Optimizing User QoE through Overlay Routing, Bandwidth Management and Dynamic Transcoding
Optimizing User QoE through Overlay Routing, Bandwidth Management and
Dynamic Transcoding
Maarten Wijnants, Wim LamotteHasselt University - Expertise Centre for Digital Media
Bart De Vleeschauwer, Filip De Turck, Bart Dhoedt, Piet Demeester
Ghent University – IBCN - Department of Information Technology
Peter Lambert, Dieter Van de Walle, Jan De Cock, Stijn Notebaert, Rik Van de Walle
Ghent University – MMLab - Department of Electronics and Information Systems
Optimizing User QoE through Overlay Routing, Bandwidth Management and
Dynamic Transcoding
Optimizing User QoE through Overlay Routing, Bandwidth Management and Dynamic Transcoding
Outline
• Introduction and Motivation• End-to-End QoE Optimization Architecture
– Overlay Routing Components– Network Intelligence Proxy
• H.264/AVC Video Transcoding• Evaluation
– Experimental Setup– Experimental Results– Discussion
• Conclusions
23/06/2008 ADAMUS2008 2
Optimizing User QoE through Overlay Routing, Bandwidth Management and Dynamic Transcoding
Introduction and Motivation
• Rising networked access of MM services– Strict requirements on transportation network
• Service consumption environment has become highly heterogeneous– Growing service dependability & adaptation
requirements
• Current-gen networks often not capable of guaranteeing requirements are satisfied– Internet routing service is best-effort– Constrained access network connections
• Insufficient last mile bandwidth Congestion
23/06/2008 ADAMUS2008 3
Optimizing User QoE through Overlay Routing, Bandwidth Management and Dynamic Transcoding
Introduction and Motivation
• Current networks often unable to provide MM users an acceptable usage experience– More formally: Quality of Experience (QoE)
• Network architecture supporting full end-to-end QoE optimization needed– Proposed by us in previous work
• We extended network architecture with a H.264/AVC video transcoding service– Dynamic rate adaptation of H.264/AVC video– Enables further optimization of user QoE
23/06/2008 ADAMUS2008 4
Optimizing User QoE through Overlay Routing, Bandwidth Management and Dynamic Transcoding
End-to-End QoE Optimization Architecture
• Proposed architecture employs 2-tier approach to achieve E2E QoE optimization– Enhance data dissemination in network core
• Through provision resilient overlay routing service
– Last mile user QoE optimization• Network traffic shaping• Multimedia service provision
• Consists of 3 types of components– Overlay Server– Overlay Access Component– Network Intelligence Proxy
23/06/2008 ADAMUS2008 5
Resilient overlayrouting
Last mile QoEoptimization
Optimizing User QoE through Overlay Routing, Bandwidth Management and Dynamic Transcoding
End-to-End QoE Optimization Architecture
• Overlay Server (OS)– Deployed in network core– Maintain an overlay topology
• Perform active monitoring to obtain connectivity info• Info is used to construct overlay routing tables
• Overlay Access Component (AC)– Located near end-users– Decide when to forward traffic to overlay servers
(based on quality direct IP connection)
• OSs exploit overlay routing tables to transport traffic to AC close to target node
23/06/2008 ADAMUS2008 6
Optimizing User QoE through Overlay Routing, Bandwidth Management and Dynamic Transcoding
End-to-End QoE Optimization Architecture
• Network Intelligence Proxy (NIProxy)– Deployed close to end-user– Improve user QoE by intelligently managing last
mile content delivery to clients– Context introduction in transportation network
• Network awareness: Access channel conditions• Application awareness: E.g. stream significance
– Last mile network traffic shaping: Orchestrate last mile BW consumption of applications
• Prevent over-encumbrance of client's access link• Intelligently allocate available client downstream BW
(based on application awareness)
23/06/2008 ADAMUS2008 7
Optimizing User QoE through Overlay Routing, Bandwidth Management and Dynamic Transcoding
End-to-End QoE Optimization Architecture
• Network Intelligence Proxy– Network traffic shaping operates by organizing
network flows in a stream hierarchy• Internal nodes: Implement BW distribution technique
– E.g. WeightStream • Leaf nodes: Correspond to actual network flows
– Discrete: Toggle between discrete # of BW values– Continuous: Any rate in [0, max flow BW usage]
– Multimedia service provision• Perform computation/processing on network flows• Services can query and exploit NIProxy’s awareness• Implementation: Plug-in approach (dynamic loading)
23/06/2008 ADAMUS2008 8
Optimizing User QoE through Overlay Routing, Bandwidth Management and Dynamic Transcoding
End-to-End QoE Optimization Architecture
23/06/2008 ADAMUS2008 9
Overlaylayer
Networklayer
Last mile QoE optimization
Resilient networkcore routing
Optimizing User QoE through Overlay Routing, Bandwidth Management and Dynamic Transcoding
H.264/AVC Video Transcoding
• Focus on bit rate reduction• Operates entirely in compressed domain
– Only entropy decoding and encoding required– # transformed coefficients are set to 0 based on
dynamically changing cut-off frequency– Transcoder steered by rate control alg
• Ensures desired bit rate is achieved (Track buffer occupancy Estimate bit budget current frame Dynamically adjust cut-off frequency)
• Integrated as plug-in for NIProxy– Dynamically set desired bit rate H.264 flows
• Enables H.264 flow mgmnt using continuous leaves
23/06/2008 ADAMUS2008 10
Optimizing User QoE through Overlay Routing, Bandwidth Management and Dynamic Transcoding
EvaluationExperimental Setup
• Experimental results produced on testbed– 10 Linux PCs: 3 OSs, 2 ACs, 2 NIProxies, 2 MM
clients, video server, 2 Click impairment nodes– Click nodes emulate varying network condition
• Introduce random packet loss in core network• Enforce BW restriction on last mile
– Communication session server to each client
23/06/2008 ADAMUS2008 11
Optimizing User QoE through Overlay Routing, Bandwidth Management and Dynamic Transcoding
EvaluationExperimental Results
• Experiment– 2 H.264/AVC flows
streamed to each client– Consisted of 5 intervals– Bit rates continuous
leaf nodes enforced by H.264/AVC transcoder
23/06/2008 ADAMUS2008 12
Continuousleaf nodes
Interval 1: Only 1 H.264/AVC flow; sufficient BW available to forward flow at maximal quality
Interval 2: Introduction V2; V1 and V2 had identical weight and comparable max bit rate received comparable BW budget
Interval 3 + 4: Significance V1 increased V1 is allocated more BW V2 transcoded to lower bit rate
Interval 5: Additional last mile BW available; used to upgrade quality V2 (V1 already at maximal quality)
Optimizing User QoE through Overlay Routing, Bandwidth Management and Dynamic Transcoding
EvaluationDiscussion
• Findings– Client’s last mile downstream capacity respected
Last mile congestion avoided• Outcome = Optimal flow reception at client-side
– BW distribution captured stream importance• Due to NIProxy’s application awareness
– H.264/AVC transcoding service enabled continuous video adaptation
• Optimal and full exploitation available last mile BW
• Did not apply for the “unprotected” client!– Degraded video playback at client-side– Clear difference in QoE provided to both clients!
23/06/2008 ADAMUS2008 13
Optimizing User QoE through Overlay Routing, Bandwidth Management and Dynamic Transcoding
Conclusions
• E2E QoE optimization platform– Resilient overlay routing service circumvents
erratic parts of network core– Last mile QoE optimization through bandwidth
management and multimedia service provision
• Extended with H.264/AVC transcoding– Enables continuous video adaptation
• Experimental results demonstrate positive impact on QoE optimization capabilities– Full exploitation available last mile BW– More dynamic and effective BW distributions
23/06/2008 ADAMUS2008 14
Optimizing User QoE through Overlay Routing, Bandwidth Management and Dynamic Transcoding
Thank you for your attention!Any questions?
Top Related