1. Polishing: A Technique to Reduce Variations in Cached Layer-Encoded Video By Michael Zink, Oliver Heckmann, Jens Schmitt, Andreas Mauthe, Ralf Steinmetz Presented By Subramanian Mohan

2. Caching Layer-encoded Video Layer encoded video can only be cached according to the available bandwidth of path between server and the cache, if congestion controlled transport medium is applied. Hence the copy of video stored in the cache might contain large amount of layer variations.

3. Caching Layer-encoded Video Video to the client is sent from the cache in two cases. –If the server or the link between the server and the cache is down, or –Server does not have additional capacity to allow retransmission in addition to already active streams

4. Problem When the cache forwards such a high layer variant video to the client, it might be annoying to the viewer, due to high variation in quality.

5. Solution In order to increase the perceived quality of layered video, layer variations should be minimized. By omitting the transmission of certain segments, especially if that reduces the amount of layer variations, quality of the video can be improved. POLISHING DOES THIS...

6. Applications of Polishing 1.Polishing reduces Layer variations in a layer- encoded video by omitting the transmission of certain segments to the client. Challenge is identifying those segments that should not be transmitted. 2.Since polishing identifies segments that are less important in relation to quality, this can be combined with cache replacement method to cache more number of objects.

7. Effect of quality variations The negative effect of quality variations has two dimensions. 1.Frequency of Variations 2.Amplitude of Variations

8. Spectrum Spectrum is a metric to gauge the quality of Layer-encoded video Spectrum takes into account both the frequency and the amplitude of quality variations Small spectrum value indicates good quality while large value indicated poor quality

9. Spectrum Parameters: h t - number of layers in time slot t, t = 1,...,T z t – indication if a step in time slot t, z t  {0,1}, t = 1,..., T

10. Spectrum Here, at time t = 1, ht = 5 and at time t = 2, ht = 4 and so on and so forth

11. Spectrum Average quality levels for entire time period for 1 to T is given by, h t contains the highest layer of the polished video at time t.

12. Spectrum Hence, the Amplitude variations can be got by the term, Frequency variation is captured by z t

13. Spectrum Finally the spectrum of a cached layered video v is represented by,

14. Spectrum Amplitude variation term is squared so that the larger amplitude variation gets higher weight Frequency variation term Amplitude variation term

15. Spectrum But, Spectrum has a drawback if it is to be used for polishing, in deciding which packets to be dropped. Why?

16. Spectrum Reason: Spectrum, being a quality metric, becomes 0 for the case when no layer changes occur irrespective of the number of layers the video object consists. Hence, even for a video with just the base layer, the spectrum shows low value, indicating a high quality. Spectrum ignores the number of layers of video that is played out at the receiver. This reduces the quality of video drastically and this effect is termed as Over-polishing

17. Polishing Goals: To Minimize the spectrum (reduce quality variations) and At the same time Maximize the number of segments played out to the client. This becomes a multi-objective optimization problem and can be formulated as mixed integer programming problem.

18. Polishing

21. Constraints

22. Polishing Term A represents Number of Segments played out to the client Term B represents the quality variations in the layer-encoded video AB

23. Polishing AB The two parameters u l and p describe the utility of the video playout. The parameter u l takes into account the number of layers in the layer-encoded video and hence avoids over-polishing Parameter p represents the utility loss due to change in the number of layers that are played back.

24. Polishing The optimization problem conveys that, 1.Term A, that represents the Number of segments played out, should be Maximized and 2.Term B that represents the layer variations, should be Minimized AB

25. Effectiveness of Polishing in increasing Perceived Quality

26. Simulation Results 100 video objects were randomly created and polished. The avg. total number of segments and avg. spectrum are calculated before and after polishing. The polishing method is compared with two version of heuristics. –Heuristic (1) drops the top layer. –Heuristic (2) drops the top TWO layers.

27. Utility Parameters

29. Polishing with Cache Replacement Simulation is done on cache with an initial fill level of 50 unpolished video objects. Then 50, additional objects are added incrementally, one per time slot, into the cache. The polishing technique is compared with a non-polished cache replacement method and two heuristic methods.

30. Cache Replacement

32. The parameter values chosen influenced the behavior of the cache replacement method. Thus the integration of polishing with cache replacement is beneficial because higher amount of video objects are cached and layer changes are reduced.

33. Thanks!!