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Preemptive Strategies to Improve Routing Performance of Native and Overlay Layers

Preemptive Strategies to Improve Routing Performance of Native and Overlay Layers. Srinivasan Seetharaman - College of Computing, Georgia Tech Volker Hilt - Multimedia Networking, Bell Labs Markus Hofmann - Multimedia Networking, Bell Labs

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Preemptive Strategies to Improve Routing Performance of Native and Overlay Layers

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  1. Preemptive Strategies to Improve Routing Performance ofNative and Overlay Layers Srinivasan Seetharaman - College of Computing, Georgia Tech Volker Hilt - Multimedia Networking, Bell Labs Markus Hofmann - Multimedia Networking, Bell Labs Mostafa Ammar - College of Computing, Georgia Tech

  2. Multi-Layer Interaction • Service overlay networks offer enhanced services by forming a virtual network of specialized nodes • They deploy independent routing schemes that • are oblivious to underlying native network • achieve a specific selfish objective • Two main problems: • Mismatch of routing objectives • Misdirection of traffic matrix estimation

  3. Repeated Game Model Player1: Overlay Routing (OR) • Latency-optimized paths between nodes • Reacts to changes in link latency by probing periodically, without concern for bandwidth Player2: Traffic Engineering (TE) • MPLS-based scheme that solves a linear program (using GNU LP kit) to obtain optimal multi-paths using traffic matrix as input • Minimize [ Max util = MaxaE ( Xa/Ca ) ]

  4. Repeated Game model (contd.) Overlay Routing Overlay routes Overlay Link Latencies Overlay layer traffic  Native link delays  Traffic on each overlay link Traffic Engineering Native routes Background traffic  TrafficMatrix

  5. Illustration of OR vs TE 14ms C Shortest latency routes A 4ms 4ms 5ms B 10ms D 23ms OVERLAY NATIVE 2 F E 4 10ms 2ms C 4 3 3 3 4 2ms 2ms Minimize(Max util) 2ms Numbers on each link represent the avail-bw 3ms 2ms 5 B A G H 4ms 2 3 2 3 6ms 3ms 2ms 3ms 2 2 I J D 10ms 10ms Initial State

  6. Illustration of OR vs TE (contd.) 14ms C Multihop paths A  B  C A  B  D A 6ms 4ms 5ms B 10ms D 23ms OVERLAY NATIVE 2 F E 4 10ms 2ms C 4 0 0 2 2 2ms 2ms 2ms 3ms 2ms 1 B A G H 4ms 2 1 2 2 6ms 3ms 2ms 3ms 2 2 I J D 10ms 10ms Overlay traffic introduced Avail-bw changed

  7. Illustration of OR vs TE (contd.) 14ms C Multihop paths A  B  C A  B  D A 4ms 5ms 5ms B 10ms D 23ms OVERLAY NATIVE 2 F E 2 10ms 2ms C 2 1 1 2 4 2ms 2ms 2ms 3ms 2ms SPLIT 3 B A G H 4ms 1 1 1 2 6ms 3ms 2ms 3ms 2 2 I J D 10ms 10ms Latencychanged After TE reacts

  8. Illustration of OR vs TE (contd.) 14ms C Multihop paths A  B  C A  B  C  D B  C  D A 4ms 5ms 5ms B 10ms D 23ms OVERLAY NATIVE 2 F E 0 10ms 2ms C 0 1 1 0 4 2ms 2ms 2ms 3ms 2ms SPLIT 5 B A G H 4ms 1 3 1 0 6ms 3ms 2ms 3ms 2 2 I J D 10ms 10ms After Overlay routing reacts Avail-bw changed

  9. TEobjective Overlayobjective Overallstability Simulation Results Round

  10. Past research • [Qiu-Sigcomm03] conducted a simulation study of scenarios where there is a conflict of objectives • [Liu-Infocom05] analyzed the interaction between OR and TE to show existence of Nash equilibrium General conclusion: The system suffers from prolonged route oscillations and sub-optimal routing costs

  11. Our goal .. is to propose strategies that • obtain the best possible performance for a particular layer • while steering the system towards a stable state.

  12. Resolving Conflict – Basic Idea • Designate leader / follower • Leader will act after predicting or counteracting the subsequentreaction of the follower • Similar to the Stackelberg approach

  13. Resolving Conflict - Obstacles • Incomplete information • Unavailable relation between the objectives • NP-hard prediction

  14. Resolving Conflict - Simplification • Assume: Each layer has a general notion of the other layer’s selfish objective • Operate leader such that • Follower has no desire to change  Friendly • Follower has no alternative to pick  Hostile • Constitutes a preemptive action • Use history to learn desired action gradually.

  15. Overlay Strategy - Friendly • Native layer only sees a set of src-dest demands • Improve latency of overlay routes, while retaining the same load pressure on the native network! • Load-constrained LP C 1 E B D 1 A

  16. Overlay Strategy – Friendly (contd.) Acceptable to both OR and TE Stable within a few rounds

  17. Overlay Strategy - Hostile • Push TE to such an extent that it does not reroute the overlay links after overlay routing • Send dummy traffic in an effort to render TE ineffective • Dummy traffic injection C 1 E Unused overlay link AB B D 1 A

  18. Overlay Strategy - Hostile (contd.) TE can’t improve further Acceptable only to OR

  19. Native Strategy - Friendly • TE pays no attention to the length of the route! • TE should balance load, while ensuring that the path length is almost the same! • Hopcount-constrained LP C 1 E B D 1 A

  20. Native Strategy - Friendly (contd.) Acceptable to both OR and TE Takes a bit longer to converge

  21. Native Strategy - Hostile • Dissuade overlay routing from using certain multihop paths • Increase latency of native links that are heavily loaded, without any knowledge of overlay networks • Load-based latency tuning Overusednative link C 1 E 1 B D 1 A

  22. Native Strategy - Hostile (contd.) Disrupted overlay routing Takes a bit longer to converge

  23. Preemptive Strategies: Summary • We proposed four strategies that improve performance for one layer and achieve a stable operating point • Inflation factor = Steady state obj value with strategy Best obj value achieved Inflation

  24. Preemptive Strategies: Summary(contd.) • Each strategy achieves best performance for the target layer • within a few rounds • with no interface between the two layers • with all information inferred through simple measurements • If both layers deploy preemptive strategies, the performance of each layer depends on the other layer’s strategy.

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