Forwarding State Reduction for One-to-Many Group Communications

1. Forwarding State Reduction for One-to-Many Group Communications Sahar A. Al-Talib (PhD. Candidate) Prof. Dr. Borhanuddin Mohd Ali Assoc. Prof. Sabira Khatun Presenter: Chong Jin Hui 22nd APAN Meeting in Singapore ’06

2. Motivations • The initial design was motivated by the need to support one-to-many (Source Specific Multicast) and many-to-many group applications in a scalable fashion. Such applications cannot be serviced efficiently with unicast delivery. • The intend of the research is trying to remove some of the obstacles encountered in the way of multicast deployment in the Internet.

3. Group Communication Applications: • Internet TV, Radio and Games • Video conferencing • Distance learning • File distribution • Streaming media • etc,..

4. Issues that have delayed IP multicast deployment: • Scalability • Scalability in multicast routing means that overhead in packets and the amount of states stored in routers must be kept minimal. • Address allocation • Billing • Security • Etc.

5. Introduction • Source Specific Multicast (SSM) is a solution for current multicast applications • It brings many benefits in address allocation, billing, and security. • SSM still faces the state scalability problem that delayed its deployment.

6. SSM is dedicated to single source applications (one-to-many Group Communications) • 90% of multicast applications of immediate interest are single-source [Cui J. et al., 2002]

7. Proposed solution • Providing means for incremental deployment of multicast Methodology • Clustering ( tree construction ) sub-trees to serve large-size group • Improve the State Scalability of Source Specific Multicast

8. Tree construction technique • The tree can be build using different techniques according to the way it spans between source & receivers (dynamic tree with routing state maintenance) • (Hash Technique with one source and thousands of receivers  source specific tree one–to-many applications

9. Multicast Source (S) Hash Function Cluster receivers based on their IPv6 address Hash key for receivers r2, r5, r10, r15,r23, r40, r7 Hash key for receivers r1, r3, r4 Hash key for receivers r6, r8 Hash Table Sub-tree 2 Cluster 2 Sub-tree 3 Cluster 3 Sub-tree 1 Cluster 1 r2 r5 r10 r15 r23 r40 r7 r1 r3 r4 r6 r8 Tree construction technique CLUSTERING Root Tree Sub-trees Leaves

10. Join/leave latency • Simulation results for the clustering stage • The join/leave delay that has been obtained from the simulation shows the efficiency of the software and the group management scheme that has been used (similar delay for 100, 1000, 10 000 and 50 000 nodes) • Subscription Delay of (0.255-0.530msec.) • Unsubscription Delay of (0.0456-0.087msec.)

14. Average Delay summery

15. Cluster 2 route Multicast source (S) 1st HOP Join(S,r15) R3 r15 2nd HOP Join(S,r7) r7 R5 r23 Join (S,r5) Join(S,r23) r5 3rd HOP Join(S,r40) R8 r2 Join(S,r2) r40 4th HOP R10 Join(S,r10) Join traffic- upstream Ri : routers ri : receivers r10 Packet forwarding-downstream

16. Matrix representation of cluster 2 route(before reduction)

17. Proposed Approach Join (S, ri ) Control messages: Join(S,ri)-upstream Tree(S,ri)-downstream S :source Ri: routers ri recievers Tree (S, ri ) Matrix representation of cluster 2 routes

18. The matrix after dropping the duplications join (S,ri) S: source Ri: routers ri: receivers Number of copies 1 2 4 3 1 Hops 1 2 3 4 5 tree (S,ri)

19. Multicast Forwarding Table (MFT) at S MFT at R3 MFT at R5 MFT at R8 MFT at R10 Multicast Forwarding States after Reduction

20. Multicast source (S) S forwards 1 copy to R3 MFT at S S R3 1st HOP R3 replicates 2 copies to R5,r15 MFT at R3 Join(S,r15) R3 S R5 r15 r15 2nd HOP R5 replicates 4 copies toR8,r23,r5,r7 Join(S,r7) r7 R5 r5 MFT at R5 r23 Join (S,r5) Join(S,r23) S r5 r7 R8 r23 3rd HOP R8 replicates 3 copies to r2,R10,r40 MFT at R8 Join(S,r40) S r40 R10 r2 R8 r2 Join(S,r2) r40 4th HOP R10 forwards 1 copy to r10 R10 MFTat R10 Join(S,r10) S r10 Join traffic- upstream r10 Packet forwarding-downstream Multicast forwarding state reduction at routers 2nd contribution

21. MFT S S r1 S: source node Ri: REUNITE routers ri: receivers U: unicast router to r1 MFT dst S r1r4 R1 to r1 to r4 R3 R2 S r1 S r4 to r4 to r1 U MFT dst S r4 r8 MFT dst S r1 r7 R5 to r7 R4 to r8 r7 to r4 r8 to r1 MFT dst MFT dst S r1 r2 r3 S r4 r5 r6 R6 R7 to r1 to r4 tor6 to r3 to r2 tor5 r1 r3 r4 r6 r2 r5 REUNITE Tree (symmetric example)

22. S r1 REUNITE (asymmetric example) MFT S S: source node Ri: REUNITE routers ri: receivers to r1 MFT dst S r1 r2 R1 to r1 to r2 R3 R2 Packet duplication to r2 R6 to r1 S r2 S r1 S r1 r2 R5 R4 to r2 r2 r1 to r1 Join message Tree message Data to dst

23. Comparison between state scalability approaches

24. Conclusion: • To conclude, this work is an important initiative towards designing a multicast framework for handling the source and receiver movement together. • The database of the nodes that has been built to do the simulation could be extended to include QoS, security related parameters for further research.

25. Conclusions (cont.) • It has been proved that the proposed method of clustering with state scalability reduction approach is more effective in supporting one- to-many group communication than other existing proposals (REUNITE, HBH, xcast)-since it could handle larger sized groups (50K nodes) as well as small-size groups

26. THANK YOU Forwarding State Reduction for One-to-Many Group Communications Sahar A. Al-Talib (PhD. Candidate) e-mail: sahartalib@hotmail.com 22nd APAN Meeting in Singapore ’06