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Threshold-Based Multicast for Continuous Media Delivery

Threshold-Based Multicast for Continuous Media Delivery. Lixin Ga o, Member, IEEE, and Don Towsle y, Fellow, IEEE. IEEE TRANSACTION ON MULTIMEDIA. Outline. INTRODUCTION THRESHOLD-BASED MULTICAST OPTIMAL THRESHOLD SIMULATION STUDY CONCUSION. INTRODUCTION.

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Threshold-Based Multicast for Continuous Media Delivery

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  1. Threshold-Based Multicast for ContinuousMedia Delivery Lixin Gao, Member, IEEE, and Don Towsley, Fellow, IEEE IEEE TRANSACTION ON MULTIMEDIA

  2. Outline • INTRODUCTION • THRESHOLD-BASED MULTICAST • OPTIMAL THRESHOLD • SIMULATION STUDY • CONCUSION

  3. INTRODUCTION • Four types of multicast approaches • Server-initiated • Broadcast video every t minutes • Server-initiated-with-prefetching (SIWP) • PB, PPB… • Client-initiated • Similar to Batch • Client-initiated-with-prefetching (CIWP) • Similar to Patch

  4. Server-initiated • No Prefetch • guarantee a maximum service latency • Waiting time independent to the number of request • With Prefetch (SIWP) • reduce the server network-I/O resources required • Reduce the waiting time more • Good for hot video

  5. Client-initiated • No Prefetch • batching reduces demand for server network-I/O bandwidth, but it does so at the cost of introducing service latency and there is no maximum service latency guarantee • With Prefetch (CIWP) • Save server network-I/O bandwidth • Reduce waiting time (in Client-initiated) • Good for cold and lukewarm video

  6. THRESHOLD-BASED MULTICAST

  7. Motivation • The Server network-I/O bandwidth • Basic CIWP：a linear function of the request rate • threshold-based：a linear function of the square root of the request rate • a hybrid of CIWP and SIWP scheme Cold and lukewarm Video Hot Video

  8. Video delivery system architecture Low Bandwidth And Reliable Complete video stream Partial video stream

  9. Interaction among client, data server, scheduler MGc：complete stream MGp：partial stream VLength：the number of packets that receive from partial channel

  10. Client Algorithm

  11. Server Scheduler Algorithm • 1) Batch the request with a complete stream of video that is scheduled to start later. • 2) Prefetch from an ongoing complete stream of video and batch a partial stream of video scheduled to start later by expanding the partial stream. • 3) Prefetch from an ongoing complete stream of video and schedule a partial stream of video at the earliest possible time. • 4) Schedule a complete stream of video at the earliest time

  12. 1. Batch a complete stream 2. <threshold Prefetch a complete stream Batch a partial stream 3. <threshold Prefetch a complete stream Schedule a partial stream 4.schedule a complete stream

  13. Data Server Algorithm

  14. OPTIMAL THRESHOLD • requests for video are generated by a Poisson process with mean interarrival time • We Assume the buffer size is not a constraint • min{ B , Li-B } • ：denote the time at which the system schedules a complete stream for video (renewal point)

  15. OPTIMAL THRESHOLD t i-1 t i

  16. OPTIMAL THRESHOLD • : the average server bandwidth Poisson process K：the number of arrivals in Ti

  17. OPTIMAL THRESHOLD Minimizes the expression Other Case

  18. Server bandwith versus request rate

  19. SIMULATION STUDY

  20. Expected waiting time versus number of server channels.

  21. Expected waiting time versus buffer size

  22. Expected waiting time versus request arrival rate • Reduces the expected waiting time • over 4.5 min compared to FCFS batching • over 3.3 min compared to the basic CIWP • Even when the request rate increases to 100 requests per minute, the expected waiting time is still less than 1 min in threshold-based multicast.

  23. Conclusion • This paper presents a novel multicast technique that significantly reduces the demand on the server network-I/O band-width • Unlike existing CIWP schemes, threshold-based multi-cast uses a threshold to control the frequency that a complete video stream is multicasted

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