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An adaptive video multicast scheme for varying workloads

An adaptive video multicast scheme for varying workloads. Kien A.Hua, JungHwan Oh, Khanh Vu Multimedia Systems, Springer-Verlag 2002. Outline. Introduction Related Work Proposed Approach Performance Model Performance Conclusion. Introduction.

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An adaptive video multicast scheme for varying workloads

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  1. An adaptive video multicast scheme for varying workloads Kien A.Hua, JungHwan Oh, Khanh Vu Multimedia Systems, Springer-Verlag 2002

  2. Outline • Introduction • Related Work • Proposed Approach • Performance Model • Performance • Conclusion

  3. Introduction • Maximize the efficiency of server resource with • Periodic broadcast • Scheduled Multicast (batching) • Hybrid Design • Will show that existing scheduled multicast techniques are not suited for hybrid designs

  4. Related WorkSkyscraper Broadcasting Scheme • Fragmentation recursive function • Series [1,2,2,5,5,12,12,25,25,52,52,…]

  5. Related WorkSkyscraper Broadcasting Scheme 22-mins video 5 min buffer Apply aforementioned series function => segment size = 10.4 !! 1.5 Mbits/sec 0.5 min latency

  6. Related Work Scheduled Multicast • Differ primarily in the criterion used to select which batch will receive service • First come, first served (FCFS) • Maximum queue length first (MQL) • Maximum factored queue length first (MFQ)

  7. Related Work Scheduled Multicast • FCFS • MQL Video 1 time Video 2 time Fair , maybe bad throughput Video 1 time time Video 2 Better throughput, maybe not fair

  8. Related WorkMaximum factored queue length first (MFQ) • Applying a discriminatory weighting factor to the length of the queue • : video i length, : the request frequency of video i • Schedule video with the largest value of

  9. Related WorkMaximum factored queue length first (MFQ) • d • d Still not fair, because not average waiting time !!

  10. Proposed Approach • Adaptive Hybrid Approach (AHA) • With a novel scheduled multicast -- “Largest aggregated waiting time first scheme” (LAW) • And SB (skyscraper broadcast)

  11. : the total number of pending requests for video i : the arrival time of the jth request for video i c : the current time LAW • Compare with MQL, it take account of the distribution of the request • With considering “aggregated waiting time”

  12. LAW Compute the sum of video i service latency S1=128*5-(107+111+115+121+126)=60 S1=128*5-(107+111+115+121+126)=60 S2=128*4-(112+119+122+127)=32

  13. Adaptive hybrid approach • With following procedures to decide which videos to broadcast

  14. Adaptive hybrid approach

  15. Performance model • Compare AHA with MFQ-SB-n • Performance metrics • Defection rate • Unfairness • Average service latency • Throughput • 100 videos, each 120 mins, avg. playback rate 1.5 Mbits/sec.

  16. Performance model

  17. Performance - LAW vs. MFQ LAW perform slightly better than MFQ in service latency, throughput, defection rate Arrival rate : 8 req/min Skew factor : 0.3

  18. Performance

  19. Performance • Compare MFQ-SB-n with altering one of • Server Capacity (channels) • Request Arrival Rate • Skew Factor

  20. Alter Server Capacity (channels)

  21. Alter Request Arrival Rate

  22. Alter Skew Factor

  23. Alter request rate & skew factor

  24. Conclusion • Prove that existing scheduled multicast schemes are not suited for hybrid design • Proposed a new technique called Largest Aggregated Waiting time first (LAW) • AHA is capable of coping with a changing workload

  25. Periodic Broadcast (1996) • PB v.s. batch: • Short initial delay • Large client-side buffer video Client requests time … … …

  26. Batching (1993) • Batch window: • The time interval to initiate a batch stream. 0 t1 t2 t3 time Client requests

  27. Adaptive hybrid approach

  28. Adaptive hybrid approach

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