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SWiM 20031 QoS Lessons from Multimedia David Maier OGI School of Science & Engineering Oregon Health & Science University
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SWiM 20032 Multimedia QoS Work with Richard Staehli and Jonathan Walpole Lessons If you are going to degrade, do so in preferred and thrifty manner: Least reduction in perceived quality for maximum reduction in resource usage Error is multifaceted: Different kinds of error more or less objectionable for different tasks, e.g., lower resolution vs. lower frame rate Software adaptivity is possible, but tricky to tune.
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SWiM 20033 Our Model ContentViewPresentation Error = Ideal vs. Actual
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SWiM 20034 Might Apply to Stream Queries ContentViewPresentation Error = Ideal vs. Actual Input Stream Query Output Stream
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SWiM 20035 More Than One Way to Explain Error Amplitude Shift Lag Drift Quantization
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SWiM 20036 Error Model Error model consists of one or more error components (e.g., amplitude, shift) An error component can be scaled by a coefficient (e.g., amount of shift) Error interpretation: expressing error between ideal and actual using error components E total = c 1 ·E 1 + c 2 ·E 2 + … + c n ·E n
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SWiM 20037 Can Have More Than One Interpretation of an Error Amplitude Lag Amplitude Lag
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SWiM 20038 Uses of Error Model Define combined quality bound 0.8*c amp + 0.2*c lag min over all interpretations Define limits on individual components State user preferences: degrade resolution before introducing lag Pre-compute effect of different load shedding options on error
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