A Comparison of Layering and Stream Replication Video Multicast Schemes

1. A Comparison of Layering and Stream Replication Video Multicast Schemes Taehyun Kim and Mostafa H. Ammar

2. Content • Research Goal • Replication VS Layering • Experimental Comparison • Results • Conclusion

3. Research Goal • A systematic comparison of video multicasting schemes designed to deal with heterogeneous receivers • Replicated streams • Cumulative layering • Non-cumulative layering

4. Stream Replication • Multiple video streams • Same content with different data rates • Receiver subscribes to only one stream • Example • SureStream of RealNetworks • Intelligent streaming of Microsoft

5. Replicated Stream Multicast • R1, R2 and R3 are from different domain • Receivers subscribe to only one stream • R1 joins the high quality stream (8.5Mbps) • R2 receives the medium quality stream (1.37Mbps) • R3 joins the low quality stream (128kbps)

6. Cumulative Layering • 1 base layer + enhancement layers • Base layer • Independently decoded • Enhancement layer • Decoded with lower layers • Improve the video quality • Example • MPEG-2 scalability modes

7. Non-Cumulative Layering • Video is encoded in two or more independent layers • Receiver can join any subset of the video layer without joining the layer 1 multicast group • Example • Multiple description coding (MDC)

8. Layered Video Multicast • R1 subscribes to all video layers (10 Mbps) • R2 joins enhancement layers 1 and the base layer (1.5 Mbps) • R3 just receives the base layer (128kbps)

9. Layering or Replication? • Common wisdom states: • “Layering is better than replication” • However, it depends on • Layering bandwidth penalty • Specifics of encoding • Protocol complexity • Topological placement of receivers

10. Layered Video Multicast • Considering 20% overhead, the data rates contributing to the video quality are 8Mbps, 1.2Mbps and 102.4Kbps • Stream Replication: video quality are 8.5Mbps, 1.37Mbps and 128kbps

11. Bandwidth Penalty • Information theoretic results • Recent results showed that the performance of layered coding is not better than that of non-layered coding • Increase the number of layers => significant quality degradation • Packetization overhead • Enhancement layers carry: • Picture header • GoP information • Macroblock information

12. Experimental Comparison • Non-layered streams has better video quality • Difference in data rates ranges from 0.4% at 27.7dB PSNR to 117% at 23.2dB PSNR • For a good quality video, the overhead is around 20%

13. Providing a Fair Comparison • Need to insure that each scheme is optimal • Two dimensions • Stream assignment algorithm • Determine the reception rate of each receiver by aggregating the data rates of the assigned streams • Rate allocation algorithm • Determine the data rate of each stream • Goal • Maximize the bandwidth utilization by each scheme for • a given network • a particular set of receivers and • given available bandwidth on the network links

14. System Model • Model the network by a graph G = (V, E) • V is a set of routers and hosts • E is a set of edges representing connection links • Isolated rate • The reception rate of the receiver if there is no constraint from other receivers in the same session

15. Stream Assignment • Cumulative layering • Define • i is the data rate of a stream and m is the number of layers • Assign as many layers as possible • Compute the isolated rates • Assign that does not exceed the isolated rate

16. Stream Assignment • Stream replication • Define • i is the data rate of a replicated stream and m is the number of replicated streams • Set of receivers assigned to stream i, • Two objectives • Minimum reception rate for all receivers is greater than zero • Maximum • Greedy algorithm • Allocate 1 to all receivers to satisfy the minimum reception rate constraint • Receiver is assigned a stream that has not been assigned and has the maximum value of group size and stream rate product

17. Stream Assignment • Non-cumulative layering • Define • i is the data rate of a non-cumulatively layered stream and m is the number of streams • Set of receivers assigned to stream i, • Two objectives • Minimum reception rate for all receivers is greater than zero • Maximum

18. Rate Allocation • Cumulative layering • Optimal receiver partitioning algorithm (Yang, Kim and Lam 2000) determines the optimal rates of layer i, i • Receivers are partitioned into K groups (G1, G2,…, GK) • Objective is to maximize the sum of receiver utilities • Dynamic programming algorithm is used to find an optimal partition • For a given partition, an optimal group transmission rate can be determined • Stream replication • Stream rates, i, are allocated based on the optimal cumulative layering rate

19. Rate Allocation • Non-cumulative layering • Receiver can subscribe to any subset of layers without joining the base layer • ={1,2,4} => isolated rates of {1,2,3,4,5,6,7} • 2m-1 different link capacities with m non-cumulative layers • i are allocated based on i =>

20. Performance Metrics • Average reception rate • Average rate received by a receiver • Average effective reception rate • Amount of data received less the layering overhead • Total bandwidth usage • Adding the total traffic carried by all links in the network for the multicast session • Efficiency • total effective reception rate / total bandwidth usage

21. Network Topology • Georgia Tech Internetwork Topology Models (GT-ITM) • 1 server • 1640 nodes with 10 transit domains • 4 nodes per transit domains, 4 stubs per transit node, 10 nodes in a stub domain • transit-to-transit edges = 2.4Gbps • stub-to-stub edges = 10Mbps and 1.5Mbps • transit-to-stub edges = 155Mbps, 45Mbps and 1.5Mbps • number of layers = 8 • amount of penalty = 20%

22. Date Reception Rate • Cumulative layering can receive more data • Number of layers in cumulative layering is twice as many as that of non-cumulative layering Cumulative Non-cumulative Replication

23. Bandwidth Usage • Bandwidth consumption of cumulatively layered multicasting is the largest Cumulative Non-cumulative Replication

24. Effective Reception Rate • Only 80% of data contributes to improving the video quality Cumulative Non-cumulative Replication

25. Efficiency • Replicated stream video multicasting is more efficient Cumulative Non-cumulative Replication

26. Effect of Overhead • Layering overhead of more than 7% tends to favor the replicated stream approach

27. Effect of the number of layers • Efficiency of stream replication is always greater than that of cumulative layering • The effect is not so significant

28. Narrow Distribution • The layering approach achieves better bandwidth efficiency when multiple streams share the bottleneck link • In narrow distribution, the reception rates in Figure (a) is larger than that of Figure (b) by 1.63Mbps Narrow distribution Wide distribution

29. Efficiency • Compared to the wide distribution results, the performance of replicated stream video multicast is degraded Cumulative Non-cumulative Replication

30. Protocol Complexity • Receiver-driven Layered Multicast (RLM) • Receivers decide whether to drop additional layer or not • Join experiment incur a bandwidth overhead • Receivers send a join message and multicast a message identifying the experimental layer to the group • Layered video multicasting • Receiver can join multiple groups • Large multicast group size • Replicated stream video multicasting • Receiver only join one group • Small multicast group size

31. Average Group Size • Group size in cumulatively layered video multicasting is twice as large as that in stream replication • More bandwidth to multicast a message reporting the “join” experiment

32. Conclusion • Identified the factors affecting relative merits of layering versus replication • Layering penalty • Specifics of the encoding • Protocol complexity • Topological placement • Developed stream assignment and rate allocation algorithms • Investigated the conditions under which each scheme is superior