Towards User-centric Video Transmission in Next Generation Mobile Networks
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Towards User-centric Video Transmission in Next Generation Mobile Networks

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There is a massive growth in mobile video consumption which outpaces the capacity improvements in next generation mobile networks. Specifically, mobile network operators face the challenge of ...

There is a massive growth in mobile video consumption which outpaces the capacity improvements in next generation mobile networks. Specifically, mobile network operators face the challenge of allocating the scarce wireless resources while maximizing the user quality of experience (QoE). The first part of this talk addresses the main challenges in uplink distribution of user-generated video content over fourth generation mobile networks. The second part explores the benefit of QoE-based traffic and resource management in the mobile network in the context of adaptive HTTP downlink video delivery.

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Towards User-centric Video Transmission in Next Generation Mobile Networks Towards User-centric Video Transmission in Next Generation Mobile Networks Presentation Transcript

  • Towards User-centric Video Transmission in Next Generation Mobile Networks Ali El Essaili Klagenfurt, February 12, 2014
  • Institute for Media Technology Prof. Dr.-Ing. Eckehard Steinbach Technische Universität München Outline  Motivation and overview  QoE-driven adaptive HTTP video delivery  QoE-driven resource allocation for LTE uplink  Conclusions February 12, 2014 A. El Essaili: Towards User-centric Video Transmission in Next Generation Mobile Networks 2
  • Institute for Media Technology Prof. Dr.-Ing. Eckehard Steinbach Technische Universität München Motivation   The majority of mobile data is streaming video and audio. The lion share of the mobile traffic is TCP/IP based. [1] http://www.sandvine.com/downloads/documents/Phenomena_1H_2012/Sandvine_Global_Internet_Phenomena_Report_1H_2012.pdf February 12, 2014 A. El Essaili: Towards User-centric Video Transmission in Next Generation Mobile Networks 3
  • Institute for Media Technology Prof. Dr.-Ing. Eckehard Steinbach Technische Universität München Overview    DASH (Dynamic Adaptive Streaming over HTTP) is standardized for mobile multimedia streaming (3GPP Rel-11, MPEG ISO/IEC 23009-1). OTT DASH provides an end-to-end server-client adaptation. The client reacts to the resources assigned by the scheduler in the operator network. Objective: Enhance the adaptive HTTP media delivery in next generation mobile networks. Standard DASH Client DASH Server LTE network Media Presentation MPD HTTP Request February 12, 2014 QoE-driven traffic management End-to-end Base station Adaptation Bit-rate estimation Segment switching A. El Essaili: Towards User-centric Video Transmission in Next Generation Mobile Networks 4
  • Institute for Media Technology Prof. Dr.-Ing. Eckehard Steinbach Technische Universität München Overview Difference to RTP-based QoE-driven optimization Application Server Find the resource allocation which maximizes overall utility based on application and channel conditions. ∑ … LTE network Application utility function QoE optimizer Optimal rate for each user Channel information Mobile Users Rate 1) In-network content adaptation is costly, may react late 2) DASH provides inherent adaptivity by encoding the same content at multiple bit-rates Traffic management (e.g., transcoding, packet dropping) Base station [1] S. Khan, Y. Peng, E. Steinbach, M. Sgroi, W. Kellerer, “Application-driven cross-layer optimization for video streaming over wireless networks,” IEEE Communications Magazine, 2006. [2] W. Kellerer, D. Svetoslav, E. Steinbach, M. Sgroi, S. Khan, EP1798897, granted June, 2008. February 12, 2014 A. El Essaili: Towards User-centric Video Transmission in Next Generation Mobile Networks 5
  • Institute for Media Technology Prof. Dr.-Ing. Eckehard Steinbach Technische Universität München Outline  Motivation and overview  QoE-driven adaptive HTTP video delivery  QoE-driven resource allocation for LTE uplink  Conclusions February 12, 2014 A. El Essaili: Towards User-centric Video Transmission in Next Generation Mobile Networks 6
  • Institute for Media Technology Prof. Dr.-Ing. Eckehard Steinbach Technische Universität München QoE-driven adaptive HTTP video delivery Proposed QoE-Proxy approach Target DASH Representation Proxy Rewrite client requests DASH Server LTE network Rate Utility Media segments QoE optimizer Optimal rate for each client Channel information Standard DASH Client Rate Resource shaper TCP rate MPD HTTP Request Base station  The QoE optimizer returns the optimal rate of each user.  The proxy rewrites the HTTP requests and forwards them to the DASH server.  The DASH Server and the DASH clients are unaware of the proxy operation. February 12, 2014 A. El Essaili: Towards User-centric Video Transmission in Next Generation Mobile Networks 7
  • Institute for Media Technology Prof. Dr.-Ing. Eckehard Steinbach Technische Universität München QoE-driven adaptive HTTP video delivery QoE-Reactive scheme Target DASH Representation LTE network DASH Server Utility Media segments QoE optimizer Optimal rate for each client Channel information Standard DASH Client Rate Resource shaper TCP rate MPD HTTP Request Base station  The TCP throughput of each client is shaped according to the optimal rate.  The streaming rate is determined by the standard DASH client. February 12, 2014 A. El Essaili: Towards User-centric Video Transmission in Next Generation Mobile Networks 8
  • Institute for Media Technology Prof. Dr.-Ing. Eckehard Steinbach Technische Universität München QoE-driven adaptive HTTP video delivery Utility curves [1] L. Choi, M. Ivrlac, E. Steinbach, and J. Nossek, “Sequence-level methods for distortion-rate behavior of compressed video,” IEEE ICIP’05 [2] S. Khan, S. Duhovnikov, E. Steinbach, and W. Kellerer, “MOS-based multiuser multiapplication cross-layer optimization for mobile multimedia communication,” Advances in Multimedia, 2007 February 12, 2014 A. El Essaili: Towards User-centric Video Transmission in Next Generation Mobile Networks 9
  • Institute for Media Technology Prof. Dr.-Ing. Eckehard Steinbach Technische Universität München QoE-driven adaptive HTTP video delivery Optimization schemes Scheme Description QoE-Server The server encodes the video stream at the optimal rate (e.g., managed content). QoE-Proxy Proposed proxy-based approach (OTT content). QoE-d-Proxy Similar to the QoE-Proxy scheme. However, the optimizer uses discrete utility representations. QoE-Reactive We shape the TCP throughput. The actual streaming rate, however, is determined by the client. Non-Opt Standard OTT DASH streaming (Reference scheme) February 12, 2014 A. El Essaili: Towards User-centric Video Transmission in Next Generation Mobile Networks 10
  • Institute for Media Technology Prof. Dr.-Ing. Eckehard Steinbach Technische Universität München QoE-driven adaptive HTTP video delivery Simulation parameters Simulation parameters LTE bandwidth 5 MHz Number of PRBs 25 CQI update Application parameters Video codec H.264 AVC, CIF, 30 fps 2 sec Segment size 2 sec Channel model Urban macrocell Number of clients 8 User speed 30 km/hr Simulation time 60 sec PSNR-MOS mapping Linear: {(1, 30 dB), (4.5, 42 dB)} Simulation runs 50 Client Standard Microsoft Smooth Streaming February 12, 2014 A. El Essaili: Towards User-centric Video Transmission in Next Generation Mobile Networks 11
  • Institute for Media Technology Prof. Dr.-Ing. Eckehard Steinbach Technische Universität München QoE-driven adaptive HTTP video delivery Experimental results  CDF of the mean MOS for 8 users over 50 runs 1 0.9 Mean MOS gain 0.8 QoE-Reactive CDF 0.6 0.19 QoE-Proxy 0.7 0.34 QoE-d-Proxy 0.49 QoE-Server 0.57 0.5 0.4 Non-Opt QoE-Reactive QoE-Proxy QoE-d-Proxy QoE-Server 0.3 0.2 0.1 0 3 3.5 4 4.5 Mean MOS February 12, 2014 A. El Essaili: Towards User-centric Video Transmission in Next Generation Mobile Networks 12
  • Institute for Media Technology Prof. Dr.-Ing. Eckehard Steinbach Technische Universität München QoE-driven adaptive HTTP video delivery Experimental results  Individual performance of 8 users over 50 runs Substantial gains for resource-demanding videos February 12, 2014 A. El Essaili: Towards User-centric Video Transmission in Next Generation Mobile Networks 13
  • Institute for Media Technology Prof. Dr.-Ing. Eckehard Steinbach Technische Universität München Subjective tests Settings  SAMVIQ (Subjective Assessment of Multimedia Video Quality) method [1]  20 test subjects after screening procedure  2 scenarios: □ Scenario 1: users move at a speed of 30km/h □ Scenario 2: users move at a speed of 120 km/h  8 users in the cell  10 seconds of video (without starting phase)  Differential MOS is used as subjective quality rating [2] □ DMOS(sequence) = R(sequence) – R(hidden ref) + 100 [1] ITU-T Rec. BT.1788 Methodology for subjective assessment of video quality in multimedia applications, 2007 [2] ITU-T Rec. P.910 Subjective video quality assessment methods for multimedia applications, 2008 February 12, 2014 A. El Essaili: Towards User-centric Video Transmission in Next Generation Mobile Networks 14
  • Institute for Media Technology Prof. Dr.-Ing. Eckehard Steinbach Technische Universität München Subjective tests User interface February 12, 2014 A. El Essaili: Towards User-centric Video Transmission in Next Generation Mobile Networks 15
  • Institute for Media Technology Prof. Dr.-Ing. Eckehard Steinbach Technische Universität München Subjective tests Overall results 100 mean DMOS (8 users) 90 80 70 60 50 mean DMOS rating 40 QoE-Proxy QoE-Reactive Non-Opt Scenario 1: 30 Km/h QoE-Proxy QoE-Reactive Non-Opt Scenario 2: 120 Km/h  Higher mean MOS, improvements more notable in dynamic scenario.  Fair user experience, up to 35% MOS increase for worst-case user. February 12, 2014 A. El Essaili: Towards User-centric Video Transmission in Next Generation Mobile Networks 16
  • Institute for Media Technology Prof. Dr.-Ing. Eckehard Steinbach Technische Universität München QoE-driven adaptive HTTP video delivery Video demo QoE-Proxy February 12, 2014 vs QoE-Reactive A. El Essaili: Towards User-centric Video Transmission in Next Generation Mobile Networks 17
  • Institute for Media Technology Prof. Dr.-Ing. Eckehard Steinbach Technische Universität München Outline  Motivation and overview  QoE-driven adaptive HTTP video delivery  QoE-driven resource allocation for LTE uplink  Conclusions February 12, 2014 A. El Essaili: Towards User-centric Video Transmission in Next Generation Mobile Networks 18
  • Institute for Media Technology Prof. Dr.-Ing. Eckehard Steinbach Technische Universität München QoE-driven resource allocation for LTE uplink Challenges February 12, 2014 A. El Essaili: Towards User-centric Video Transmission in Next Generation Mobile Networks 19
  • Institute for Media Technology Prof. Dr.-Ing. Eckehard Steinbach Technische Universität München QoE-driven resource allocation for LTE uplink Use-cases  Use-case 1: □ Service‐centric approach for uplink distribution of real‐time usergenerated video content. □ Based on QoE and popularity of the video content.  Use-case 2: □ Joint upstream of live and time‐shifted video content under scarce uplink resources. □ Transmit a basic quality in real‐time and upload a refined quality for on‐demand consumption. February 12, 2014 A. El Essaili: Towards User-centric Video Transmission in Next Generation Mobile Networks 20
  • Institute for Media Technology Prof. Dr.-Ing. Eckehard Steinbach Technische Universität München QoE-driven resource allocation for LTE uplink Use-cases  Use-case 1: □ Service‐centric approach for uplink distribution of real‐time usergenerated video content. □ Based on QoE and popularity of the video content.  Use-case 2: □ Joint upstream of live and time‐shifted video content under scarce uplink resources. □ Transmit a basic quality in real‐time and upload a refined quality for on‐demand consumption. February 12, 2014 A. El Essaili: Towards User-centric Video Transmission in Next Generation Mobile Networks 21
  • Institute for Media Technology Prof. Dr.-Ing. Eckehard Steinbach Technische Universität München QoE-driven resource allocation for LTE uplink Proposed approach  Motivation: Mobile networks will have to deal with a vast increase in user-generated video content given limited resources in the wireless uplink.  Contribution: We propose a QoE-driven approach for jointly optimizing the uplink transmission of live and on-demand videos. February 12, 2014 A. El Essaili: Towards User-centric Video Transmission in Next Generation Mobile Networks 22
  • Institute for Media Technology Prof. Dr.-Ing. Eckehard Steinbach Technische Universität München QoE-driven resource allocation for LTE uplink Application model  Utility function for video streaming is defined on the MOS scale.  A Group of Pictures (GoP) is encoded into a set of video layers with a common deadline (i.e., base layer (BL), enhancement layer (EL)).  Joint optimization of video layers with playout deadline d1 (live) and cached layers with playout deadline d2 (on-demand). S L  set of all deadlines February 12, 2014 A. El Essaili: Towards User-centric Video Transmission in Next Generation Mobile Networks 23
  • Institute for Media Technology Prof. Dr.-Ing. Eckehard Steinbach Technische Universität München QoE-driven resource allocation for LTE uplink Optimization functions  Network-based QoE optimization that maximizes the sum of utilities of K users: K arg max  U k (ck ) ( c1 ,..., c K ) k 1  Distributed QoE optimization for each user k: arg max al , Rl ,S L ,d ,lS L ,d Uk   S L ,d lS L ,d  a R s.t. S L ,d lS L ,d   a  b  MOS ( R ) l l l  ck  Ll (1  al )  H k S L ,d lS L ,d  al tl  d , S L,d lS L ,d February 12, 2014 l l l ck : instantaneous uplink capacity H k : cache size MOSl : additional QoE improvement Ll : size, Rl : instantaneous rate tl : time to transmit al : 1 if scheduled, 0 otherwise bl  {0,1} describes layer dependencies A. El Essaili: Towards User-centric Video Transmission in Next Generation Mobile Networks 24
  • Institute for Media Technology Prof. Dr.-Ing. Eckehard Steinbach Technische Universität München QoE-driven resource allocation for LTE uplink Simulation results Simulation parameters Scheme Description MOS-CLO QoE distributed and QoEdriven network optimization LTE bandwidth 5 MHz QoE distributed and PF Channel model Urban macrocell Scheduling metric Proportional Fair (PF) Number of upstream users 4: Bus, Football, Soccer, Foreman Video codec H.264/SVC, CIF, 30 fps, 4 layers Relative cache size 0.3 (Live, VoD) delay (266 ms, 20 sec) Simulation time, runs 100 sec, 20 Simulator LTE OPNET 16.0 MOS-PF 4 3,75 Mean MOS 3,5 3,25 3 2,75 2,5 2,25 2 1,75 1,5 MOS-CLO Live MOS-CLO VoD MOS-PF Live Scheme February 12, 2014 MOS-PF VoD A. El Essaili: Towards User-centric Video Transmission in Next Generation Mobile Networks 25
  • Institute for Media Technology Prof. Dr.-Ing. Eckehard Steinbach Technische Universität München QoE-driven resource allocation for LTE uplink Demo February 12, 2014 A. El Essaili: Towards User-centric Video Transmission in Next Generation Mobile Networks 26
  • Institute for Media Technology Prof. Dr.-Ing. Eckehard Steinbach Technische Universität München Outline  Motivation and overview  QoE-driven adaptive HTTP video delivery  QoE-driven resource allocation for LTE uplink  Conclusions February 12, 2014 A. El Essaili: Towards User-centric Video Transmission in Next Generation Mobile Networks 27
  • Institute for Media Technology Prof. Dr.-Ing. Eckehard Steinbach Technische Universität München Conclusions QoE-driven adaptive HTTP video delivery  Exploit the benefits of QoE-driven traffic management: □ Propose a proactive approach for rewriting the client requests. □ Requires no adaptation of the media content, suitable for OTT services. □ Main results: improved QoE, fairness, and network awareness.  Playout buffer-aware traffic and resource management. QoE-driven resource allocation for LTE uplink  Service-centric approach for uplink resource allocation: □ Higher QoE compared to standard scheduling mechanisms in LTE. □ Improved video quality and efficient usage of the network resources by considering the consumers' consumption patterns. February 12, 2014 A. El Essaili: Towards User-centric Video Transmission in Next Generation Mobile Networks 28
  • Institute for Media Technology Prof. Dr.-Ing. Eckehard Steinbach Technische Universität München Acknowledgments  Prof. Eckehard Steinbach (Institute for Media Technology, TUM)  Damien Schroeder (Institute for Media Technology, TUM)  Prof. Wolfgang Kellerer (Institute for Communication Networks, TUM)  Dr. Dirk Staehle (DoCoMo Euro-Labs)  Dr. Liang Zhou (Nanjing University of Posts and Telecommunications) February 12, 2014 A. El Essaili: Towards User-centric Video Transmission in Next Generation Mobile Networks 29