~/talk

eDoctor: Automatically Diagnosing Abnormal Battery Drain Issues on Smartphones

Talkat NSDI 2013 · 2013-04-02..04-05
name:Xiao Ma
links:none on file
links:none on file
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name:Pei Wang
github:uraj
links:none on file
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slides:none on file

eDoctor automatically detects and diagnoses abnormal battery drain by segmenting app runs into execution phases using resource-usage vectors and k-means on RUVs, correlating new energy-heavy phases with recent installs/config changes. It includes an on-phone diagnostic engine and an app reverter to roll back updates. Evaluation with 31 users, 17 real issues plus 4 injected across 19 apps yields 47 of 50 cases correctly diagnosed and under 1.5% power overhead.

AI-written summary · about

  1. 0:00Intro
  2. 2:22NORMAL VS. ABNORMAL
  3. 3:43APPLICATION DEFECT
  4. 4:42OUTLINE
  5. 8:04IDEAL SOLUTION
  6. 8:35PHASE BEHAVIORS
  7. 11:17TRIGGER EVENTS
  8. 12:25COLLECTOR
  9. 14:21DATA ANALYZER
  10. 14:47PHASE ANALYSIS
  11. 15:20DIAGNOSIS ENGINE
  12. 15:54REPAIR ADVISOR
  13. 17:18DIAGNOSIS ACCURACY
  14. 19:38ENERGY OVERHEAD
  15. 20:21CONCLUSION
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