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Authors Suman Banerjee, Christopher Kommareddy, Koushik Kar, Bobby Bhattacharjee, Samir Khuller

Construction of an Efficient Overlay Multicast Network Infrastructure for Real-time Applications (OMNI). Authors Suman Banerjee, Christopher Kommareddy, Koushik Kar, Bobby Bhattacharjee, Samir Khuller Affiliation University of Maryland, College Park Appeared in IEEE INFOCOM 2003.

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Authors Suman Banerjee, Christopher Kommareddy, Koushik Kar, Bobby Bhattacharjee, Samir Khuller

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  1. Construction of an Efficient Overlay Multicast Network Infrastructure for Real-time Applications (OMNI) Authors Suman Banerjee, Christopher Kommareddy, Koushik Kar, Bobby Bhattacharjee, Samir Khuller Affiliation University of Maryland, College Park Appeared in IEEE INFOCOM 2003

  2. One Line Comment • Given a set of MSNs with access bandwidth constraints • construct a multicast data delivery backbone such that the overlay latency to the client set is minimized

  3. Evaluation Criteria • Aggregate subtree clients • Aggregate subtree latency (Λ)

  4. Overlay Management Procedure • Initial Tree Construction • Local Transformation • Successive incremental refinements of the initial tree • Periodically performed if this operation can reduces the avg-latency of the tree • Probabilistic Transformation

  5. Initial Tree Creation 7 6 8 5 Source r Join Msg to the root MSN <LatencyToRoot, DegreeBound> 1 2 3 4

  6. Features of Initial Tree • Centralized Algorithm • The root node gathers the latency information and construct the tree locally • Guarantees Log(N) Approximation Bound • Overlay latency from the root MSN to any other MSN, I, is bounded by 2LlogN • L – the direct unicast latency between the root MSN r, and the MSN, I • N the number of MSNs in the OMNI

  7. Local Transformation • Child-Promote • Parent-Child Swap • Iso-level-2 Swap • Aniso-level-1-2 Swap

  8. Child-Promote g g Available degree c p p 3 3 c 1 1 2 2

  9. Parent-Child Swap g g p p Other MSNs Other MSNs c c 1 1 2 2 5 3 5 3 4 4

  10. Iso-level-2 Swap g g p q p q x x 2 2 1 1 y y

  11. Aniso-Level-1-2 Swap p p c c 1 1 x 3 3 x y 2 y 2

  12. Probabilistic Transformation Local Transformation will guide the tree towards the local minimum Local Transformation alone can NOT guarantee a global minimum

  13. Node Join

  14. Simulation Setup • Topology: generated by GT_ITM topology generator • 10,000 routers with avg. node degree between 3 and 4 • MSNs uniformly distributed • The number of MSNs: 16 ~ 512

  15. Simulation Results Effect of the initialization phase Varying the probability of performing the random-swap operation

  16. Simulation Results Effect of the initialization phase Varying the probability of performing the random-swap operation

  17. Comparison of the average tree latency

  18. Conclusion

  19. Critiques • Good Points • Service provider can deploy MSNs without considering optimal node placement • Highly adaptive to the network changes • Very Scalable • Two-Tier infrastructure • Algorithm considers the capacity constraints of each node • Use of dedicated nodes • Bad Points • Not applicable to Many-to-Many Applications • No overload management mechanism • If one server is overloaded by a large number of clients, OMNI can not address this • No Exp. In the msg. overhead in Tree maintenance

  20. Back-up Slides

  21. Dynamics of OMNI

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