DISTRIBUTED ADAPTATION   DECISION-TAKING FRAMEWORK ANDSCALABLE VIDEO CODING TUNNELING FOREDGE AND IN-NETWORK MEDIA ADAPTAT...
OUTLINE  Introduction & Problem Statement  Research Challenges  ALICANTE Adaptation Framework          Adaptation & SV...
INTRODUCTION & PROBLEM STATEMENT  Universal Multimedia Access (UMA)          Evolution of device and network infrastruct...
RESEARCH CHALLENGES  Distributed adaptation decision-taking framework          Where to adapt? – at source, in-network, ...
ALICANTE ADAPTATION FRAMEWORK  FP7 ICT project          "Media Ecosystem Deployment through Ubiquitous           Content...
ALICANTE ADAPTATION FRAMEWORK                       End-to-End Multimedia Communication (MPEG-2, MPEG-4, AVC, SVC, ...)   ...
ADAPTATION & SVC TUNNELING  Adaptation Decision-Taking Framework (ADTF) coordinating   local adaptation decisions of modu...
TARGETED RESEARCH OUTCOMES  Guidelines for scalable media encoding/transcoding parameters   (with SVC as example)  Guide...
PROPOSED INTEGRATED TEST-BEDMichael Grafl et al.   Distributed ADTF and SVC Tunneling for Edge and In-Network Media Adapta...
SCIENTIFIC RESULTS ACHIEVED SO FAR  Achieved results          Quality impact of SVC tunneling using MPEG-2 as           ...
RC MODES FOR SVC TUNNELING  Comparing rate control (RC) modes for SVC tunneling          Extended previous tests [3] to ...
RESULTS (1)                                                                MainConcept                          MainConcep...
RESULTS (2)                                                     MainConcept MainConcept   Target Quality                  ...
RESULT EVALUATION  Less quality impact for VBR mode  CBR mode: SVC tunneling more bandwidth   efficient than MPEG-2 simu...
CONCLUSIONS  Research challenges and key innovations for edge   and in-network adaptation              SVC tunneling    ...
SELECTED LITERATURE [1] F. Pereira and I. Burnett, "Universal multimedia experiences for     tomorrow," IEEE Signal Proces...
THANK YOU FOR YOUR ATTENTION!                                                                               Questions?    ...
Upcoming SlideShare
Loading in …5
×

Distributed Adaptation Decision-Taking Framework and Scalable Video Coding Tunneling for Edge and In-Network Media Adaptation

673 views

Published on

Existing and future media ecosystems need to cope with the ever-increasing heterogeneity of networks, devices, and user characteristics collectively referred to as (usage) context. The key to address this problem is media adaptation to various and dynamically changing contexts in order to provide a service quality that is regarded as satisfactory by the end user. The adaptation can be performed in many ways and at different locations, e.g., at the edge and within the network resulting in a substantial number of issues to be integrated within a media ecosystem. This paper describes research challenges, key innovations, target research outcomes, and achievements so far for edge and in-network media adaptation by introducing the concept of Scalable Video Coding (SVC) tunneling.

Published in: Technology
0 Comments
0 Likes
Statistics
Notes
  • Be the first to comment

  • Be the first to like this

No Downloads
Views
Total views
673
On SlideShare
0
From Embeds
0
Number of Embeds
3
Actions
Shares
0
Downloads
11
Comments
0
Likes
0
Embeds 0
No embeds

No notes for slide

Distributed Adaptation Decision-Taking Framework and Scalable Video Coding Tunneling for Edge and In-Network Media Adaptation

  1. 1. DISTRIBUTED ADAPTATION DECISION-TAKING FRAMEWORK ANDSCALABLE VIDEO CODING TUNNELING FOREDGE AND IN-NETWORK MEDIA ADAPTATION Michael Grafl, Christian Timmerer, Markus Waltl, George Xilouris, Nikolaos Zotos, Daniele Renzi, Stefano Battista, and Alex Chernilov TEMU 2012, Heraklion, Greece, July 31, 2012Michael Grafl et al. Distributed ADTF and SVC Tunneling for Edge and In-Network Media Adaptation 1
  2. 2. OUTLINE  Introduction & Problem Statement  Research Challenges  ALICANTE Adaptation Framework  Adaptation & SVC Tunneling  Targeted Research Outcomes  Proposed Integrated Test-Bed  Scientific Results Achieved So Far  RC Modes for SVC Tunneling  Results  Result Evaluation  ConclusionsMichael Grafl et al. Distributed ADTF and SVC Tunneling for Edge and In-Network Media Adaptation 2
  3. 3. INTRODUCTION & PROBLEM STATEMENT  Universal Multimedia Access (UMA)  Evolution of device and network infrastructure  Heterogeneity of devices, platforms, and networks  Scalable Video Coding (SVC): bitstream consists of cumulative layers that refine the video (resolution, framerate, bitrate)  SVC tunneling approach featuring edge and in-network media adaptation (for streaming)  Content-Aware Networking (CAN) as evolutionary approach towards the Future InternetMichael Grafl et al. Distributed ADTF and SVC Tunneling for Edge and In-Network Media Adaptation 3
  4. 4. RESEARCH CHALLENGES  Distributed adaptation decision-taking framework  Where to adapt? – at source, in-network, receiver, and combinations thereof  When to adapt? – at request and during delivery  How often to adapt? – too often (risk: flickering), too seldom (risk: stalling)  How to adapt? – optimization towards resolution, framerate, SNR (bitrate), accessibility, etc.; (too) many possibilities  Efficient, scalable SVC tunneling and signaling thereof  Low (end-to-end) delay, minimum quality degradation, scalability (# parallel sessions)  Impact on the Quality of Service/Experience (QoS/QoE)  Trade-off (for certain use cases and applications); QoS  QoEMichael Grafl et al. Distributed ADTF and SVC Tunneling for Edge and In-Network Media Adaptation 4
  5. 5. ALICANTE ADAPTATION FRAMEWORK  FP7 ICT project  "Media Ecosystem Deployment through Ubiquitous Content-Aware Network Environments"  Goal: New Home-Box layer and CAN layer with cross-layer adaptation enabling cooperation between providers, operators, and end-users  2 new virtual layers  Home-Box (HB) Layer: enhanced home gateways  CAN Layer: content-aware adaptation of SVC at Media-Aware Network Elements (MANEs)Michael Grafl et al. Distributed ADTF and SVC Tunneling for Edge and In-Network Media Adaptation 5
  6. 6. ALICANTE ADAPTATION FRAMEWORK End-to-End Multimedia Communication (MPEG-2, MPEG-4, AVC, SVC, ...) Context- Aware Adaptation HB HB Home-Box Layer HB HB HB SVC (Layered-Multicast) Tunnel CAN ... CAN Dynamic, Network-Aware MANE MANE MANE MANE Adaptation Autonomous System ... Autonomous SystemMichael Grafl et al. Distributed ADTF and SVC Tunneling for Edge and In-Network Media Adaptation 6
  7. 7. ADAPTATION & SVC TUNNELING  Adaptation Decision-Taking Framework (ADTF) coordinating local adaptation decisions of modules at  the content source;  the border to the user (Home-Box); and  within the network at MANEs  SVC (layered-multicast) tunnel  Adaptation of scalable media resource at MANE  At the border to the user (Home-Box), adaptation modules are deployed enabling device-independent access  Key Innovations  Better network resource utilization & maintaining a satisfactory Quality of Experience  Adaptation decision aggregation and propagation  Distributed coordination with CAN layer for optimal adaptation & improved bandwidth usageMichael Grafl et al. Distributed ADTF and SVC Tunneling for Edge and In-Network Media Adaptation 7
  8. 8. TARGETED RESEARCH OUTCOMES  Guidelines for scalable media encoding/transcoding parameters (with SVC as example)  Guidelines for distributed adaptation decision-taking framework  Enhancement of  decision-taking algorithm by exploiting active and passive monitoring  SVC adaptation based on network load/conditions and QoS constraints using a content-aware approach  Assessment of the performance and scalability (e.g., number of flows, flow traffic profile)  computing resources utilized (e.g., CPU and memory)  network related metrics (e.g., processing delay per flow, maximum achieved bandwidth)  Mappings of network and device monitoring parameters  Enable prediction of QoE; validation through subjective quality assessments  Holistic approach for in-network adaptation applying different adaptation policies per content-aware virtual networkMichael Grafl et al. Distributed ADTF and SVC Tunneling for Edge and In-Network Media Adaptation 8
  9. 9. PROPOSED INTEGRATED TEST-BEDMichael Grafl et al. Distributed ADTF and SVC Tunneling for Edge and In-Network Media Adaptation 9
  10. 10. SCIENTIFIC RESULTS ACHIEVED SO FAR  Achieved results  Quality impact of SVC tunneling using MPEG-2 as starting point: baseline for further research [3]  Initial performance evaluations of SVC streaming and real-time in-network adaptation [4]  End-to-end QoS control including a model for QoS-QoE mapping [5]Michael Grafl et al. Distributed ADTF and SVC Tunneling for Edge and In-Network Media Adaptation 10
  11. 11. RC MODES FOR SVC TUNNELING  Comparing rate control (RC) modes for SVC tunneling  Extended previous tests [3] to compare SVC tunneling for • Variable bitrate (VBR) constant quantization parameter (QP) • Constant bitrate (CBR) • Different codecs: bSoft, MainConcept • SVC config: 4 medium-grained scalability (MGS) layers  Procedure: • Pixel-domain transcoding (PDT) from MPEG-2 to SVC • Transcode resulting bitstream back from SVC to MPEG-2 • Measured Bjontegaard Delta (BD) Y-PSNR • Compared required bandwidths to MPEG-2 simulcastMichael Grafl et al. Distributed ADTF and SVC Tunneling for Edge and In-Network Media Adaptation 11
  12. 12. RESULTS (1) MainConcept MainConcept bSoft (VBR) (VBR) (CBR) Sequence BD- BD- BD- BD- BD- BD- PSNR bitrate PSNR bitrate PSNR bitrate [dB] [%] [dB] [%] [dB] [%]foreman -2.08 50.3 -2.03 53.7 -2.40 61.6container -1.57 38.2 -1.99 51.0 -2.91 66.9hall_monitor -0.75 22.6 -1.40 54.1 -1.82 73.6stefan -2.59 41.0 -2.09 32.1 -2.88 53.4Average -1.74 38.04 -1.88 47.7 -2.50 63.9Table 1: Bjontegaard Delta for SVC tunnelingMichael Grafl et al. Distributed ADTF and SVC Tunneling for Edge and In-Network Media Adaptation 12
  13. 13. RESULTS (2) MainConcept MainConcept Target Quality bSoft (VBR) (VBR) (CBR) SVC SVC MPEG-2 SVC MPEG-2 SVC MPEG-2 VBR CBR encoding tunnel simulcast tunnel simulcast tunnel simulcast [QP] [Mbps] config [kbps] [kbps] [kbps] [kbps] [kbps] [kbps]Q1 16 3 5333 3041 3694 3454 3286 4721Q2 20 2 3446 2025 2418 2082 2242 3191Q3 24 1.5 2201 1452 1650 1277 1687 2093Q4 28 1 1438 1102 1132 900 1109 1287Average 3105 1905 2224 1928 2081 2823 Table 2: Comparison of required bandwidths for SVC tunneling vs. MPEG-2 simulcast Michael Grafl et al. Distributed ADTF and SVC Tunneling for Edge and In-Network Media Adaptation 13
  14. 14. RESULT EVALUATION  Less quality impact for VBR mode  CBR mode: SVC tunneling more bandwidth efficient than MPEG-2 simulcast (~26% reduction)  Bandwidth efficiency of SVC tunneling depends on number and configuration of SVC layers (mainly on quality of Base Layer)  Other scenarios: VBR mode SVC tunneling favorable to MPEG-2 simulcast if only server-side transcoding needed (i.e., client supports SVC)Michael Grafl et al. Distributed ADTF and SVC Tunneling for Edge and In-Network Media Adaptation 14
  15. 15. CONCLUSIONS  Research challenges and key innovations for edge and in-network adaptation  SVC tunneling  Distributed Adaptation  Performance evaluations of SVC streaming  End-to-end QoS control & QoS-QoE mapping approach  CBR and VBR mode for SVC tunneling compared  Integrated test-bed proposed  Future work: HD content; subjective tests; integrate QoS-QoE mapping; multi-video rate allocationMichael Grafl et al. Distributed ADTF and SVC Tunneling for Edge and In-Network Media Adaptation 15
  16. 16. SELECTED LITERATURE [1] F. Pereira and I. Burnett, "Universal multimedia experiences for tomorrow," IEEE Signal Processing Magazine, vol.20, no.2, Mar. 2003. [2] European Commission, "ALICANTE, Annex I – Description of Work," FP7-ICT-2009-4, Grant agreement no. 248652, 2009. [3] M. Grafl, C. Timmerer, and H. Hellwagner, "Quality Impact of Scalable Video Coding Tunneling for Media-Aware Content Delivery," Proc. ICME’11, Barcelona, Spain, July 2011. [4] N. Zotos et al., "Performance evaluation of H264/SVC streaming system featuring real-time in-network adaptation," Proc. IWQoS’11, San Jose, California, June 2011. [5] B. Shao et al., "An Adaptive System for Real-Time Scalable Video Streaming with End-to-End QoS Control," Proc. WIAMIS’10, Desenzano Del Garda, Italy, Apr. 2010. [6] G. Bjontegaard, "Improvements of the BD-PSNR model," ITU-T SG16/Q6, 2008.Michael Grafl et al. Distributed ADTF and SVC Tunneling for Edge and In-Network Media Adaptation 16
  17. 17. THANK YOU FOR YOUR ATTENTION! Questions? http://ict-alicante.eu/ http://itec.uni-klu.ac.at/~mgraflMichael Grafl et al. Distributed ADTF and SVC Tunneling for Edge and In-Network Media Adaptation 17

×