Router Virtualization as an Enabler for Future Internet Multimedia … · 2010-11-24 · Streaming...
Transcript of Router Virtualization as an Enabler for Future Internet Multimedia … · 2010-11-24 · Streaming...
KOM - Multimedia Communications Lab
Prof. Dr.-Ing. Ralf Steinmetz (Director)
Dept. of Electrical Engineering and Information Technology
Dept. of Computer Science (adjunct Professor)
TUD – Technische Universität Darmstadt
Rundeturmstr. 10, D-64283 Darmstadt, Germany
Tel.+49 6151 166150, Fax. +49 6151 166152
www.KOM.tu-darmstadt.de
© 2010 author(s) of these slides including research results from the KOM research network and TU Darmstadt. Otherwise it is specified at the respective slide
httc –
Hessian Telemedia Technology
Competence-Center e.V - www.httc.de
Osama Abboud, M.Sc
Prof. Dr.–Ing Ralf Steinmetz
Tel.+49 6151 16 4115
23. November 2010Future_Internet_Hannover___2010.11.22.ppt
Router Virtualization as an Enabler for
Future Internet Multimedia
Applications
KOM – Multimedia Communications Lab 2
Motivation
Evolution of the Internet
Multimedia apps getting more popular
Cisco VNI predicts in 2014: Video
will be 70% of all Internet traffic
More powerful devices with increasing
connection speeds
High definition and 3D content
More load on central instances
Routers, backbones, servers
Media-oriented networks will
become necessary
Source: Cisco Visual Networking Index Forecast 2010
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Outline
Motivation
Future Multimedia Systems
System Overview
Scalable Video Coding
Media-aware Networking
Router Virtualization
Data Prioritizing
Evaluation
Scenario
Results
Conclusion
KOM – Multimedia Communications Lab 4
Streaming System - Overview
Peer-assisted architecture
Hybrid server/P2P solution
Tracker with contact information of the peers
Video streaming
Uses the H.264 Scalable Video Coding (SVC)
Video divided into many parts (chunks)
Each chunk consists of multiple video blocks
More blocks are requested to get higher quality
Osama Abboud et al : Quality Adaptive Peer-to-Peer Streaming using Scalable Video CodingIn the Proceedings of the 12th IFIP/IEEE MMNS09 Conference
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Scalable Video Coding
Video file encoded only once but with different quality levels
Different quality can be requested independently
Scalability in 3 dimensions
Temporal: Frames per second
Spatial: Resolution of the picture
Quality: Quantization levels, sharpness
Enables quality adaptation
Received quality level adjustable according to
Device and connection properties (e.g. resources, screen size, bandwidth)
Network status (congestions, system capacity, availability of required quality blocks,…)
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Quality Adaptation
Osama Abboud et al : Quality Adaptive Peer-to-Peer Streaming using Scalable Video CodingIn the Proceedings of the 12th IFIP/IEEE MMNS09 Conference
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Why do we need Media Awareness?
Media-aware
Intelligence
Media-aware
Intelligence
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Outline
Motivation
Future Multimedia Systems
System Overview
Scalable Video Coding
Media-aware Networking
Router Virtualization
Data Prioritizing
Evaluation
Scenario
Results
Conclusion
KOM – Multimedia Communications Lab 9
Media-aware Multimedia Networks –
Router Virtualization
Media awareness can be introduced using router virtualization
Why router virtualization?
Quality of service at the application level (optimize (QoE) )
Efficient and custom-made QoS solutions (e.g. live and on-demand streaming)
Enables the gradual development of media aware solutions
Efficient architectures being developed: e.g. Using OpenFlow
Why not classical QoS management solutions, e.g. DiffServ?
QoS controlled by the network provider not the content provider
Heterogeneous QoS algorithms across networks make traffic handling complex
How?
During bottlenecks, the virtual router prioritizes and controls block transfers
Block priority calculated based on various important QoS/QoE metrics
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SVC Video Block Prioritization (1)
Temporal aspect reflecting the real time properties of streaming
How soon is the block needed?
Video block near the playback positions are more important
The least need block is the first to be slowed down upon congestions
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SVC Video Block Prioritization (2)
Quality aspect reflecting the interdependencies between the layers
How many block depend on a certain block?
E.g. Base layer: all blocks depend on it
The more a block is needed by lower layer, the more priority it gets
BaseTier (0)
Tier 2
Tier 2
Tier 3
Tier 3 Tie
r 3
Tier 1 Tier 2
Tier 1 Tier 1 Tier 2
Tier 3 Tier 3 Tier 3
Spat
ial R
eso
luti
on
(D
)
Temporal Resolution (T)
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Media Aware Networking - Virtual Router
Intelligence
The priority of a block calculated by the virtual router is
P = t * T + q * Q
t: weight of temporal aspect
q: weight for quality aspect
T: block temporal priority
Q: block quality priority
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Simulation Setup
Typical peer-assisted video-on-demand system
100 Peers with 8 seeders (2 per subnetwork)
SVC video with 8 layers
Scenario 1
10 minute bandwidth bottleneck of the virtual router (3000 kbps)
Router configuration
T100, T70/Q30, T50/Q50, T30/Q70, Q100
Compared to a media agnostic router (random packet drop)
Scenario 2:
10 minute bandwidth bottleneck of the virtual router (3000 & 4000 kbps)
Different quality adaptation intervals: 5, 10, 20, 30, 45 seconds
Router configuration
T100 compared to media agnostic router (random packet drop)
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Evaluation Metrics
Perceived Quality of Service
Session Quality
Startup time and number and duration of playback stalls
The shorter and fewer are the stalls, the better is the session quality
Video Quality
Number of quality changers
Constant received level Better user experience
Received quality level (compared to the maximal level)
Higher quality level Better user experience
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Simulation Results – Scenario 1
Session Quality
45% smoother playback during
bottelnecks
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Simulation Results – Scenario 1
Video Quality
20% less quality swtiches during
bottelnecks
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Simulation Results – Scenario 2
Session Quality Video Quality
More predictable impact of quality
adaptation
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Conclusion
Media-awareness achieves better perceived QoS without any
additional traffic costs
Evolution of internet applications
Media-aware networking will become a must to better handle the enormous
amount of video traffic.
Future Work
Integrate the algorithms into a real virtual router
Perform prototpye evaluation
Develop more sophisticated prioritization algorithms
Build more advanced control and management mechanisms
Security issues when reporting high priority for many blocks.
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Thank you for your attention