The document discusses various techniques for optimizing battery usage in Android apps. It describes how different app activities consume battery, such as video streaming, web browsing, and data transfers. It then provides recommendations for improving battery life, including bundling network requests, prefetching data, caching data locally, compressing data, and minimizing the use of wakelocks and GPS. The document emphasizes the importance of monitoring an app's battery usage and making adjustments to reduce consumption.

1. Battery Optimization for
Android Apps
Murat AYDIN
STM
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2. About Me
• Android Developer and blogger in his free time
• Senior Software Developer at work
• GDG Ankara member
www.androiddeveloperdays.com
• Author
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3. Why Battery is Important?
• Limited and main resource for device to function
• Device may be needed for an important task when the
battery is running out of power
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4. Why Battery is Important?
• Part of user experience
• Bad user reviews and ratings
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5. What to do?
• Buy extended batteries
• Buy case batteries
• Carry external batteries
Trontium-reactor can charge phones 50 times-299$
• Carry solar charges
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6. What consumes the most?
Derived from Jeff Sharkey’s presentation
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7. Usage Measurements
For a 1150mAh battery:
• Watching YouTube videos: 340mA 1150/340=3.4 hours
• Browsing 3G web: 225mA 1150/225=5 hours
• Typical usage,10 minute for every hour:42mA=32 hours
• EDGE completely idle: 5mA=9.5 days
• Airplane mode idle:2mA=24 days
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8. Bulk Data Transfer
Bulk data transfer for a 6MB song:
• EDGE (90kbps):300mA*9.1 min = 45 mAh
• 3G (300kbps):210mA*2.7 min = 9.5 mAh
• WiFi (1Mbps):330mA*48 sec = 4.4 mAh
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9. • Research by Purdue University into energy consumption
by apps (March 2012)
“Free apps like Free Chess and Angry Birds spend under
25-35 percent of their energy on game play, but over 65-75
percent on user tracking, uploading user information and
downloading ads.”
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10. Radio State Machine
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11. Bundled vs Unbundled Transfers
• Suppose 3 data transfer
each 3s in every 20s
• Unbundled 1 data
transfer =
3s+5s+12s=20s
• 20s x 3 totally 60s
• Bundled 9s+5s+12s =
totally 26s
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12. Prefetch Data
• Reduce download times
• Minimize in-app latency
• Dont use it aggressively
• Prefetch data such that you will only need to initiate
another download every 2 to 5 minutes, and in the order
of 1 to 5 megabytes
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13. Batch Data
• Create a pending transfer queue
• Transfer from the queue when there is scheduled
updates
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14. Use Traffic Stats API
TrafficStats.setThreadStatsTag(0xF00D);
try {
// Make network request using HttpClient.execute()
} finally {
TrafficStats.clearThreadStatsTag();
}
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15. Polling?
• Use GCM instead of polling
• Use Inexact Repeating Alarms for pollings
• Dont use _WAKEUP versions of alarm types
• Implement exponential back-off pattern for pollings
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16. Cache Data
• Cache as much as possible
• Be careful about displaying stale data
Monitor Connectivity
• Avoid connection attempts if there is no network
• Modify download pattern based on the connectivity type
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17. Compress Data
• Compress data before transferring
• Especially textual data
import java.util.zip.GZIPInputStream;
HttpGet request = new HttpGet(“http://url”);
HttpResponse resp = new DefaultHttpClient().execute(request);
HttpEntity entity = response.getEntity();
InputStream compressed = entity.getContent();
InputStream rawData = new GZIPInputStream(compressed);
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18. Compress Data
Derived from Jeff Sharkey’s presentation
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19. Battery Monitoring
• Monitor changes in charging state
• Monitor Significant Changes in Battery Level
• Maximize update rate when device is charging, minimize
when discharging
• Decrease update frequency when the battery is low
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20. Wakelock
• Q: What is wakelock?
• A: A wake lock is a mechanism to indicate that your
application needs to have the device stay on
• Device battery life will be significantly affected by the
use of this API. Do not
acquire PowerManager.WakeLocks unless you really
need them, use the minimum levels possible, and be
sure to release them as soon as possible.
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21. Wakelock
• Use keepScreenOn instead of wakelock
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22. Derived from Jeff Sharkey’s presentation
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23. GPS
• Use coarse network location if possible
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24. Trepn Profiler
• Real-time overlay-mode allows developers to see the
impact of their actions on performance
• Helps developers optimize code for CPU, power usage
and network usage
• Profiles the entire system or a single app
• Displays accurate battery power readings with charts
• Supports offline analysis of data
• Can be started or stopped from a script for Automated
tests
• Eclipse plug-in
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25. Demo
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26. As a Result
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27. Questions?
• Twitter: @maydintr
• Email: maydin@gmail.com
• Web: www.ottodroid.net
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