UbiComp 2013 presentation by David T. Nguyen College of William and Mary, USA

1. Evaluating Impact of Storage
on Smartphone Energy Efficiency
DavidT. Nguyen

2. LIFE IN MOBILE ERA..
1,038,000,000 SMARTPHONE USERS WORLDWIDE [IBTIMES]
27% INCREASED # SMARTPHONES SOLD ANNUALLY [IDC]
Figure Courtesy: http://www.ideas4ios.com
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3. SMARTPHONE APPS DO EVERYTHING!
850,000 APPS IN APPLE STORE 05/13 [APPLE]
800,000 APPS IN GOOGLE PLAY 05/13 [CANALYS]
145,000 APPS IN WINDOWS STORE 05/13 [CANALYS]
120,000 APPS IN BLACKBERRY WORLD 05/13 [CANALYS]
Figure Courtesy:
http://aptito.com
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4. Still BIG Problem
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Figure Courtesy: http://cdn.cultofmac.com

5. Smartphone Dislikes
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0% 10% 20% 30% 40%
Call Quality
Contact List Import
Excessive Dropped Calls
3G Quality
Screen Size
4G Capability
Battery Life
Source: ChangeWave

6. Outline
Introduction
Background
Experimental Study
Pilot Solution
Evaluation
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7. Introduction
 Researching energy consumption essential
 What has been done
◦ Performance bottleneck in storage
[Kim et al., FAST ‘12]
◦ No direct study of storage – energy
consumption correlation
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8. Introduction
 Thesis Statement
◦ Investigate impact of storage on smartphone
energy efficiency
◦ Explain root reasons of such impact
◦ Develop storage-aware energy saving solutions
 Expected Contributions
◦ Better understanding of storage subsystem and
its impact on energy efficiency
◦ Storage-aware energy saving solutions
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9. Outline
Introduction
Background
Experimental Study
Pilot Solution
Evaluation
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10. I/O Path
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Red: Nexus One default static configurations

11. Outline
Introduction
Background
Experimental Study
Pilot Solution
Evaluation
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12. Approach
 Investigate impact of different storage
configurations on power levels
1. Run series of benchmarks under default
configurations
2. Repeat benchmarks under different
configurations
3. Compare energy consumptions
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13. Setup
 Rooted smartphone Nexus One
 8 benchmarks
 Monsoon Power Monitor
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14. Power Consumption: Default Config.
(Queue Depth 128 / Write-back cache)
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 Different algorithms - different power levels
 No algorithm optimal for all benchmarks
 Changing algorithms may save energy

15. Power Consumption:
Queue Depth 4
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 Shorter queue depth saves energy in most cases
 Not storage intensive benchmarks consume more
power due to overhead of smaller queue

16. Optimal Configurations
 Run benchmarks with all combinations of
scheduling algorithms and queue
depths
 Record in benchmark table
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17. Outline
Introduction
Background
Experimental Study
Pilot Solution
Evaluation
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18. Big Idea
Track phone’s
run-time I/O
pattern
Match phone’s
pattern with
pattern from
benchmark table
Dynamically
configure
parameters with
optimal savings
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19. SmartStorage Architecture
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20. GUI
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21. I/O Pattern Matching
 Compare phone’s I/O pattern with patterns from
benchmark table
 Matching feature:
#𝑟𝑒𝑎𝑑𝑠 𝑐𝑜𝑚𝑝𝑙𝑒𝑡𝑒𝑑 /𝑠𝑒𝑐𝑜𝑛𝑑
#𝑤𝑟𝑖𝑡𝑒𝑠 𝑐𝑜𝑚𝑝𝑙𝑒𝑡𝑒𝑑 /𝑠𝑒𝑐𝑜𝑛𝑑
 If phone’s rate of reads/writes per second close
to a benchmark from table
◦ match is found
 Else
◦ no match
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22. Outline
Introduction
Background
Experimental Study
Pilot Solution
Evaluation
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23. Energy Savings: Nexus One
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24. Remaining Steps
 Energy savings with different
caching policies / file systems / queue depths
 Matching using machine learning
 Adaptive I/O pattern recalculation
 Root reasons of energy savings
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25. THANKYOU!
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