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Presented by Pierre-Élie Fauché 1 XL: An Efficient Network Routing Algorithm Kirill Levchenko Geoffrey M. Voelker, Ramamohan Paturi, and Stefan Savage.

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Presentation on theme: "Presented by Pierre-Élie Fauché 1 XL: An Efficient Network Routing Algorithm Kirill Levchenko Geoffrey M. Voelker, Ramamohan Paturi, and Stefan Savage."— Presentation transcript:

1 presented by Pierre-Élie Fauché 1 XL: An Efficient Network Routing Algorithm Kirill Levchenko Geoffrey M. Voelker, Ramamohan Paturi, and Stefan Savage University of California San Diego

2 Routing Getting from point A to point B Need to know some state of the network Today we do this by flooding 2

3 Flooding link changes here everyone gets update anyway does not need to know 3

4 Flooding Number of updates per node grows with the number of links Slowest link or node effectively limits sustainable size of an AS network Is flooding inherent to routing? 4

5 Outline Selective flooding XL update propagation rules Simulation results Conclusion 5

6 Selective Flooding Idea A: Artificial Hierarchy Manually restrict scope of updates Example: OSPF areas “Considered harmful” Results in sub-optimal routing Hard to adapt to growth 6

7 Reducing Updates Idea B: Bound Radius Idea: limit update scope by distance Drawback: not always correct Distant links may be important Greatly delays convergence 7

8 Goals Automatically limit update scope Formal correctness Loop-free routing All destinations reachable Bounded stretch 8

9 Reducing Updates Idea XL: Selective Updates Idea: Link state with selective update propagation Need to know which updates are necessary and which can be suppressed 9

10 Propagation Rules Ensures distance estimate decreases along forwarding path Path cost finite → no long-term loops  Always propagate a link cost increase.  Neighbor should know best cost to destination if it is the next hop. 10

11 Propagation Rules Guarantees all connected nodes are reachable and stretch is bounded Bonus: stretch can be set per-destination or in response to network load Under “normal” conditions set stretch to 1.0 (optimal)  Propagate update if it significantly improves some route. 11

12 Applying the Rules Different link state tables (external views) for each neighbor Internal view consists of most recent information from neighbors’ external views 12

13 Applying the Rules Compute forwarding table using internal view 13

14 Applying the Rules Propagate update to neighbor’s view if: S The link cost increases S Link cost decreased and neighbor is next hop to link C Cost decreased and new route much better 14

15 Example stretch 1.5 Rule S1 (link increase must be propagated) {CD: 1 → ∞} 15

16 Example stretch 1.5 Rule C1 (significant improvement)No rules apply: update suppressed {CD: ∞ → 1} ☺ A-B-C-D: 3 (actual path) 16

17 Goals ✓ Loop-free routing ✓ All destinations reachable ✓ Bounded stretch 17

18 Simulation Model No traffic or propagation delays Poisson failure model 1 day mean time to failure 1 hour mean time to recovery Flapping failure model 2 days mean time to failure High probability of repeat failure 18

19 Simulation Networks Crown64 — crown-like ring (192 nodes) H. 16 × 16 — honeycomb grid (289 nodes) Q. 16 × 16 — square grid (576 nodes) Abilene — Abilene backbone (11 nodes) AS 1221 — Telstra (104 nodes) AS 1239 — Sprint (315 nodes) 19

20 Simulated Algorithms Distance Vector (e.g. RIP) Link State (e.g. OSPF) Distance Vector with Parent Pointer fixes “counting-to-infinity” by sending shortest-path tree in addition to distances Link Vector SPT-based like Distance Vector with Parent Pointer 20

21 Updates per Day Poisson failure model □ Relative to Link State Crown64H. 16 × 16Q. 16 × 16AbileneAS 1221AS

22 Updates per Day Flapping failure model □ Relative to Link State Crown64H. 16 × 16Q. 16 × 16AbileneAS 1221AS x 22

23 Transient Loop Duration Poisson failure model □ Relative to Link State Crown64H. 16 × 16Q. 16 × 16AbileneAS 1221AS

24 Time to Find New Path Poisson failure model □ Relative to Link State Crown64H. 16 × 16Q. 16 × 16AbileneAS 1221AS

25 Crown64 H. 16 × 16 Q. 16 × 16 Abilene AS 1221 AS 1239 Actual Stretch Poisson link failure model Average (over all pairs of nodes) Maximum (over all pairs of nodes) median

26 OSPF Compatibility Observation: classic link state algorithm is a “special case” of the XL algorithm OSPF satisfies the XL rules XL could be mixed with OSPF for incremental deployment 26

27 Conclusion Provable correctness Bounded (user-specified) stretch Up to 3-10x fewer updates Compatible with the favorite link-state protocol — OSPF 27


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