Improving VoD System Efficiency with Multicast and Caching

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1 Improving VoD System Efficiency with Multicast and Caching Jack Yiu-bun Lee Department of Information Engineering The Chinese University of Hong Kong Contents 1. Introduction 2. Previous Works 3. UVoD 4. Results 5. Interactive Controls 6. Conclusions Improving VoD System Efficiency with Multicast and Caching 2

2 1. Introduction VoD technologies have been available for many years, why VoD services are still not popular? It s expensive and not economically viable. How can cost be reduced? By evolution of faster computer hardware, higher bandwidth network for the same price. By taking advantage of economy of scales, i.e. using commodity hardware platforms like the PC. E.g. parallel servers. By intelligent ways of reducing the system requirement. E.g. batching, caching, and piggybacking. Improving VoD System Efficiency with Multicast and Caching 3 1. Introduction Observation In real-world applications, a large proportion of VoD users watch only a small number of popular movies. Studies from traditional video rental services show that the movie popularity is Zipf distributed:.12 q i = n f j= 1 i 1 where fi = 1/ i with θ =.271. f, for i = 1 n j θ Selection Probability Movie Number Improving VoD System Efficiency with Multicast and Caching 4

3 1. Introduction Motivation The movie popularity is highly skewed. Many users are likely to watch the same movies. Why not let the users share them? Share What? Server Share retrieved video data at the server by caching. [Freedman et al. 1995] Network Share transmitted video data by multicasting. [Dan et al. 1994, Li et al. 1996, Shachnai et al. 1997, etc.] Client Share received video data by buffering. [Sheu et al. 1997, Ma et al. 1997] Improving VoD System Efficiency with Multicast and Caching 5 2. Previous Works Multicasting Video Transmitting a video by multicast enables the system to serve more than one viewers using only onechannel s worth of resources at the server and part of the network. Replicates by network Switch Switch Switch Switch Improving VoD System Efficiency with Multicast and Caching 6

4 2. Previous Works Problems Video playback of different clients are unlikely to be synchronized. Hence simply sharing a multicast video session among clients arriving at roughly the same time isn t going to be very effective. Interactive VCR operations cannot be supported. Possible Solutions Tradeoff Delay (e.g. NVoD, Batching) Tradeoff Buffer (e.g. Split and Merge) Tradeoff Quality (e.g. Piggybacking) Any combinations of the above. Improving VoD System Efficiency with Multicast and Caching 7 2. Previous Works Near-Video-on-Demand: Ch.1 Video Server Broadcast Network 1 2 Ch.2 Ch.1 Passive receive, limited controls. 3 Ch.3 end of movie start of movie Same movie Ch.1 Ch.2 Ch.3 Ch.4 Improving VoD System Efficiency with Multicast and Caching 8

5 2. Previous Works Near-Video-on-Demand: end of movie start of movie Same movie Ch.1 Ch.2 Ch.3 Ch.4 T If movie length is L then number of channels needed per movie is: N = L / T For example, if L = 12 minutes, T = 1 minutes, then number of video channels needed N = 12 / 1 = 12 channels. This also means that in the worst case, the user has to wait 1 minutes before viewing a movie. System response time inversely proportional to number of required channels. Improving VoD System Efficiency with Multicast and Caching 9 2. Previous Works Batching [Dan et al. 1994] Serve waiting users requesting the same movie using a single multicasted video stream. First-Come-First-Serve (FCFS) Scheduling Incoming requests are queued: 2 Incoming requests wait 4 5 FIFO Queue 8 4-Streams Video Server A video stream is multicasted to all users requesting the same video. Improving VoD System Efficiency with Multicast and Caching 1

6 2. Previous Works Batching [Dan et al. 1994] First-Come-First-Serve (FCFS) Scheduling The HOL request and all requests for the same video title are then served when a channel becomes available. A free channel becomes available FIFO Queue 4-Streams Video Server Video 8 completed 2 Two users are batched wait 4 5 FIFO Queue 9 4-Streams Video Server Video 9 started to serve 2 users. Improving VoD System Efficiency with Multicast and Caching Previous Works Batching [Dan et al. 1994] First-Come-First-Serve (FCFS) Scheduling Advantage Fairness (unpopular videos will not be denied service) Disadvantage Does not consider batching efficiency. Example FCFS assigns the available channel to video 9 with 2 waiting users while there are 5 users waiting for video In terms of batching efficiency, the system should serve video 3 instead of video 9. Improving VoD System Efficiency with Multicast and Caching 12

7 2. Previous Works Batching [Dan et al. 1994] Maximal Queue Length (MQL) Scheduling One FIFO queue per video title Q Serve the longest queue first. Q 1 Q 2 Q 3 Q 4 Q 5 Q 6 Q 7 Q 8 Q Streams Video Server Video 8 completed FIFO Queues Improving VoD System Efficiency with Multicast and Caching Previous Works Batching [Dan et al. 1994] Maximal Queue Length (MQL) Scheduling Advantage Improved batching efficiency. Disadvantage No consideration for waiting time and fairness; Users may leave the queue (turned away) if the waiting time is too long. Results Bandwidth reduction of ~7% with average response time of 2~3 minutes. VCR operation is not supported. Batching is efficient only at high loads, where there are sufficient number of queuing users for effective batching. Improving VoD System Efficiency with Multicast and Caching 14

8 2. Previous Works Batching with Bridging [Li et al. 1997, etc.] Motivation To support interactive operations under batching. Principles Absorb the playback time differences by buffering at the client; or at an intermediate node. Some capacity of the video server is for multicast, while the rest is for unicast. The unicast channels are used to fill the gap between the time difference of the multicasted stream and the requested video stream. Improving VoD System Efficiency with Multicast and Caching Previous Works Batching with Bridging [Li et al. 1997, etc.] Normal Playback: Multicast Unicast Playback from a multicast video stream. Buffer to absorb delay jitters. decoder Video Client Improving VoD System Efficiency with Multicast and Caching 16

9 2. Previous Works Batching with Bridging [Li et al. 1997, etc.] Initiates interactive control (e.g. pause): Multicast Unicast The client breaks away from the multicast session. decoder Video Client Improving VoD System Efficiency with Multicast and Caching Previous Works Batching with Bridging [Li et al. 1997, etc.] Resumes normal playback using a unicast channel: Use a unicast stream to start playback immediately. Multicast Unicast Video Client decoder Buffers to simultaneously store video data from the nearest multicast channel. Improving VoD System Efficiency with Multicast and Caching 18

10 2. Previous Works Batching with Bridging [Li et al. 1997, etc.] Continues normal playback from a multicast channel: Multicast Unicast Video Client decoder When the video playback reaches the point of the buffered video data, the decoder is switched to use the multicast stream and releases the unicast stream. Improving VoD System Efficiency with Multicast and Caching UVoD Motivation TVoD performs well only at light loads while NVoD performs well only at heavy loads. Batching incur substantial startup delay (in minutes) in order to achieve performance gains. Performance of batching over a short time scale depends heavily on the request arrival pattern. Unified VoD Architecture Achieves very significant performance gain (e.g. 5%) even with very low latency (e.g. 2 secs). TVoD and NVoD can be considered special cases of the UVoD architecture. Given the same number of channels, UVoD always achieves lower latency than both TVoD and NVoD. Improving VoD System Efficiency with Multicast and Caching 2

11 3. UVoD Architecture Divides server and network channels into two types: unicast and multicast channels. N U Unicast Channels Request Queue. Unicast video transmission Requests Admission Scheduling. Multicast video transmission N M Multicast Channels Improving VoD System Efficiency with Multicast and Caching UVoD Multicast Scheduling Available M-channels are equally divided among movies. Length of movie (L) Multicast Cycle Movie 1 Movie 2... Improving VoD System Efficiency with Multicast and Caching 22

12 3. UVoD Admission Scheduling A new user is admitted to the nearest multicast channel if the delay will be smaller than a given admission threshold δ. Multicast Repeat M-Ch δ Time Client Waiting Starts with multicast Time Arrival Improving VoD System Efficiency with Multicast and Caching UVoD Admission Scheduling Otherwise the user will start with an I-Channel while simultaneously caching data from a M-Channel. Multicast Repeat M-Ch M-Ch δ 1 Time I-Ch Client Starts with unicast stream Continues via cached multicast stream 1 Time Arrival Playback starts Waiting Improving VoD System Efficiency with Multicast and Caching 24

13 3. UVoD Startup Latency Admission via multicast channel: wm δ ( δ ) = 2 I.e. half the admission threshold (assumes equally probable to arrive at any time within the threshold). Admission via unicast channel: Equals to the waiting time at the unicast channels. Derivations: Probability of admit-via-multicast: Arrival rate at unicast channels: P m δ = T R λ = ( 1 P )λ u m Improving VoD System Efficiency with Multicast and Caching UVoD Startup Latency Admission via unicast channel: Derivations: Range of service time: < s < TR δ Modeled as G/G/m queue, Allen-Cunneen approximation for average wait: EC NU u 2 (, ) C A C w + U ( δ ) N U (1 ρ) 2 Which is load-dependent. 2 S T S Improving VoD System Efficiency with Multicast and Caching 26

14 3. UVoD Startup Latency Observations Latency in general not the same for the two cases. w M ( δ ) w ( δ ) U Increasing admission threshold diverges more users to the multicast channels, thereby reducing w U (δ). Adaptive Admission Scheduling Adjust the admission threshold to maintain a uniform latency. { x ( w ( x) w ( x) ) ε, T } δ = min x M U R Improving VoD System Efficiency with Multicast and Caching UVoD Channel Partitioning Problem How many channels should one reserves for unicast? Intuitions At light loads, more channels should be allocated for unicast to reduce startup latency (i.e. approaches TVoD). At heavy loads, more channels should be allocated for multicast to increase capacity (i.e. approaches NVoD). Special Cases Allocates all channels for unicast, equivalent to TVoD. Allocates all channels for multicast, equivalent to NVoD. Somewhere in between? Improving VoD System Efficiency with Multicast and Caching 28

15 3. UVoD Channel Partitioning Consider W U (δ) versus channel partition policy: 12 9 Latency (sec) Proportion of Multicast Channels Arrival Rate =.55/s Arrival Rate =.6/s Arrival Rate =.65/s Allocating too few I-Channels leads to large latency. Surprisingly, allocating too many I-Channels can be counter-productive as service time will become very long. Improving VoD System Efficiency with Multicast and Caching UVoD Channel Partitioning To minimize load at the unicast channels, it can be shown that a near-optimal allocation is given by: N opt M LN = 2 LM δn M N Where opt N M is the proportion of M-Channels and is the rounding operator. Improving VoD System Efficiency with Multicast and Caching 3

16 4. Results Assumptions Poisson Arrivals Movie length is 12 minutes. Scenario 1: 1 channels, 1 movies. Scenario 2: 5 channels, 5 movies. No interactive control. Improving VoD System Efficiency with Multicast and Caching Results Channel Partition Policy 1 Proportion of Multicast Channels (%) Arrival Rate (customers/sec) 1 Channels, 1 Movies 1 Channels, 2 Movies Improving VoD System Efficiency with Multicast and Caching 32

17 4. Results Comparison with TVoD and NVoD Light load ranges up to.7 (1 channels) Latency (sec) Arrival Rate (customer/sec) TVoD UVoD w/ 5% Multicast Channels (1 Movies) UVoD w/ Near-optimal Channel Allocation (1 Movies) UVoD w/ 5% Multicast Channels (25 Movies) UVoD w/ Near-optimal Channel Allocation (25 Movies) Latency for NVoD is fixed at 36 seconds (1 movies case) regardless of arrival rates. Improving VoD System Efficiency with Multicast and Caching Results Comparison with TVoD and NVoD Heavy load ranges up to.2 (1 channels) Latency (sec) Arrival Rate (customer/sec) TVoD UVoD w/ 5% Multicast Channels (1 Movies) UVoD w/ Near-optimal Channel Allocation (1 Movies) UVoD w/ 5% Multicast Channels (25 Movies) UVoD w/ Near-optimal Channel Allocation (25 Movies) Latency for NVoD is fixed at 36 seconds (1 movies case) regardless of arrival rates. Improving VoD System Efficiency with Multicast and Caching 34

18 4. Results Performance Gain Over TVoD v.s. Latency Constraint Small latency ranges (~3s): 8 Capacity Relative to TVoD (%) Latency Constraint (sec) 1 Channels, Movie/Channel=.1 1 Channels, Movie/Channel=.2 5 Channels, Movie/Channel=.1 5 Channels, Movie/Channel=.2 Improving VoD System Efficiency with Multicast and Caching Results Performance Gain Over TVoD v.s. Latency Constraint Large latency ranges (~7s): 2 Capacity Relative to TVoD (%) Latency Constraint (sec) 1 Channels, Movie/Channel=.1 1 Channels, Movie/Channel=.2 2 Channels, Movie/Channel=.1 2 Channels, Movie/Channel=.2 5 Channels, Movie/Channel=.1 5 Channels, Movie/Channel=.2 Latency for NVoD is fixed at 36 seconds (movie-channel ratio =.1) and fixed at 72 seconds (movie-channel ratio =.2). Improving VoD System Efficiency with Multicast and Caching 36

19 4. Results Performance Gain Over TVoD v.s. System Scale 1 9 Capacity Relative to TVoD (%) Total Number of Channels Movie/Channel=.1 (Latency=2s) Movie/Channel=.2 (Latency=2s) Movie/Channel=.1 (Latency=15s) Movie/Channel=.1 (Latency=3s) Improving VoD System Efficiency with Multicast and Caching Results Model Validation via Simulation Fixed channel partition policy; Three admission threshold settings Queueing Time (sec) sec Admission Threshold: 3 sec 12 sec Analytical: Solid Curves Simulation: Dotted Curves Arrival Rate (customers/sec) Improving VoD System Efficiency with Multicast and Caching 38

20 4. Results Model Validation via Simulation Fixed admission threshold setting; Three channel partition policies Queueing Time (sec) No. of multicast channels: 5 6 Analytical: Solid Curves Simulation: Dotted Curves Arrival Rate (customers/sec) Improving VoD System Efficiency with Multicast and Caching Interactive Controls Supporting Interactive Controls with Unicast Treats users broken away from a multicast channel due to an interactive control as new users. Increasing load at the unicast channels. Performance gain will decrease with increase in rates of interactivity. Supporting Pause-Resume with Channel Hopping UVoD employs static multicast scheduling such that repeating intervals are known and fixed. This enables broken-away users to resume a paused video session simply by joining a nearby multicast session. No overhead is incurred at the server and the network. Suitable for movie-on-demand applications. Improving VoD System Efficiency with Multicast and Caching 4

21 5. Interactive Controls Channel Hopping User initiates pause: Incoming multicasted video data decoder Video Client The video client keeps caching Incoming multicasted video data decoder Video Client Improving VoD System Efficiency with Multicast and Caching Interactive Controls Channel Hopping User resumes playback before cache overflow: No-op, just resumes playback via cache. Incoming multicasted video data decoder Video Client Playback When cache is full, then stops caching: decoder Video Client Note that the cache contains T R seconds worth of video. Improving VoD System Efficiency with Multicast and Caching 42

22 5. Interactive Controls Channel Hopping User resumes playback: Starts playback immediately and wait for the upcoming multicast. decoder Playback Video Client Since every point in a movie is repeated every T R seconds, we guarantee that the next multicast will come before the client runs out of cached video data. Incoming multicasted video data decoder Video Client Playback Improving VoD System Efficiency with Multicast and Caching Conclusions UVoD operates efficiently over a wide range of loads. The existing TVoD and NVoD architectures can be considered special cases of UVoD. Performs at least as good as and mostly better than TVoD and NVoD. Significant performance gain over TVoD (5%) can be achieved even at low latency (1 second). Zero overhead for pause-resume interactive control. Improving VoD System Efficiency with Multicast and Caching 44

23 References [1] A. Dan, D. Sitaram, and P. Shahabuddin, Scheduling Policies for an On-Demand Video Server with Batching, Proc. 2 nd ACM International Conference on Multimedia, 1994, pp [2] H. Shachnai and P.S. Yu, Exploring Waiting Tolerance in Effective Batching for Video-on-Demand Scheduling, Proc. 8 th Israeli Conference on Computer Systems and Software Engineering, Jun 1997, pp [3] V.O.K. Li, W. Liao, X. Qiu, and E.W.M. Wong, Performance Model of Interactive Video-on-Demand Systems, IEEE Journal of Selected Areas in Communications, vol.14(6), Aug 1996, pp [4] W. Liao and V.O.K. Li, The Split and Merge protocol for interactive video-ondemand, IEEE Multimedia, vol.4(4), 1997, pp [5] L. Golubchik, J.C.S. Lui, and R.R. Muntz, Adaptive piggybacking: a novel technique for data sharing in video-on-demand storage servers, ACM Multimedia Systems, vol.4(3), 1996, pp [6] A.O. Allen, Probability, Statistics, and Queueing Theory with Computer Science Applications, 2 nd Ed. Academic Press, New York, 199. Improving VoD System Efficiency with Multicast and Caching 45

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