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Optimal Multicast Smoothing of Streaming Video over an Internetwork

Optimal Multicast Smoothing of Streaming Video over an Internetwork. S. Sen, D. Towsley, Z-L. Zhang, J. Dey {sen,towsley}@cs.umass.edu zhzhang@cs.umn.edu dey@gte.com Presented by : Shubho Sen. Streaming VBR Video Distribution. Problem Setting One-many streaming of prerecorded video

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Optimal Multicast Smoothing of Streaming Video over an Internetwork

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  1. Optimal Multicast Smoothing of Streaming Video over an Internetwork S. Sen, D. Towsley, Z-L. Zhang, J. Dey {sen,towsley}@cs.umass.edu zhzhang@cs.umn.edu dey@gte.com Presented by :Shubho Sen

  2. Streaming VBR Video Distribution Problem Setting • One-many streaming of prerecorded video • High bandwidth, multi-timescale burstiness • Heterogeneous client and network resources Goal: Efficient transmission schemes • Use application-aware multicast of smoothed video • Q. how should VBR video be shaped/smoothed for transmission through network? Video Server Client

  3. Outline • Review single link smoothing problem • Multicast smoothing and differential caching • Optimal smoothing for multicast problem • Benefits - trace based evaluation • Summary

  4. Single Link Problem Goal :Reduce peak and variability on path from proxy to client Doworkahead transmission proxy client A(t) S(t) D(t-w) B Bs streaming video Bsbits sourcebuffer at proxy A(t) bits arrive by time t S(t) bits sent by proxy by time t Bbits sink buffer at client D(t-w)bits playback by time t wstartup delay

  5. Single Link Smoothing Feasible schedule should not overflow or underflow buffers : Lower Constraint = max{ D(t-w), A(t) - Bs} Upper Constraint = min{ D(t-w)+ B, A(t) } Solution [Salehi:96] • O(N) shortest path algorithm finds schedule S that minimizes • peak rate Smoothing benefit increases with buffer size S Upper • rate variance Lower Cum. bytes w time t

  6. Multicast Smoothing root root - 0 bi- buffer size at node i D- consumption schedule for leaf node x Si- transmission schedule for incoming link of node i (link i) A b0 Use internal buffers for Differential Caching - Store difference between transmissions to clients with smaller and larger buffers Q.What should the smoothed transmission schedule be along each link ? S1 S2 ... b2 b1 Link i Si bi Node i Sx ... Sy bx clients by D D

  7. Multicast Smoothing Problem Root A b0 ... • Set of schedules {Si} should be feasible • Sx< Si and Sx> Si - bi • Inter-related set of schedules {Sj} Approach: Transform to multipleindependentsingle-link problems bP Parent Si Link i bi Node i Sx Link x bx Node x by D D

  8. Root ... A b0 Transformation to Single Link Problem Independent single link problem bp Parent Source buffer Sink buffer Si D A Link i Bi Bs Si = ? bi Node i Bs ,Bi: Effective buffer capacities Can showBs= b0 + …. + bp Bi = ? bx by D D

  9. Computing Bi Bi depends on children: First estimate= EBi EBm = bm , if m is a leaf = bm + min(EBk) , otherwise k is child Example:EBx = bx , EBy = by EBi = bi + min (EBx , EBy) bp Parent Link i bi Node i bi EBi= bi + bx bx bx by D D

  10. Computing Bi (contd) Bi depends on parent :cannot exceed Bp • depends on other nodes Bi = min (EBj | j on path to root) EBp bp Parent Link z EBi Link i EBz bi Node i bz bx • Recursively compute Bi by D D

  11. Multicast Smoothing Solution • Converted multicast problem to multiple independent single link problems • ComputeSifor each problem - use along link i Key Properties • Set {Si} is feasible • {Si} : set of globally optimal smoothed schedules among all feasible sets Si: smoothest schedule along link i

  12. Demonstration of Benefits Setting • CBR reservation model • Complete 3-ary distribution tree, depth = 4, video stored at root • Client buffers in (512 KB, 32 MB) • Identical buffer sizes at internal nodes Performance metrics • Total bandwidth requirements • Sum of bw requirements on path to smallest client 17 min MPEG2 Blues Brothers (peak rate = 44 Mbps, mean = 1.48 Mbps)

  13. How much does internal buffering and smoothing help ? • Substantial benefits with smoothing • Small internal buffering gives substantial benefits • Useful to place buffers on path to smallest client

  14. Summary • Developed optimal smoothing algorithm for multicasting in internetworking environments • Integrates smoothing with differential caching • Demonstrated smoothing benefits with example • Rate constrained problem (paper) • find minimum buffer allocation to nodes in distribution tree, and set of optimal smoothed transmission schedules

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