idash: improved Dynamic Adaptive Streaming over HTTP using Scalable Video Coding

Transcription

1 idash: improved Dynamic Adaptive Streaming over HTTP using Scalable Video Coding Yago Sánchez, Thomas Schierl, Cornelius Hellge, Thomas Wiegand - Fraunhofer HHI, Germany Dohy Hong - N2N Soft, France Danny De Vleeschauwer, Werner Van Leekwijck, Bell Labs - Alcatel Lucent, Belgium Yannick Lelouedec - Orange Labs FT, France

2 OUTLINE Motivation HTTP Streaming SVC Caching Results Conclusion

3 MOTIVATION Service providers have resorted to use HTTP/TCP for Multimedia Delivery Relying on RTP/UDP may result in traversal problems with NATs and Firewalls HTTP/TCP allows re-useing existing HTTP cache infrastructures Different type of users => poor cache performance Different equipment capabilities Different connectivity characteristics Resources at the network limited Capacity on the links shared Storage in the HTTP cache not enough

4 HTTP STREAMING - INTRODUCTION HTTP caches placed in the network reducing the load on the server and transit link server kbps transit link R (kbps) = 768 Video split in smaller segments/ chunks and transported over HTTP 768 kbps 768 kbps Different representation of the video to allow the users to request the one that matches at best their capabilities 768 kbps 768 kbps 0 kbps Internet 768 kbps 768 kbps

5 HTTP STREAMING EFFECT OF MULTIPLE REPRESENTATIONS Multiple Representations Video on Demand (MR-VoD) is less effective for caches performance than Single Representation Video on Demand (SR- VoD) cache- hit- ratio 1 0,9 0,8 0,7 0,6 0,5 0,4 0,3 0,2 0, cache capacity (C) [media units] SR- VoD MR- VoD

6 HTTP STREAMING EFFECT OF MULTIPLE REPRESENTATIONS With MR-VoD more data has to be sent from the server (though the transit link) than with SR-VoD 250 Transit link traffic [Mbps] SVC- VoD MR- VoD cache capacity (C) [media units]

7 HTTP STREAMING Proposed solution: USE SCALABLE VIDEO CODING (SVC) TO IMPROVE CACHE PERFORMANCE

8 SVC (SCALABLE VIDEO CODING) This works focuses on SNR Scalability Representations are created from sub-streams of the whole SVC stream Different representations mapped to Operation Points (OP) OPs based on complete Layers => If many it may increase the SVC overhead OPs also based on smaller parts of layers.

9 SVC (SCALABLE VIDEO CODING) - EXAMPLE Different representations/operation Points (OP) OPs also based on smaller parts of layers. GOP Border GOP Border T3 T2 T1 T0

10 SVC (SCALABLE VIDEO CODING) Different representations/operation Points (OP) OPs also based on smaller parts of layers. GOP Border GOP Border T3 T2 T1 T0 OP 0

11 SVC (SCALABLE VIDEO CODING) - EXAMPLE Different representations/operation Points (OP) OPs also based on smaller parts of layers. GOP Border GOP Border T3 T2 T1 T0 OP 1

12 SVC (SCALABLE VIDEO CODING) - EXAMPLE Different representations/operation Points (OP) OPs also based on smaller parts of layers. GOP Border GOP Border T3 T2 T1 T0 OP 2

13 SVC (SCALABLE VIDEO CODING) - EXAMPLE Different representations/operation Points (OP) OPs also based on smaller parts of layers. GOP Border GOP Border T3 T2 T1 T0 OP 3

14 SVC (SCALABLE VIDEO CODING) - EXAMPLE Different representations/operation Points (OP) OPs also based on smaller parts of layers. GOP Border GOP Border T3 T2 T1 T0 OP 5

15 SVC (SCALABLE VIDEO CODING) - EXAMPLE Different representations/operation Points (OP) OPs also based on smaller parts of layers. GOP Border GOP Border T3 T2 T1 T0 OP 7

16 CACHING - I Caches store data supposed to be asked in the future to relieve the server from having to send directly the data There are many different cache replacement algorithms that improve the cache performance based on some especial criteria/metric LRU: Least Recently used LFU: Least Frequently used CC: Chunk-based Caching

17 CACHING - I Caches store data supposed to be asked in the future to relieve the server from having to send directly the data There are many different cache replacement algorithms that improve the cache performance based on some especial criteria/metric LRU: Least Recently used LFU: Least Frequently used CC: Chunk-based Caching Chunk #n+3 Certain video file Other files Chunk #n Chunk #n+1 & #n+2 Chunk #n+4 & #n+5

18 CACHING - II Cache performance can be easily improved by using SVC Cache storage better used than with MR-VoD Uneven distribution of request = more pronounced

19 CACHING - CAPACITY USAGE COMPARISON rep3 rep2 rep1 MR-VoD Removed files from cache File 7 File 6 File 5 File 4 File 3 File 2 File 1 SVC-VoD rep3 rep2 rep1 File 7 File 6 File 5 File 4 File 3 File 2 File 1

20 CACHING EXAMPLE MR-VoD server Q1 Q2 Q Kbps R (kbps) = wired Q3 768 Kbps 1280 Kbps 768 Kbps 512 Kbps wired Q2 wireless 512 Kbps Internet 256 Kbps wireless Q2 Q1

21 CACHING EXAMPLE MR-VoD server Q1 Q2 Q3 0 Kbps R (kbps) = wired Q3 256 Kbps 768 Kbps wired Q2 wireless Q2 256 Kbps Q1 wireless Internet 768 Kbps Q3 Q1 wireless

22 CACHING EXAMPLE SVC-VoD server 844 Kbps Q3 Q2 Q1 R (kbps) wired Q3 844 Kbps 844 Kbps 550 Kbps 550 Kbps wired Q2 wireless 550 Kbps Internet 256 Kbps wireless Q2 Q1

23 CACHING EXAMPLE SVC-VoD server 0 Kbps Q3 Q2 Q1 R (kbps) wired Q3 0 Kbps 294 Kbps wired Q2 wireless Q2 256 Kbps Q1 wireless Internet 844 Kbps Q3 Q1 wireless

24 SIMULATIONS SIMULATED SCENARIO Statistics for users requests extracted from a deployed system Measured during a month More than 5000 files among which the users can choose 3400 requests per day on average This real system is SR-VoD Cross traffic in access links 2 scenarios considered - Heavy cross traffic in Access link - Light cross traffic in Access link

25 SIMULATIONS AVAILABLE REPRESENTATIONS 4 representations for each video to allow adaptation SVC overhead of 10% compared to AVC Rate Distribution of the representations Codec Rep. 1 Rep.2 Rep.3 Rep. 4 AVC 500 kbps 1000 kbps 1500 kbps 2000 kbps SVC 500 kbps 1066 kbps 1633 kbps 2200 kbps

26 SIMULATIONS AVAILABLE REPRESENTATIONS Needed throughput in transit link and capacity in caches for all reps AVC = 5000 kbps per video = (video of 90 min) 3375 MB SVC = 2200 kbps per video = (video of 90 min) 1485 MB Rate Distribution of the representations Codec Rep. 1 Rep.2 Rep.3 Rep. 4 AVC 500 kbps 1000 kbps 1500 kbps 2000 kbps SVC 500 kbps 1066 kbps 1633 kbps 2200 kbps

27 CROSS TRAFFIC Four state Markov-chain simulated p 11 p 22 p 33 p 44 p12 p23 p P=[p ij ] p 21 p 32 p 43 Cross traffic characterization: Mean state sojourn time ti E[ t ] ( t + 1) * p *( 1 p ) i = i ii ii = t = 0 1 i 1 p Average percentage of time in each state p i : π * P = π ii

28 HEAVY CROSS TRAFFIC Transition matrix P = Mean state sojourn time E[t i ] = 40 min (for segment of 10 sec length) Average percentage of time in each state 25% of the time in each state

29 LIGHT CROSS TRAFFIC Transition matrix P = Mean state sojourn time E[t i ]=(approx.){2min, 2min, 10min, 40min}(for segment of 10 sec length) Average percentage of time in each state p={9.1%, 9.5%, 19.1%, 62.3%}

30 RESULTS-HEAVY CROSS TRAFFIC Comparison of cache efficiency with MR-VoD and SVC-VoD Cache capacity (media units) LRU CC MR-VoD SVC-VoD MR-VoD SVC-VoD % 45.6 % 42.9 % 56.6 % % 58.2 % 52.0 % 64.5 % % 69.0% 61.5% 72.0%

31 RESULTS-HEAVY CROSS TRAFFIC Comparison of cache efficiency with MR-VoD and SVC-VoD cache- hit- ratio 1 0,9 0,8 0,7 0,6 0,5 0,4 0,3 0,2 0, cache capacity (C) [media units] MR- VoD layer1 layer3 SVC- VoD layer2 layer4

32 RESULTS-LIGHT CROSS TRAFFIC Comparison of cache efficiency with MR-VoD and SVC-VoD cache- hit- ratio 1 0,9 0,8 0,7 0,6 0,5 0,4 0,3 0,2 0, cache capacity (C) [media units] MR- VoD SVC- VoD layer1 layer2 layer3 layer4

33 CONCLUSIONS SVC can be efficiently encoded to get a high enough number of representations HTTP-based VoD service can be easily improved by only using SVC SVC-VoD results in a higher cache-hit-ratio and consequently in a lower traffic transmitted across the transit link between the server and the cache Further work: Study the enhanced adaptability, faster response times with SVC Advantages of using SVC in DASH for Live Streaming

34 THANKS FOR YOUR ATTENTION!!! Acknowledgments: The research leading to these results has received funding from the European Union's Seventh Framework Programme ([FP7/ ] ) under grant agreement n