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Proxy-Assisted Techniques for Delivering Continuous Multimedia Streams

Lixin Gao, Zhi-Li Zhang, and Don Towsley

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Agenda

Related work Proxy-Assisted Video Delivery Architecture Proxy-Assisted Catching Proxy-Assisted Selective Catching Simulation results Conclusion

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Related WorkMulticast Techniques

Client pull Server-push

Batching Patching

Server-push

-> Typically designed for “hot” (frequently requested) objects

-> Fixed number of multicast channels

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Limitations of current technology

Server and network resources (Server I/O bandwidth and network bandwidth) are major limiting factors in widespread usage of video streaming over the internet

Need techniques to efficiently utilize server and network resources

Service latency and popularity of video object should be considered

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Proxy-Assisted Video Delivery Architecture

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Advantages of proxy-assisted video delivery Latency reduction without increasing demand

on backbone network resources Need to store only the initial frames hence

feasible with large data volume I/O bandwidth requirement on proxy server is

insignificant, since responsible for limited number of clients

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ClassificationProxy-assisted video delivery architecture

Proxy-assisted catching

Proxy-assisted Selective catching

Proxy-assisted catching : Suited for “hot” video objects

Proxy-assisted selective catching : Even suited for “cold” (less frequently requested) video objects

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Advantages of proposed architectures

Reduce the resources requirements at central server

Reduce service latency experienced by clients

Assumptions

Client can receive data from 2 channels simultaneously

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Proxy-Assisted Catching Reduces service

latency by allowing clients to join an ongoing broadcast

Clients catch-up by retrieving initial frames using unicast channel from proxy

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Proxy-Assisted Catching

Partition function used

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Optimizing

Server and network bandwidth are major bottleneck. Hence reducing total number of channels required

Trade-off between -> Number of dedicated channels by server -> Storage space required by proxy

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Terms involved

N : No. of video objects on central server L : Length of video λ : Request rate (Poisson distribution) K : Server channels to broadcast video K* : Optimal number of server channels i : Video object no. j : Broadcasting frame

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Calculation

No. of proxy channels required :

Total no. of channels required :

Tradeoff between number of server channels and expected number of proxy channels required for catch-up

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Calculation contd..

Optimization problem :

Expected number of channels :

Optimal no. of server channels

Optimal no. of proxy channels

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Controlled Multicast Client pull technique Allows client to join the ongoing multicast if it requests with a

certain threshold time Ti

Else a new multicast channel is allocated

Proxy-assisted Controlled Multicast Proxy pre-store the initial Ti frames of video Missing portion of video is send separately through a

unicast channel Good technique for “cold” video objects

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Comparison with Proxy-Assisted Controlled Multicast Total no. of channels required for controlled

multicast is : For large value of λ no. of channels

required by proxy-assisted catching is less Verified using following setup :

L : 90 min. video object

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Observation

0.4

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Proxy-Assisted Selective Catching

Combines Proxy-Assisted Catching and Controlled Multicast

Broadcast most frequent videos using Proxy-Assisted Catching and less frequent videos using Controlled Multicast

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Classifying “Hot” and “Cold” videos

Hot video if

Total no. of channels required using catching

Total no. of channels required using controlled multicast

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Simulation results

Simulation settings N : No. of video objects on central server λ : Request rate (Poisson's distribution) Simulates 150 hours of client requests Ki* : Broadcasting channels for “hot” video

objects Remaining channels for controlled multicast First-come-first-serve basis

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Assumptions

Sufficient proxy resources to store prefixes for all videos

Proxy server has 40GB of storage space and I/O bandwidth of 88 Mb/s

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Waiting time vs. total number of channels

710 900λ = 50

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Waiting time vs. Arrival rate λ varies from 40 to 80 Total no. of channels = 700

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Total no. of channels vs. arrival rate

100150

Performance of selective catching and catching same

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Waiting time vs. Server channels

460 700

36% saving in number of channels required at central server

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Number of channels vs. Arrival rate

Significant reduction in central server channel requirement

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Waiting time vs. Server channels

Advantage of proxy-assisted selective catching does not critically depend on availability of proxy storage space

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Conclusion

Approach is proved using quite realistic simulations without any major assumptions

If the arrival rate exceeds beyond certain assumptions then the service latency will increase

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