QoE based Traffic Management for Multimedia Traffic in Mobile Networks
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1 QoE based Traffic Management for Multimedia Traffic in Mobile Networks Dirk Staehle, DOCOMO Euro Labs euro.com Copyright 2012 DOCOMO Communications Laboratories Europe GmbH Dirk Staehle, Service Research Group
2 Outline Motivation DOCOMO s QoE framework DASH: Dynamic Adaptive Streaming for HTTP DOCOMO s QoE framework and DASH concept results Conclusion Copyright 2012 DOCOMO Communications Laboratories Europe GmbH Dirk Staehle, Service Research Group 2
3 3GPP Standardization: UPCON UPCON: User Plane Congestion Control 3GPP SA1 study item Scope (3GPP TR ) scenarios and use cases where high usage levels lead to user plane traffic congestion in the RAN make efficient use of available resources to increase the potential number of active users while maintaining the user experience handling of user plane traffic when RAN congestion occurs based on: the subscription of the user the type of application the type of content Focus of QoE-based traffic management Copyright 2012 DOCOMO Communications Laboratories Europe GmbH Dirk Staehle, Service Research Group 3
4 Trends in Mobile Data Traffic Traffic total amount of traffic heavily increasing web, data, video key traffic classes video dominating Devices increasing diversity smartphones and notebook dominating Smart over the top applications application adapt to performance provided by the network Skype, DASH Copyright 2012 DOCOMO Communications Laboratories Europe GmbH Dirk Staehle, Service Research Group 4
5 Challenge Manage mobile web, data, ADAPTIVE and NON ADAPTIVE VIDEO traffic Traditional traffic management differentiate traffic types: web, data, video 20% interactive web > high priority 10% data e.g. software updates > low priority 70% video traffic > no differentiation, one class QoE based traffic management for multimedia traffic additionally differentiate based on video and device characteristics optimize overall QoE for limited radio resources Copyright 2012 DOCOMO Communications Laboratories Europe GmbH Dirk Staehle, Service Research Group 5
6 Example Videos Low Data Rate High Data Rate Copyright 2012 DOCOMO Communications Laboratories Europe GmbH Dirk Staehle, Service Research Group
7 Application Sensitivity (QoE) Curves Low Data Rate Copyright 2012 DOCOMO Communications Laboratories Europe GmbH Medium Data Rate Dirk Staehle, Service Research Group Reference: Journal of Communications, 2009
8 QoE Based Traffic Management: Concept Traffic Management Module (Optimization): decides on network resource allocation to provide best trade-off user satisfaction vs network cost Input: network status, application sensitivity w.r.t. user satisfaction Output: network resource allocation, feedback to application Information gathering Application modeling Network monitoring Core Network RAN signaling Content sources Traffic management (optimizer module) Mobile users Traffic engineering (adaptation, traffic shaper/ resource allocation, transcoding, layer dropping) Traffic Engineering Module (enforcement function): adapt data stream to rate determined by optimizer to avoid uncontrolled QoE degradation (stalling, artifacts) due to packet loss or delays at enb Copyright 2012 DOCOMO Communications Laboratories Europe GmbH Dirk Staehle, Service Research Group 8
9 QoE Based Traffic Management: Architecture Network/RAN Monitoring (e.g. NW topology, device/link s status) traffic management (optimizer) Application sensitivity Customer satisfaction Data rate (kbps) Signaling Data stream Mobile users 3. Application sensitivity + Network/RAN knowledge 4. Optimal rate adaptation (e.g. 300Kbps instead of 500Kbps) Content sources 1. Data stream + Application sensitivity 500 Kbps xgsn SGSN / EPC SGW CN 2. Wireless resources /capacity 300 Kbps 7. Forward adapted data stream RAN RNC/ enodeb GGSN PGW 8. Support rates for traffic subject to QoE Management 5. Forward data stream to traffic engineering module + signaling of optimal rate adaptation 500 Kbps 300 Kbps 6. Return a modified data stream Traffic engineering (adaptation, traffic shaper/ resource allocation) Copyright 2012 DOCOMO Communications Laboratories Europe GmbH Dirk Staehle, Service Research Group
10 QoE Based Traffic Management and Adaptive HTTP Streaming How does end-to-end adaptive streaming solutions work together with network-centric QoE-based traffic optimization framework? Does end-to-end adaptation for Over-the-top (OTT) streaming services solve all congestion problems? Results from cooperation with Prof. Steinbach, Lehrstuhl f. Medientechnik, TUM Thanks to Ali El-Essaili and Damien Schröder for result figures Copyright 2012 DOCOMO Communications Laboratories Europe GmbH Dirk Staehle, Service Research Group
11 Adaptive HTTP Streaming Pull based HTTP streaming technology, client adapts multimedia quality to the rate experienced from the network Different proprietary solutions Microsoft s Smooth Streaming, Apple s HTTP Live Streaming, Adobe HTTP Dynamic Flash Streaming, Standardized by MPEG and 3gpp: MPEG DASH, 3GP DASH Support by Microsoft, Adobe, Available clients: Microsoft Silverlight, VLC DASH client, Copyright 2012 DOCOMO Communications Laboratories Europe GmbH Dirk Staehle, Service Research Group 11
12 Non Adaptive HTTP Streaming Progressive Download, Non adaptive HTTP Streaming Client http request (video URL) http response (video file) Video File Video plays while downloading Server Copyright 2012 DOCOMO Communications Laboratories Europe GmbH Dirk Staehle, Service Research Group 12
13 Dynamic Adaptive Streaming for HTTP Dynamic Adaptive Streaming over HTTP (DASH) Client MPD (Multimedia Presentation Description) defines in what format and where the video is stored URLs of video segments of different quality Seconds 4-6 in request for MPDlow quality MPD MPD First 2s in high quality request for segment 1, representation x segment k, representation y request for segment k, representation y segment k, representation y Video File Server while playing client determines best representation based on available rate and playout buffer video segments in multiple representations (formats of different quality and size) Copyright 2012 DOCOMO Communications Laboratories Europe GmbH Dirk Staehle, Service Research Group 13
14 DASH and QoE Based Traffic Management Features of QoE Optimization Framework traffic management (optimizer): determine optimal video quality and data rates taking into account video characteristics (QoE curve) and long term radio channel quality traffic engineering (enforcement function): adapt video to rate determined by optimizer to avoid uncontrolled QoE degradation (stalling, artifacts) due to packet loss or delays at enb Features of DASH adapt video to available bandwidth to avoid uncontrolled QoE degradation (stalling) DASH offers lightweight traffic engineering (enforcement) functionality reactive approach proactive approach Copyright 2012 DOCOMO Communications Laboratories Europe GmbH Dirk Staehle, Service Research Group 14
15 Reactive Approach Long term channel quality Optimizer TM Video Information (QoE value per representation) MPD, Segment Requests Video Rate DASH Client DASH Proxy HTTP Requests UE Standard DASH client adapts requests for rate set by rate shaper enb TE Rate Shaper P-GW Rate Shaper limits data rate of HTTP download to target rate set by optimizer HTTP Response (Video Segments) HTTP or Streaming Server Copyright 2012 DOCOMO Communications Laboratories Europe GmbH Dirk Staehle, Service Research Group
16 Proactive Approach Long term channel quality Optimizer TM Video Information (QoE value per representation) MPD, Segment Requests Representation Video Rate DASH Client UE Standard DASH client adapts requests for rate set by rate shaper enb DASH Proxy TE DASH proxy modifies URL of requested segment to URL of optimal representation Rate Shaper P-GW HTTP Requests HTTP Response (Video Segments) Rate Shaper limits data rate of HTTP download to target rate set by optimizer HTTP or Streaming Server Copyright 2012 DOCOMO Communications Laboratories Europe GmbH Dirk Staehle, Service Research Group
17 Evaluation Framework Microsoft Silverlight, VLC DASH Squid Proxy Dummynet Apache DASH Client Proxy HTTP Requests Live UE Rate Shaper HTTP Response (MPD, Video Segments) HTTP or Streaming Server Offline representation per segment data rate per 2ms interval Channel Traces Scheduler / Optimizer Simulation QoE Curves Copyright 2012 DOCOMO Communications Laboratories Europe GmbH Dirk Staehle, Service Research Group
18 Scenario 8 different videos 50 replications with different channel traces Evaluation of video specific MOS (averaged over segments) mean MOS (averaged over segments and videos) Comparison of pure DASH (Non Opt) reactive approach, only rate shaper (QoE reactive) proactive approach rate shaper + proxy, opt. on continuous QoE curves (QoE Proxy) rate shaper + proxy, opt. on discrete QoE points sets (QoE Proxy d) server based approach, optimal encoding at server (QoE Server) Copyright 2012 DOCOMO Communications Laboratories Europe GmbH Dirk Staehle, Service Research Group 18
19 Mean MOS Potential Gain of 0.5 in Mean MOS by QoE framework Gain of 0.25 in Mean MOS by proactive approach Copyright 2012 DOCOMO Communications Laboratories Europe GmbH Dirk Staehle, Service Research Group
20 Individual MOS Almost equal Mean MOS for non-demanding videos Clear Mean MOS improvement for demanding videos Copyright 2012 DOCOMO Communications Laboratories Europe GmbH Dirk Staehle, Service Research Group
21 Subjective Tests Copyright 2012 DOCOMO Communications Laboratories Europe GmbH Dirk Staehle, Service Research Group 21
22 Overall results Mean MOS improves MOS range gets smaller ( fairer ) Proactive Reactive DASH Proactive Reactive DASH 30 km/h 120 km/h Copyright 2012 DOCOMO Communications Laboratories Europe GmbH Dirk Staehle, Service Research Group
23 Conclusion Trends in mobile multimedia communication video is/becomes dominating traffic type smart applications like adaptive HTTP streaming QoE based traffic management framework differentiates multimedia content based on its inherent characteristics efficiently utilizes radio resources for an overall optimal QoE flexible to integrate new streaming technologies End to end adaptive streaming (DASH) is a big step for high quality mobile multimedia delivery but rate allocation depends on enb scheduler such that QoE based traffic management achieves significant gain, in particular for demanding videos Copyright 2012 DOCOMO Communications Laboratories Europe GmbH Dirk Staehle, Service Research Group 23
24 Dr. Dirk Staehle euro.com DOCOMO Communications Laboratories Europe GmbH Landsberger Strasse Munich, Germany Phone: +49 (89) euro.com Copyright 2012 DOCOMO Communications Laboratories Europe GmbH Dirk Staehle, Service Research Group
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