p7 withdrawn 49 p6 withdrawn 49 p5 (y, b) 50 p2 (y, d, e, c)

  21. Message Correlation Problem • How to find the routing messages triggered by the same events in the stream of BGP updates? • Difficulties: • Number of transient path changes is unknown. • Number of prefixes affected is unknown. • Number of events happened is unknown. • Number of observing vantage points is unknown.

  22. Peering Location Problem • How can we locate the candidate peerings where the event takes place?

  23. Peering Location Problem • How can we locate the candidate peerings where the event takes place? • VP in AS-x observes Time Prefix Path 0 p1 (x, a, b, c, o) 10 p1 withdrawn 35 p1 (x, a, d, e, c, o) • VP in AS-y observes Time Prefix Path 0 p1 (y, b, c, o) 11 p1 (y, d, b, c, o) 30 p1 (y, d, e, c, o)

  24. c a b x o e d y Peering Location Problem • How can we locate the candidate peerings where the event takes place? • VP in AS-x observes Time Prefix Path 0 p1 (x, a, b, c, o) 10 p1 withdrawn 35 p1 (x, a, d, e, c, o) • VP in AS-y observes Time Prefix Path 0 p1 (y, b, c, o) 11 p1 (y, d, b, c, o) 30 p1 (y, d, e, c, o) • Example: (d, e) • High local_pref • Recover from previous failure

  25. b c c a a b x x o o e e d d y y b c c a b a x x o o e e d d y y c a b b c a x x o o e e d d y y b c b a c a x x o o e e d d y y Which Peerings Can Cause The Path Change?

  26. Peering Locating Problem (cont.) • Hint: The candidate peerings include those peerings that appears only in the original paths or the new paths.

  27. b c a x o e d y Peering Locating Problem (cont.) • Hint: The candidate peerings include those peerings that appears only in the original paths or the new paths. • VP in AS-x observes Time Prefix Path 0 p1 (x, a, b, c, o) 10 p1 withdrawn 35 p1 (x, a, d, e, c, o) • VP in AS-y observes Time Prefix Path 0 p1 (y, b, c, o) 11 p1 (y, d, b, c, o) 30 p1 (y, d, e, c, o)

  28. Methodology • Cluster the BGP updates triggered by the same routing event into one group based on: • Temporal Relation: the receiving time. • Topological Relation: prefix, peerings of the path. • Two-step clustering: • Prefix-based: for message correlation problem. • Peering-based: for peering location problem.

  29. Prefix-based Clusters • A sequence of path advertisements for the same prefix that are sent by the same vantage point and closely spaced in time.

  30. Prefix-based Clusters • A sequence of path advertisements for the same prefix that are sent by the same vantage point and closely spaced in time. • VP in AS-x observes Time Prefix Path 4 p3 (x, a) 10 p1 withdrawn 25 p3 withdrawn 25 p4 (x, a, d) 26 p3 (x, a) 27 p5 withdrawn 28 p6 (x, a, d) 30 p2 (x, a, d, e, c) 32 p7 (x, a, d, e) 33 p6 withdrawn 35 p1 (x, a, d, e, c, o) 42 p5 (x, a, b) 42 p8 (x, a, d) 45 p7 withdrawn 47 p8 (x, a, b, d) 50 p5 withdrawn • VP in AS-y observes Time Prefix Path 6 p8 withdrawn 8 p3 (y, b, a) 10 p4 withdrawn 11 p1 (y, d, b, c, o) 11 p2 (y, d, b, c) 25 p5 withdrawn 28 p6 (y, d) 29 p2 withdrawn 30 p1 (y, d, e, c, o) 31 p8 (y, b, d) 32 p3 (y, d, a) 48 p4 (y, d) 48 p7 withdrawn 49 p6 withdrawn 49 p5 (y, b) 50 p2 (y, d, e, c)

  31. Prefix-based Clusters • A sequence of path advertisements for the same prefix that are sent by the same vantage point and closely spaced in time. • VP in AS-x observes Time Prefix Path 4 p3 (x, a) 10 p1 withdrawn 25 p3 withdrawn 25 p4 (x, a, d) 26 p3 (x, a) 27 p5 withdrawn 28 p6 (x, a, d) 30 p2 (x, a, d, e, c) 32 p7 (x, a, d, e) 33 p6 withdrawn 35 p1 (x, a, d, e, c, o) 42 p5 (x, a, b) 42 p8 (x, a, d) 45 p7 withdrawn 47 p8 (x, a, b, d) 50 p5 withdrawn • VP in AS-y observes Time Prefix Path 6 p8 withdrawn 8 p3 (y, b, a) 10 p4 withdrawn 11 p1 (y, d, b, c, o) 11 p2 (y, d, b, c) 25 p5 withdrawn 28 p6 (y, d) 29 p2 withdrawn 30 p1 (y, d, e, c, o) 31 p8 (y, b, d) 32 p3 (y, d, a) 48 p4 (y, d) 48 p7 withdrawn 49 p6 withdrawn 49 p5 (y, b) 50 p2 (y, d, e, c) <= T1 > T1

  32. Prefix-based Clusters • A sequence of path advertisements for the same prefix that are sent by the same vantage point and closely spaced in time. • VP in AS-x observes Time Prefix Path 4 p3 (x, a) 10 p1 withdrawn 25 p3 withdrawn 25 p4 (x, a, d) 26 p3 (x, a) 27 p5 withdrawn 28 p6 (x, a, d) 30 p2 (x, a, d, e, c) 32 p7 (x, a, d, e) 33 p6 withdrawn 35 p1 (x, a, d, e, c, o) 42 p5 (x, a, b) 42 p8 (x, a, d) 45 p7 withdrawn 47 p8 (x, a, b, d) 50 p5 withdrawn • VP in AS-y observes Time Prefix Path 6 p8 withdrawn 8 p3 (y, b, a) 10 p4 withdrawn 11 p1 (y, d, b, c, o) 11 p2 (y, d, b, c) 25 p5 withdrawn 28 p6 (y, d) 29 p2 withdrawn 30 p1 (y, d, e, c, o) 31 p8 (y, b, d) 32 p3 (y, d, a) 48 p4 (y, d) 48 p7 withdrawn 49 p6 withdrawn 49 p5 (y, b) 50 p2 (y, d, e, c) <= T1 converged path > T1

  33. Prefix-based Clusters • A sequence of path advertisements for the same prefix that are sent by the same vantage point and closely spaced in time. • VP in AS-x observes Time Prefix Path 4 p3 (x, a) 10 p1 withdrawn 25 p3 withdrawn 25 p4 (x, a, d) 26 p3 (x, a) 27 p5 withdrawn 28 p6 (x, a, d) 30 p2 (x, a, d, e, c) 32 p7 (x, a, d, e) 33 p6 withdrawn 35 p1 (x, a, d, e, c, o) 42 p5 (x, a, b) 42 p8 (x, a, d) 45 p7 withdrawn 47 p8 (x, a, b, d) 50 p5 withdrawn • VP in AS-y observes Time Prefix Path 6 p8 withdrawn 8 p3 (y, b, a) 10 p4 withdrawn 11 p1 (y, d, b, c, o) 11 p2 (y, d, b, c) 25 p5 withdrawn 28 p6 (y, d) 29 p2 withdrawn 30 p1 (y, d, e, c, o) 31 p8 (y, b, d) 32 p3 (y, d, a) 48 p4 (y, d) 48 p7 withdrawn 49 p6 withdrawn 49 p5 (y, b) 50 p2 (y, d, e, c) cluster 10 (ab,bc,ad, de,ec)

  34. Prefix-based Clusters • A sequence of path advertisements for the same prefix that are sent by the same vantage point and closely spaced in time. • VP in AS-x observes Time Prefix Path 4 p3 (x, a) 10 p1 withdrawn 25 p3 withdrawn 25 p4 (x, a, d) 26 p3 (x, a) 27 p5 withdrawn 28 p6 (x, a, d) 30 p2 (x, a, d, e, c) 32 p7 (x, a, d, e) 33 p6 withdrawn 35 p1 (x, a, d, e, c, o) 42 p5 (x, a, b) 42 p8 (x, a, d) 45 p7 withdrawn 47 p8 (x, a, b, d) 50 p5 withdrawn • VP in AS-y observes Time Prefix Path 6 p8 withdrawn 8 p3 (y, b, a) 10 p4 withdrawn 11 p1 (y, d, b, c, o) 11 p2 (y, d, b, c) 25 p5 withdrawn 28 p6 (y, d) 29 p2 withdrawn 30 p1 (y, d, e, c, o) 31 p8 (y, b, d) 32 p3 (y, d, a) 48 p4 (y, d) 48 p7 withdrawn 49 p6 withdrawn 49 p5 (y, b) 50 p2 (y, d, e, c) cluster 10 (ab,bc,ad, de,ec)

  35. Prefix-based Clusters • A sequence of path advertisements for the same prefix that are sent by the same vantage point and closely spaced in time. • VP in AS-x observes Time Prefix Path 4 p3 (x, a) 10 p1 withdrawn 25 p3 withdrawn 25 p4 (x, a, d) 26 p3 (x, a) 27 p5 withdrawn 28 p6 (x, a, d) 30 p2 (x, a, d, e, c) 32 p7 (x, a, d, e) 33 p6 withdrawn 35 p1 (x, a, d, e, c, o) 42 p5 (x, a, b) 42 p8 (x, a, d) 45 p7 withdrawn 47 p8 (x, a, b, d) 50 p5 withdrawn • VP in AS-y observes Time Prefix Path 6 p8 withdrawn 8 p3 (y, b, a) 10 p4 withdrawn 11 p1 (y, d, b, c, o) 11 p2 (y, d, b, c) 25 p5 withdrawn 28 p6 (y, d) 29 p2 withdrawn 30 p1 (y, d, e, c, o) 31 p8 (y, b, d) 32 p3 (y, d, a) 48 p4 (y, d) 48 p7 withdrawn 49 p6 withdrawn 49 p5 (y, b) 50 p2 (y, d, e, c) 4 (xa) 10 (ab,bc,ad, de,ec) 25 (xa) 27 (xa) 28 (xa) 30 (ab,bc,ad, de,ec) 32 (xa) 42 (xa) 6 (bd) 8 (ba) 10 (yd) 11 (yb,bc,yd, de,ec) 11 (yb,bc,yd, de,ec) 25 (yb) 28 (yd) 48 (yd)

  36. Peering-based Clusters • A sequence of prefix-based clusters that are closely spaced in time and have at least one candidate peerings. 4 (xa) 10 (ab,bc,ad, de,ec) 25 (xa) 27 (xa) 28 (xa,ad) 30 (ab,bc,ad, de,ec) 32 (xa) 42 (xa) 6 (bd) 8 (ba) 10 (yd) 11 (yb,bc,yd, de,ec) 11 (yb,bc,yd, de,ec) 25 (yb) 28 (yd) 48 (yd)

  37. Peering-based Clusters • A sequence of prefix-based clusters that are closely spaced in time and have at least one candidate peerings. 4 (xa) 6 (bd) 8 (ba) 10 (ab,bc,ad,de,ec) 11 (yb,bc,yd,de,ec) 11 (yb,bc,yd.de,ec) 25 (yb) 25 (xa) 27 (xa) 28 (yd) 28 (xa,ad) 30 (ab,bc,ad,de,ec) 32 (xa) 42 (xa) 48 (yd) 4 (xa) 10 (ab,bc,ad, de,ec) 25 (xa) 27 (xa) 28 (xa,ad) 30 (ab,bc,ad, de,ec) 32 (xa) 42 (xa) 6 (bd) 8 (ba) 10 (yd) 11 (yb,bc,yd, de,ec) 11 (yb,bc,yd, de,ec) 25 (yb) 28 (yd) 48 (yd)

  38. Peering-based Clusters • A sequence of prefix-based clusters that are closely spaced in time and have at least one candidate peerings. 4 (xa) 6 (bd) 8 (ba) 10 (ab,bc,ad,de,ec) 11 (yb,bc,yd,de,ec) 11 (yb,bc,yd.de,ec) 25 (yb) 25 (xa) 27 (xa) 28 (yd) 28 (xa,ad) 30 (ab,bc,ad,de,ec) 32 (xa) 42 (xa) 48 (yd) <= T2 > T2

  39. Peering-based Clusters • A sequence of prefix-based clusters that are closely spaced in time and have at least one candidate peerings. 4 (xa) 6 (bd) 8 (ba) 10 (ab,bc,ad,de,ec) 11 (yb,bc,yd,de,ec) 11 (yb,bc,yd.de,ec) 25 (yb) 25 (xa) 27 (xa) 28 (yd) 28 (xa,ad) 30 (ab,bc,ad,de,ec) 32 (xa) 42 (xa) 48 (yd) 10 (bc,de,ec)

  40. Peering-based Clusters • A sequence of prefix-based clusters that are closely spaced in time and have at least one candidate peerings. 4 (xa) 6 (bd) 8 (ba) 10 (ab,bc,ad,de,ec) 11 (yb,bc,yd,de,ec) 11 (yb,bc,yd.de,ec) 25 (yb) 25 (xa) 27 (xa) 28 (yd) 28 (xa,ad) 30 (ab,bc,ad,de,ec) 32 (xa) 42 (xa) 48 (yd) Event occurs at time-10. 10 (bc,de,ec) 3 candidate peerings

  41. Experimental Data • Dataset: BGP updates from RouteViews from July 2002 to June 2003. • 31 vantage points in 24 ASes. • 1.68 billion path advertisements. • 62%: AS_PATH changes. • Experiments • Prefix-based clustering: T1 = 60, 120, 240 seconds • Peering-based clustering: T2 = 30, 60, 90 seconds • Results are similar for T1 , T2 we studied.

  42. How Many Path Changes Per Event? • Prefix-based clustering: ~50% of clusters have only one path advertisement. • MinRouteAdver rating limiting is effective. • Peering-based clustering: median number of path advertisements is 8-9. • Not all vantage points see each event.

  43. What Is The Impact of Event? • There are ~4,000 peering-based clusters per hour. • Median number of prefixes in a cluster is 2. • Most events have only local impact. • But a few events can affect tens of thousands of prefixes.

  44. Where Events Happen? • 47% of clusters are caused by routing events in transit peerings. These clusters consist of at least 50% of all path advertisements. • Question: Is Internet core more unstable than edges? • Near-far problem: vantage points receives more routing messages when events occur in near peerings than far peerings.

  45. Summary • Summary • MinRouteAdver rate limiting mechanism is effective. • Most events have only local impact. • Open question: does Internet core change more frequently than edges? • Future work • Parameter evaluation • Validation

  46. Question?

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