1. 17 th -21 st July 200622 nd APAN Meeting in Singapore ’06 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

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 r 6, r 8 Hash key for receivers r 2, r 5, r 10, r 15,r 23, r 40, r 7 Hash key for receivers r 1, r 3, r 4 Sub-tree 1 Cluster 1 Sub-tree 2 Cluster 2 Sub-tree 3 Cluster 3 r 6 r 8 r 2 r 5 r 10 r 15 r 23 r 40 r 7 r 1 r 3 r 4 Hash Table Tree Root Sub-trees Leaves Tree construction technique CLUSTERING

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 Table size Subscription delay (in msec.)Unsubscription delay (in msec.) minimummaximumminimummaximum 101 0.250.53300 211 0.2850.6200 307 0.2150.6400 1 007 0.3130.470.0320.0588 10 007 0.2190.3180.0470.0605 49 999 0.2460.5970.05780.14295 Average delay 0.2550.5300.04560.087

15. Multicast source (S) 1 st HOP 2 nd HOP 3 rd HOP 4 th HOP R3 R5 R8 R10 Join(S,r 15 ) r 15 r 23 r5r5 r7r7 r2r2 r 40 r 10 Join(S,r 10 ) Join(S,r 40 ) Join(S,r2) Join(S,r 23 ) Join (S,r 5 ) Join(S,r 7 ) Packet forwarding-downstream Join traffic- upstream R i : routers r i : receivers Cluster 2 route

16. Matrix representation of cluster 2 route (before reduction) SR3R3 R5R5 R8R8 r2r2 SR3R3 R5R5 r5r5 SR3R3 R5R5 R8R8 R 10 r 10 SR3R3 r 15 SR3R3 R5R5 r 23 SR3R3 R5R5 R8R8 r 40 SR3R3 R5R5 r7r7

17. SR3R3 R5R5 R8R8 r2r2 SR3R3 R5R5 r5r5 SR3R3 R5R5 R8R8 R 10 r 10 SR3R3 r 15 SR3R3 R5R5 r 23 SR3R3 R5R5 R8R8 r 40 SR3R3 R5R5 r7r7 Control messages: Join(S,ri)-upstream Tree(S,ri)-downstream Join (S, r i ) Tree (S, r i ) S :source R i: routers r i recievers Proposed Approach Matrix representation of cluster 2 routes

18. The matrix after dropping the duplications SR3R3 R5R5 R8R8 r2r2 r5r5 R 10 r 10 r 15 r 23 r 40 r7r7 join (S,ri) 124 45 Number of copies Hops123 31 tree (S,ri) S: source Ri: routers ri: receivers

19. SR3R3 Hope 1: S replicates 1 copy to R 3 SR5R5 r 15 Hope 2: R 3 replicates 2 copies to R 5, r 15 Sr 23 r7r7 R8R8 r5r5 Hope 3: R 5 replicates 4 copies to r 23, r 7, R 8, r 5 Sr2r2 r 40 R 10 Hope 4: R 8 replicates 3 copies to r 2, r 40, R 10 Sr 10 Hope 5: R 10 replicates 1 copy to r 10 Multicast Forwarding States after Reduction Multicast Forwarding Table (MFT) at S MFT at R3 MFT at R5 MFT at R8 MFT at R10

20. Multicast source (S) 1 st HOP 2 nd HOP 3 rd HOP 4 th HOP S forwards 1 copy to R 3 R3 R5 R8 R1 0 R 3 replicates 2 copies to R 5,r 15 R 5 replicates 4 copies toR 8,r 23,r 5,r 7 R 8 replicates 3 copies to r 2,R 10, r 40 R 10 forwards 1 copy to r 10 Join(S,r 15 ) r 15 r 23 r5r5 r7r7 r2r2 r 40 r 10 Join(S,r 10 ) Join(S,r 40 ) Join(S,r2) Join(S,r 23 ) Join (S,r 5 ) Join(S,r 7 ) S r 40 R 10 r 2 MFT at R 8 S r 5 r 7 R 8 r 23 MFT at R 5 S R 3 MFT at S S R 5 r 15 MFT at R 3 Packet forwarding- downstream Join traffic- upstream S r 10 MFT at R 10 Multicast forwarding state reduction at routers 2 nd contribution

21. REUNITE Tree (symmetric example) S R1R1 R2R2 R3R3 U R4R4 R6R6 r7r7 r1r1 r2r2 r3r3 R5R5 R7R7 r8r8 r4r4 r5r5 r6r6 S: source node R i : REUNITE routers r i : receivers U: unicast router S r 1 MFT S r 1 S r 1 r 4 S r 4 S r 4 r 8 S r 1 r 7 S r 4 r 5 r 6 S r 1 r 2 r 3 MFT dst to r 1 to r 4 to r 7 to r 1 to r 2 to r 3 to r 4 tor 6 tor 5 to r 4 to r 8 to r 4 MFT dst

22. REUNITE (asymmetric example) S R1R1 R2R2 R3R3 R4R4 r1r1 R5R5 r2r2 S: source node R i : REUNITE routers r i : receivers S r 1 MFT to r 1 to r 2 to r 1 to r 2 MFT dst R6R6 S r 1 r 2 S r 1 S r 2 S r 1 r 2 Join message Tree messageData to dst Packet duplication

23. Comparison between state scalability approaches REUNITEHBHREHASH Tree typeShortest path Reverse Path Forwarding (RPF) Address typeunicastClass Dunicast Network typesymmetricAsymmetricboth Group sizeSmall-size Small & Large-size

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. 17 th -21 st July 200622 nd APAN Meeting in Singapore ’06 Forwarding State Reduction for One-to-Many Group Communications Sahar A. Al-Talib (PhD. Candidate) e-mail: sahartalib@hotmail.com THANK YOU