2011 islped: backlight scaling service
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TRANSCRIPT
International Symposium on Low Power Electronics and Design
Dynamic Backlight Scaling Optimization for Mobile Streaming Applications
Pi‐Cheng Hsui, Chun‐Han Lin, and Cheng‐Kang Hsieh
Research Center for Information Technology Innovation Academia Sinica, Taiwan
• Introduction• Dynamic Backlight Scaling Optimization
– An optimal algorithm– Demonstration
• Performance Evaluation– System deployment– Experimental results
• Conclusion
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Outline
• Introduction• Dynamic Backlight Scaling Optimization
– An optimal algorithm– Demonstration
• Performance Evaluation– System deployment– Experimental results
• Conclusion
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Outline
• Mobile applications and services are having a profound effect on people's lifestyles
• The energy consumption of mobile devices is a major challenge in sustaining the applications and services.
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Research Motivation
• Battery extenders
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Possible Solutions• Cloud‐based Energy‐Saving
Services
• With the service is applied, the service provider help reduce the energy consumption of mobile devices when they access Internet applications.
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What is the use?
What application to start? What hardware to target?
Cisco Forecast:Video streams will account for 66% of mobile data traffic by 2014
Power distribution on HTC Desire when browsing videos on YouTube
CPU, 16.87%
WIFI, 24.62%
Backlight, 34.12%
LCD Screen, 24.38%
• Introduction• Dynamic Backlight Scaling Optimization
– An optimal algorithm– Demonstration
• Performance Evaluation– System deployment– Experimental results
• Conclusion
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Outline
• Dynamic backlight scaling– Dynamically adjust backlight
levels for video frames
• A technical problem– Determine appropriate levels
for a video subject to scaling constraints• Video distortion• Hardware/software limitation• User perception• Etc.
• Contributions– Problem formulation– An optimal algorithm– System implementation
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Dynamic Backlight Scaling Optimization for Mobile Streaming Applications
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A Dynamic‐Programming AlgorithmImage frames in video
Video distortion
Backlight assignment
Hardware/software limitation
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Demonstration – HTC DesireApproach validation
Performance evaluation
• Introduction• Dynamic Backlight Scaling Optimization
– An optimal algorithm– Demonstration
• Performance Evaluation– System deployment– Experimental results
• Conclusion
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Outline
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System Deployment
Case studies
System architecture
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Experimental Results• Impact of video distortion on
energy savings• 18‐31% when the distortion
threshold is set at 0.9
• Impact of duration on energy savings
• 18‐31% when the duration threshold is set at 10
• Introduction• Dynamic Backlight Scaling Optimization
– An optimal algorithm– Demonstration
• Performance Evaluation– System deployment– Experimental results
• Conclusion
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Outline
• We raise the concept of cloud‐based energy‐saving services and have developed the dynamic backlight scaling service as an example service.– With the service is applied, an HTC Desire mobile phone can save 18‐
31% backlight energy when browsing videos on YouTube.
• We will release the mobile application program in the Android Market and seek feedback to identify more issues in this research direction.
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Conclusion
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We are the Research Center for IT Innovation