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On a Unified Architecture for Video-on-Demand Services

On a Unified Architecture for Video-on-Demand Services. Jack Y. B. Lee IEEE TRANSACTIONS ON MULTIMEDIA, VOL. 4, NO. 1, MARCH 2002. Outline. Introduction UVoD Architecture Performance Modeling Numerical Results Simulation Results Interactive Controls Conclusions. Introduction.

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On a Unified Architecture for Video-on-Demand Services

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  1. On a Unified Architecture forVideo-on-Demand Services Jack Y. B. Lee IEEE TRANSACTIONS ON MULTIMEDIA, VOL. 4, NO. 1, MARCH 2002

  2. Outline • Introduction • UVoD Architecture • Performance Modeling • Numerical Results • Simulation Results • Interactive Controls • Conclusions

  3. Introduction • true-VoD (TVoD) • Service quality is maximized • near-VoD (NVoD) • System cost is minimized • unified VoD (UVoD) • Cost-performance tradeoff

  4. UVoD Architecture (1)

  5. UVoD Architecture (2)

  6. UVoD Architecture (3)

  7. Arrives at time t tm-1< t < (tm –δ) After (t – tm-1) Admit-via-Unicast

  8. Recourse reduction over TVoD • Admit-via-Multicast • As multicast channels is fixed, Admit-via-Multicast users will not result in additional load • Increasing the admission threshold δ thenmore user will be admitted to the multicast channels • Admit-via-Unicast • Since 0 < (t – tm-1) < (T –δ) ≪ L, unicast channels are occupied for a much shorter duration compared to TVoD

  9. Performance Modeling • Latency (average waiting time) • Admit-via-Multicast • Admit-via-Unicast • Admission Threshold • Channel Partitioning

  10. Waiting Times (1) • Admit-via-Multicast • wM (δ)=δ / 2 • Admit-via-Unicast • Arrival process • λu = ( 1 –δ / TR)λ • Service time • Uniform distribution between 0 < s < TR –δ • Approximation by Allen and Cunneen for G/G/m queue

  11. Coefficient of variation Traffic intensity Average service time Server utilization Erlang-C function Waiting Times (2)

  12. Admission Threshold

  13. Channel Partitioning • Find the optimum number of multicast channel such that the resultant latency is minimized • Theorem 1: The optimal proportion of available channels to multicast that minimizes the load at the unicast channels is given by

  14. Numerical Results • Corresponding Latency Formula • NVoD • The latency is constant at 360(900)s for 10(20) movies • TVoD

  15. Admission Threshold verus Queueing Delay

  16. Channel Partition versus Latency

  17. Latency Comparison With TVoD and NVoD

  18. System Capacity and Scalability (1) λ arrival rate in customers/s ulatency constraint in seconds WUVoDlatency fo UVoD WTVoDlatency fo TVoD

  19. 0.2 0.1 System Capacity and Scalability (2)

  20. System Capacity and Scalability (3)

  21. Simulation Results • Environments • Simulation program is developed in C++ using CNCL version 1.10 • Run 31 days • Model Validation • Admission Rescheduling

  22. Model Validation (1)

  23. Model Validation (2)

  24. Admission Rescheduling (1) • When Admission Rescheduling? • For heavy system loads, a user by Admit-via-Unicast may waiting exceed the time to the next multicast of the requestd movie

  25. Admission Rescheduling (2)

  26. Interactive Controls (1) • Using Unicast Channels • Break current multicast video stream then restart at some point • Treat interactive controls as new-video requests starting at the middle of a movie • Could increase waiting for both and interactive requests

  27. Interactive Controls (2) • Channel Hopping • Client has a buffer large enough to cache TR s • User pause at a movie time Tp • Case1: • If resume before buffer overflow, nothing need to be done • Case2: • Once buffer is full, stop buffering • Later resume immediately and determine the nearest multicast channel at movie time Tm ≤Tp

  28. Conclusions • This paper propose and analyzes an architecture that unifies the existing TVoD and NVoD • Through admission-threshold and channel partitioning can achieve cost-performance tradeoff • Results show large performance gain

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