Reducing the Energy Usage of Office Applications Jason Flinn M. Satyanarayanan Carnegie Mellon University Eyal de Lara Dan S. Wallach Willy Zwaenepoel Rice University

2 Motivation Energy is a vital resource in mobile computing Previous work shows value of energy-aware adaptation  Reduce fidelity  Requires modification to application source code Can this work without source code? Middleware-based proxy can help!

3 Validation Common office applications can be made energy-aware  Puppeteer uses well-defined data format and API  Modified PowerPoint to reduce energy usage Preview of results:  Energy reductions up to 49% for some activities  Proxy approach modifies PowerPoint behavior  Other opportunities for increased energy-efficiency

4 Outline  Motivation  Background: Puppeteer  Energy benefits of adaptation  Other opportunities for extending battery lifetime  Future work and conclusions

5 Component-Based Adaptation Documents often stored on a central file server Must download and edit on a mobile client Can save time and energy by editing a low-fidelity version ServerClient skeleton high-fidelity component reintegrated on save reintegrated on save missing component

6 Server Puppeteer Data Server Client PowerPoint Documents Client Proxy Server Proxy Transcoded Documents Server proxy parses and transcodes documents Client proxy uses external API to interact with PowerPoint How much energy can component-based adaptation save? Uses well-defined data formats, exported APIs

7 Measuring Application Energy Usage Digital multimeter samples laptop power use Applications mark start and end of events Energy usage is integral of power over time Event Start Event End

8 Benchmark Presentations Benchmark consists of 10 PowerPoint presentations Size and effect of distillation vary

9 Experiment: Loading Documents Client: IBM 560X laptop with 2 Mb/s wireless network Server: Wall-powered desktop Client runs NT, PowerPoint, Puppeteer client proxy Server runs NT, Apache, Puppeteer server proxy Measure energy used to load documents:  From Apache (native mode)  Using Puppeteer (distilling out multimedia data)

10 Energy Benefit for Loading Documents Average energy usage reduced 40%! Oops! With simple filter, energy usage reduced 49%!

11 Experiment: Editing Documents Load documents on the client Measure energy needed to page through document for:  Full-quality version  Distilled version

12 Energy Benefit for Editing Documents Distillation reduces paging energy 13% Benefit less on subsequent traversals of document

13 Reducing Computational Fidelity How much energy is used by background activities? Not a lot to be gained by disabling most activities... But, the Office Assistant is quite expensive!

14 Experiment: Autosave Frequency Documents are saved on the client  Autosaves over network prohibitively expensive!  Reducing frequency saves energy  But, greater possibility of losing data! Measure additonal power savings for autosave frequency:  One minute (very expensive)  Five minutes (less expensive)  No autosave (optimal savings)

15 Effect of Autosave Frequency Average energy reduction of 11%

16 Outline  Motivation  Puppeteer: component-based adaptation  Energy benefits of adaptation  Other opportunities for extending battery lifetime  Future work and conclusions

17 Comparing Puppeteer and Native Mode Mystery: Why does Puppeteer take less time and energy to load a presentation than native mode?

18 Effect of Network Power Management Hypothesis: power management slows down transfer  Network receiver disabled for 100 ms. periods  Wireless bandwidth 2 Mb/s  In effect, a high bandwidth*delay product (25 KB)  Socket buffer and receive window only 8 KB  Native mode uses only 1 connection  Puppeteer uses up to 4 connections Verified this hypothesis by measuring:  With 64KB buffer sizes  Without network power management

19 Network Power Management Results With 64 KB buffers, native mode uses 26% less energy Disabling power management saves additional 18%

20 Disk Power Management Autosave Disk spinning = Wasted Energy Disk power management predicts periods of inactivity After autosave, waits for additional activity Disk in high-power state for 30 seconds

21 Transparent Power Management Applications and power mgmt. layer don’t communicate  Power management balances performance & energy  Tries to minimize impact on applications  Difficult without knowledge of application activity Transparent power management can help!  Applications provide hints about their activities  OS combines hints from all applications  OS chooses the optimal power mgmt. settings Applications Transparent Power Management Layer CPU Disk Network Power Mgmt. Settings Hints

22 PowerPoint and Power Management Puppeteer could provide PM hints for PowerPoint 1.Signals start and end of large transfers  Power management disabled during transfers  Uses 18% less energy, 22% less time 2.Signals when regular autosave is occurring  Can spin-down disk immediately after autosave  Uses 4% less energy

23 Outline  Motivation  Puppeteer: component-based adaptation  Energy benefits of adaptation  Other opportunities for extending battery lifetime  Future work and conclusions

24 Future Work System support for energy-aware applications  Currently open-source implementation (Linux)  Monitors supply and demand, adjusts fidelity  Port to closed-source environment (Windows) Transparent power management  Create API for expressing application hints  Develop algorithms that combine hints  Investigate other hardware devices (CPU)

25 Conclusions No one magic bullet for reducing PowerPoint energy use But, many opportunities for significant energy reduction  Reducing data fidelity  Reducing computational fidelity  Transparent power management Puppeteer provides a mechanism for achieving reductions  Proxy approach requires no source-code modification  Takes advantage of exported APIs Other potential domains for this work:  Other Microsoft Office applications  Web browsers