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1 Provision of VCR-like Functions in Multicast VoD
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2 Presentation Map Introduction Problem identification Review on solutions Issues in algorithm design Q & A
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3 Introduction Targets Based on multicast network architecture, implement VCR-like functions Minimize additional system resources for the resultant system
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4 Problem Identification TVoD (True Video-on-Demand) NVoD (Near Video-on-Demand) Comparisons: server bandwidth, response time, play-out point control Unicast network Multicast network staggered multicast channels TrTr L One channel is dedicated to one client Waiting time depends on system load Clients have total control once they are admitted Adjacent multicast channels stream video data with time lag of Tr Clients have to wait for the start of movie broadcast, max wait = T r, mean = T r / 2
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5 Problem Identification Challenge: How to achieve both: Bounded access latency in NVoD Total control in TVoD with a given set of system restrictions (e.g. server bandwidth, access bandwidth) Current solutions: Periodic broadcasting protocols
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6 Problem Identification What are VCR-like operations? Pause, stop Fast forward / backward Slow motion Jump forward / backward Result change of client play-out point relative to the movie
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7 Problem Identification VCR-like functions resumption Client play-out point and server broadcasting point are out of phase Client has to either Be served by unicast contingency channels bandwidth save due to multicast is lost, or Wait for next broadcast of play-out point the waiting time is unacceptable under normal system configurations (e.g. staggered broadcasting of 2hr movie with 25 channels, mean wait = 144s) staggered multicast channels time t bp 2 bp 1 bp 4 bp 3 movie pppp’ bp server broadcasting point pp client play-out point
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8 Solutions for Providing VCR-like Functions Some proposed solutions Channel merging Pre-fetching / Buffering Staggered broadcasting Quality degradation Precision reduction Movie preview
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9 Channel Merging client buffer bp pp client buffer bp pp’ client buffer bp’ pp’’ forward VCR operation channel merging Examples: patching, piggybacking etc. Goal: to enjoy server bandwidth save by multicast by merging streams together
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10 Patching K. A. Hua, Y. Cai and S. Sheu, "Patching: A Multicast Technique for True Video-on-Demand Services," Proc. 6th International Conference on Multimedia, Sept 1998 Page(s): 191-200. pp bp contingency channel multicast channel bp’ pp’ transient period (T = t L ) tLtL movie pp bp client buffer time
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11 Patching Gain: Further reduction of response time Multicast efficiency improvement Simulation results: No. of server channels: 95 vs 100 for general multicast systems (arrival rate 0.1 / s) Blocking probability: 8% vs 13% for general multicast systems (arrival rate 0.1 / s) Trade-off: Access bandwidth = 2X movie rate Client buffer (max size = T r of movie data, for staggered broadcasting) Ho Kyun Park, Hwang Bin Ryou, “Multicast Delivery for Interactive Video-on-Demand Service,” Proc. 12th International Conference on Information Networking, 1998 Page(s): 46 -50.
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12 Patching Variant: Playback rate of contingency channel: SRMDRU* (Single Rate Multicast Double Rate Unicast) B u = 2 Transient duration halved (T = t L /2) Requires access bandwidth of 3X movie rate Desirable application: Small phase offset (t L ) between client play-out point and multicasting point short patching duration Poon, W.F., Lo, K.T., Feng, J., “Design and analysis of multicast delivery to provide VCR functionality in video-on-demand systems,” 2nd International Conference on ATM, 1999, Page(s): 132 -139.7
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13 Algorithm: To merge two streams by altering display rate Gain: Enables stream merging without the use of contingency channels and client buffer Trade-off: Long merging duration (T = 10t L for r = 5%) Requires sophisticated hardware or pre-coding to supply movie of different playback rate Desirable application: Small time lag (t L ) between streams to be merged Piggybacking 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(30), 1996 Page(s): 14-55. pp 2 pp 1 stream 1 at (1-r*) movie rate merged and share muticast stream 2 at (1+r) movie rate tLtL r display rate alternation ratio transient period (T = t L / 2r)
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14 Pre-fetching / Buffering Algorithm: Always keeps the pp in the middle of buffered video Zongming Fei; Kamel, I.; Mukherjee, S.; Ammar, M.H., “Providing Interactive Functions for Staggered Multicast Near Video-on-Demand Systems,” IEEE International Conference on Multimedia Computing and Systems, Volume: 2, 1999, Page(s): 949 -953. staggered multicast channels time t bp 2 bp 1 bp 4 bp 3 buffer pp bp 2 bp 1 bp 4 bp 3 pp’ bp 2 bp 1 bp 4 bp 3 pp’’
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15 Pre-fetching / Buffering Gain: Higher probability of buffer hit VCR operation completion Simulation result: 92% vs 63% for conventional buffer schemes Trade-off: Extra client access bandwidth requirement (max. 3X) Large client side buffer size (3 T r of movie data : T r = L / N s ) Desirable application: Used together with periodic broadcasting
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16 Staggered Broadcasting Algorithm: Gain: An upper bound on buffer size for merging (T r ) An upper bound on resumption waiting time (T r, mean = T r / 2) Trade-off: Wastage of server bandwidth in case of batch size = 0 (no req. arrival in a whole time slot) Desirable application: Medium to high arrival rate (arrival rate > 1/T r ) staggered multicast channels TrTr time L
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17 Quality Degradation Algorithm: Quality of movie playback, such as frame rate or resolution is lowered during transient period Gain: Lower client access bandwidth / server bandwidth requirement Trade-off: Lower movie quality Sophisticated hardware or pre-coding may be required for production of the altered video stream Desirable application: Efficient transcoding techniques available
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18 Algorithm: Restricts play-out point jumps to video broadcasting points Gain: No additional contingency requirement Zero buffer requirement Trade-off: Resumption points after VCR-like operations are in the increment of t (e.g. 5 mins.) Desirable application: Little phase offset (t) between consecutive movie broadcasts high precision Precision Reduction Almeroth, K.C.; Ammar, M.H., “On the Performance of a Multicast Delivery Video-on-Demand Service with Discontinuous VCR Actions, “ IEEE International Conference on Communications, Seattle, 'Gateway to Globalization', Volume: 3, 1995, Page(s): 1631 -1635. staggered multicast channels time t bp 2 bp 1 bp 4 bp 3 bp 2 bp 1 bp 4 bp 3 movie pppp’pp’’
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19 Previewing Movie Algorithm: Shows preview during admission / VCR resumption downloading / waiting period Gain: Creates an illusion which shortens clients’ perceived waiting time Let clients confirm the right movie selection / seek point Trade-off: Zero or even slightly negative bandwidth save, depending on reusability of the preview data Desirable application: Client is content with movie preview Wallapak Tavanapong, Kien A. Hua, James Z. Wang, “A Framework for Supporting Previewing and VCR Operations in a Low Bandwidth Environment, “, Proceedings of the fifth ACM international conference on Multimedia, November 1997
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20 Algorithm Design Main VoD system design considerations Quality of service Access latency VCR-like function resumption destination shift Movie playback quality FF / FB speed-up factor STB design Client access bandwidth Client buffer size Channel retrieval policy Server design Channel scheduling complexity Server bandwidth
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21 Algorithm Design Trade-offs of different techniques Compared to an on-demand batching multicast VoD system.
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22 Algorithm Design Different approaches work well under different system parameters Staggered broadcasting is suitable for moderate to high request arrival rate Real-time video transcoding necessary for ‘Quality Degradation’ approach is possible only on high- end servers
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23 Algorithm Design We consider an adaptive & hybrid approach: Adaptive different combinations of algorithms utilized reacting to change in admission / VCR resumption request arrival pattern Hybrid different combinations of algorithms utilized depending on the initial system parameter restrictions
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24 Current Work Current proposed system Based on SS-VoD, uses a combination of 3 approaches Staggered broadcasting Batched patching Precision reduction C.H. Lee, Y. B. Lee, “Design, Performance Analysis and Implementation of a Super-Scalar Video-on-Demand System”
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25 Current Work – Staggered Broadcasting SS-VoD architecture Staggered broadcasting by static multicast channels Dynamic multicast channels for admission patching and VCR-like functions resumptions Problem: Even a small (0.7 time per client) Prob(VCR-op) saturates the whole system (1 movie, L = 9500, 25/25 channel allocation, arrival rate: 0.1 /s) (admission wait 6.58 143.01) static multicast channels TrTr time L dynamic multicast channels
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26 Current Work – Batched Patching Motivation: Attempt to minimize server loading due to VCR resumptions by multicasting Algorithm: Admission / merging requests of the same target point are served by one single dynamic multicast channel Result: Able to reduce channel requirement for dynamic admission Problem: VCR resumption request target points are sparsely distributed in time domain, and it is impossible to form a batch merging request 1 merging request 2 batched merging request 1
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27 Current Work – Precision Reduction Motivation: Try to maximize VCR resumption batch size by reduction of seeking accuracy Algorithm #1: All VCR resumption requests fall within a window of pp +/- t w are served as a batch pp 1 pp 1 ’ pp 2 ’ twtw twtw pp 2 twtw twtw batching
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28 Current Work – Precision Reduction Algorithm #2: Restrict clients to seek to predefined points only (chapter-based seeking) Result: Further reduce bandwidth requirement by batching pre-defined chapter seek points L movie
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29 Future Work Method to further increase batch size Investigation of applicability of transition patching (recursive patching) on current system Ying Cai, Kien A. Hua, “An efficient bandwidth-sharing technique for true video on demand systems,” Proceedings of the seventh ACM international conference on Multimedia, 1999, Orlando, Florida, United States
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30 Q & A Thank you
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