energy efﬁciency of handheld computer interfaces: limits, … · 2019-02-25 · driven mobile...

Energy Efficiency of Handheld Computer Interfaces:Limits, Characterization and Practice ∗

Lin Zhong and Niraj K. JhaDepartment of Electrical Engineering

Princeton UniversityPrinceton, NJ 08544

lzhong,[email protected]

AbstractEnergy efficiency has become a critical issue

for battery-driven computers. Significant work has beendevoted to improving it through better software andhardware. However, the human factors and user inter-faces have often been ignored. Realizing their extremeimportance, we devote this work to a comprehensivetreatment of their role in determining and improvingenergy efficiency. We analyze the minimal energy re-quirements and overheads imposed by known humansensory/speed limits. We then characterize energy ef-ficiency for state-of-the-art interfaces available on twocommercial handheld computers. Based on the charac-terization, we offer a comparative study for them.

Even with a perfect user interface, computers willstill spend most of their time and energy waiting foruser responses due to an increasingly large speed gapbetween users and computers in their interactions. Sucha speed gap leads to a bottleneck in system energy effi-ciency. We propose a low-power low-cost cache device,to which the host computer can outsource simple tasks,as an interface solution to overcome the bottleneck.We discuss the design and prototype implementationof a low-power wireless wrist-watch for use as a cachedevice for interfacing.

With this work, we wish to engender more interestin the mobile system design community in investigatingthe impact of user interfaces on system energy efficiencyand to harvest the opportunities thus exposed.

I. IntroductionEnergy consumption is a critical concern for battery-

driven mobile devices, such as handhelds, laptops, andcell-phones. Most handheld computers serve their usersdirectly through human-computer interaction, and mosttasks are interactive. From the user’s perspective, theconcern is not really the power consumption itself butwhat the user can do, given the battery lifetime. Energyefficiency is, therefore, better evaluated in terms ofenergy consumption per user task. At a higher level,one needs to evaluate:

∗Acknowledgments: This work was supported in part by NSFunder Grant No. CCF-0428446 and in part by a Princeton UniversityHonorific Fellowship.

User productivityAverage power consumption

or (User productivity) × (Power efficiency).From such a perspective, human factors and user

interfaces have a large impact on system energy ef-ficiency, simply because they determine not only thepower consumption for interaction but also user pro-ductivity. Most low-power research has focused onreducing power consumption, given a computation orinteractive task. However, it is equally, if not more,important to optimize the interaction itself, i.e., reducethe interaction power and improve user productivity.

In this paper, we focus on the impact of humanfactors and user interfaces on energy efficiency. Tothe best of our knowledge, this is the first work ofthis nature. We first present theoretical studies of theminimal energy/power requirements for user interfacesbased on human sensory limits, and then take intoaccount the human speed for human-computer inter-action. We then investigate the energy efficiency ofthe state-of-the-art interfaces by characterizing differentinterfacing technologies available on two commercialhandheld computers. Based on the characterization, weoffer a comparative study of energy efficiency of thesedifferent interfacing methods. We find that speech-basedinput has a great potential to become the most energy-efficient interfacing method since we can speak at amuch higher rate than we can write or type. Such acomparative study offers guidelines for mobile systemdesigners when choosing interfacing technologies.

As the characterization clearly shows, energy require-ments of state-of-the-art interfaces are far from the the-oretical minimal. In fact, interfacing components, suchas the display and speaker subsystems, are among themost power-consuming components. On the other hand,human capacity is essentially limited, and the computerusually spends most of its time waiting for the humanuser during interaction. Therefore, significant energyis spent in waiting due to power-hungry interfacingcomponents and a slow user, leading to an energy effi-ciency bottleneck. Such a bottleneck cannot be removedwith more sophisticated user interfaces, which usually

MobiSys ’05: The Third International Conference on Mobile Systems, Applications, and ServicesUSENIX Association 247

consume even more power. Motivated by memory-cachetheory, we show how a low-power interface cache de-vice with much simpler and lower power interfaces canbe used to handle simple interactive tasks outsourcedfrom a host computer, and thus improve the batterylifetime of the latter. It saves energy essentially bybringing the interface energy requirements closer to thetheoretical minimal without sacrificing user productivitymuch for the simple outsourced tasks. In this work, wedesigned and prototyped a wireless wrist-watch as aninterface cache device to serve an HP iPAQ handheldcomputer.

The paper is organized as follows. We discuss limitson energy efficiency imposed by human factors inSection II. We then offer user interface energy character-ization and comparative studies in Sections III and IV,respectively. We present the design and experimentalresults for the wrist-watch as an interface cache devicein Section V. We discuss related works in Section VI,and conclude in Section VII. It is worth mentioning thatthere are many other issues involved in user interfacedesign and evaluation than energy efficiency, such asuser acceptance and form factors. In this work, how-ever, we focus on energy efficiency from a computerengineering perspective.

II. Limits due to Human FactorsThis section examines how human factors impose

limits on energy efficiency with regard to interfacingpower and user productivity (speed). It highlights theimportance of human factors and interfaces in determin-ing system energy efficiency as compared to computing.It also provides theoretical foundations for improvinguser interfaces for better energy efficiency.

A. Sensory Perception-based Limits

Landauer [23] showed that the theoretical lowerbound for energy consumption of an irreversible logicoperation is kT ln2, where k is the Boltzmann constantand T is the temperature. kT is of the order of 10−21Jat room temperature. All commercially available com-puting devices use irreversible logic operations and arehence governed by this bound. On the other hand,the computer has to communicate with its human userthrough the latter’s sensory channels. These channels infact set the minimal power/energy requirements for thecomputer output.

1) Visual output: Human vision energy thresholdshave been measured in different forms [4] in termsof minimal absolute energy, minimal radiant flux, andjust-perceptible luminance. Minimal absolute energy ismeasured for a very small solid-angle field, e.g., a pointsource, presented for a very short time (10−3s) so thatno temporal summation of radiant flux occurs. Minimal

radiant flux is measured for a very small solid-anglefield lasting for a long time so that temporal summationof radian flux occurs. Just-perceptible luminance ismeasured for a large-area visual field. These thresholdsare used to estimate the energy/power dissipation lowerbound for displaying information as follows.

Minimal absolute energy: Let us assume the user’scornea area is A, viewing distance D, and viewingangle Ω. We assume the light irradiance is the same forevery point within the viewing angle that is at the samedistance from the point source. Let Emin(λ) denotethe minimal light energy reaching the cornea that isdetectable by the user for light of wavelength λ. Thetotal energy emitted by the source is thus:

E(λ) =ΩD2

Ai·Emin(λ)≈ΩD2

A·Emin(λ)

where Ai is the area of the viewing sphere that isincident on the cornea. Ai is approximated as the corneaarea A.

Experimental results reported by psychology re-searchers [4] indicate that Emin for light of wavelength510nm is about 2·10−17∼6·10−17J . Assuming A =0.5cm2, D = 0.3m, and Ω = 0.125·2π sr, we haveE≈3·10−14∼9·10−14J , which is about seven ordersof magnitude larger than the energy required for anirreversible logic operation.

Note that the energy limit derived above is for rodvision, which is human vision under extremely lowluminance and colorless. Only the cone vision containscolor and is normally required for human-computerinteraction. The energy threshold for cone vision forλ = 510nm is more than 100 times that of rod vision.For users to sense color, the minimal energy would thusbe of the order of 10−11J .

Minimal radiant flux: Let Rmin(λ) denote theminimal radiant flux for light of wavelength λ thathumans can sense. For the viewing distance D andviewing angle Ω, the source radiant power is given by:

Φmin(λ) =Rmin(λ)·ΩD2

683·V (λ)

where V (λ) is the relative visibility factor and 683 isthe spectral efficiency for λ = 550nm in lumen/W .According to [4], the minimal radiant flux for whitelight rod vision is about 4·10−9lumen/m2. AssumingV (λ) for white light to be 0.8, we obtain Φmin ≈5·10−13W under the same assumptions for D and Ωas before.

Just-perceptible luminance: Suppose the just-perceptible luminance for light of wavelength λ isLmin(λ). Let S denote the area of the display andΩ the viewing angle. The total display radiant power,

MobiSys ’05: The Third International Conference on Mobile Systems, Applications, and Services USENIX Association248

Φmin(λ), is then

Φmin(λ) =Lmin(λ)·S·Ω

683·V (λ)

For white light, Lmin has been determined to be7.5·10−7candella/m2 [4]. With the same assumptionsas above, the minimal radiant power for a 12.1′′ laptopdisplay and white light is about 5·10−11W . For com-fortable reading, the luminance level is, however, about100π candella/m2 [4], which requires a radiant power of

about 2mW for a 12.1′′ display. This minimal radiantpower for comfortable reading is about seven orders ofmagnitude larger than the just-perceptible threshold.

2) Auditory output: Let Ω denote the solid hearingangle and D the distance between ears and the soundsource. The minimal sound intensity human beingscan hear is about 10−12W/m2 for a sound field ofrelatively long duration (>300ms) [12]. Below 300ms,the threshold sound intensity increases fast as the soundduration decreases [12]. Therefore, we can estimate theminimal energy, Emin, for human beings to detect onebit of auditory information to be

Emin = 10−12·300·10−3ΩD2

Assuming Ω = 0.125π sr and D = 0.3m, wehave Emin≈10−14J , which is of the same order ofmagnitude as the minimal energy required for dis-playing one bit of visual information. Note that theminimal sound intensity varies for sounds of differentfrequencies. 10−12W/m2 is approximately the just-perceptible intensity of sound at a 1000Hz frequency,which belongs to the span of frequencies human beingsare most sensitive to. A normal conversation generatesa sound level that is about 106 times larger than thejust-perceptible sound intensity. Therefore, for a user toobtain auditory information from a computing system,the sound intensity should be no less than 10−6W/m2.For the values of Ω and D given above, this results in anacoustic energy requirement of about 10−8J . Moreover,the above thresholds assume no noise (just-perceptibleintensity) or relatively low noise (conversational inten-sity). When ambient noise increases, the output soundlevel has to increase accordingly, according to Webber’sLaw [12].

3) Power reduction techniques: Based on the abovediscussion, we can formulate the power requirement ofa visual/auditory output as follows

P ∝ Ω·D2

η(λ)·V (λ)(1)

where η(λ) is the conversion efficiency from electricalpower to light/sound radiant power for wavelength λ,and V (λ) the relative human sensitivity factor. Mostdisplay research efforts have been devoted to improving

η(λ) by adopting new display devices. For organiclight-emitting devices (OLEDs), the best η(λ) so faris 70lumen/W for λ = 550nm [10]. This is about 10-fold smaller than the theoretical 683lumen/W upperlimit [4].

Reducing the viewing/hearing distance D seems tobe the most effective way to reduce output powerrequirement. Unfortunately, it poses a practical problemfor visual output since it requires changes to the way adisplay is used. Moreover, reducing D may also havean impact on other display parameters such as pixelsize and aperture (the ratio of the effective area todisplay area). A head-mounted display is a successfulexample where a reduced D is used. However, it ispromising only for limited scenarios such as militaryand virtual reality applications at this moment. Unlikehead-mounted displays, their auditory counterparts, ear-phones, are quite popular. Due to their extremely smallD and Ω, earphones are much more power-efficient thanloudspeakers, as we will see in Section III.

Moreover, many applications do not need a largeviewing/hearing angle. The viewing/hearing angle canbe controlled to reduce output power consumption too.Another hint from Equation (1) is that choosing thecolors/sounds with a higher human sensitivity, thushigher V (λ), will also reduce power. Human visionsensitivities to different colors differ by several ordersof magnitude. However, user experience with colors isquite complicated since color contrast and aestheticsalso matter.

B. Input/Output Speed

The energy consumption per task depends not only onsystem power consumption but also on the task duration,or speed. We next characterize input/output speeds forhuman-computer interaction, which will be used tocompare the energy efficiency of different interfacingtechnologies in Section IV. This subsection draws uponmany previous surveys [1].

Speaking/Listening/Reading speeds: 150 words perminute (wpm) is regarded as normal for conversationalEnglish for both speaking and listening. When speak-ing to computers, users tend to be slower at about100wpm [20]. Also, users can listen to compressedspeech at about 210wpm [29]. Such speaking and lis-tening rates set limits to the energy efficiency of speech-based interfaces, as shown in Section IV. Moreover,when speech-recognition errors have to be corrected,the speaking rate is reduced drastically to as low as25wpm [20]. For reading printed English text, 250 to300wpm is considered typical [5]

Text entry: Text entry on handheld devices is well-known to be much slower than on PCs with a full-size QWERTY keyboard. Table I summarizes results


from the literature about input speeds for popular textentry methods available on commercial handheld com-puters, such as HP iPAQ and Sharp Zaurus, which arestudied in this work. “Typical speed” refers to the rawspeed regardless of accuracy while “Corrected speed”refers to real speed when error correction is taken intoconsideration. Note that handwriting speed is for hand-printing, which serves as an upper bound for the inputspeed for any handwriting recognition-based text entry.The corrected word per minute (cwpm) for handwritingrecognition is around 7 [8]. We assume that the errorrate is low for hardware mini-keyboard thumbing, i.e.,typing with two thumbs, and error correction is fast, asassumed for the virtual keyboard in [8].

TABLE ITYPICAL TEXT-ENTRY SPEEDS FOR DIFFERENT METHODS

Method Typical speed Corrected speed(wpm) (cwpm)

Hardware mini-keyboard 23 [33] 22Virtual keyboard 13 [32] 12 [8]

Handwriting 15 [25] N/A

Stylus/touch-screen: For GUI-based human-computer interaction, the speed is usually dependenton how fast the user can respond to the GUI. In [37],we characterized the user delays and investigatedhow they could be predicted for aggressive powermanagement. As we are more interested in typicaldelays for energy-efficiency evaluation, we assumethat a 500 to 1000ms user delay is typical for GUIoperations on handheld devices.

III. Energy CharacterizationThe previous section demonstrated that human factors

impose limits on both interfacing power consumptionand interaction speed. It also offered the theoreticalminimum power requirements for interfacing. Althoughsuch minimum power requirements are orders of mag-nitude larger than those for computing, they are still farfrom the reach of the state of the art user interfaces aswe will see in this section.

A. Characterization Setup

Table II provides information on system settingsand input methods for the two handheld computerscharacterized in this work. iPAQ is also equippedwith Bluetooth. Note that several different handwritingrecognition schemes are available on both computers.The user can input text letter-by-letter using letter orblock recognition on both computers. The user can alsoinput a group of letters using Microsoft Transcriber [27]on the iPAQ.

Power measurements: Power measurements areobtained by measuring the voltage drop across a 100mΩ

TABLE IISYSTEM INFORMATION FOR IPAQ AND ZAURUS

iPAQ Zaurus

Model HP iPAQ 4350 Sharp SL5600SoC Intel XScale 400MHz

Storage 32MB ROM,64MB RAM

16MB ROM,64MB RAM

Display 240 × 320, 16-bit colorTransflective/backlight

Reflective/frontlight

OS MS Pocket PC 2003 Embedix Plus PDA2.0 (Linux 2.4.18)

Battery 1560mAh/3.7V 1700mAh/3.7V

Text entry Touch-screen with stylusHardware mini-keyboard (QWERTY)

Virtual keyboard (QWERTY)Handwriting recognition

Image/Video N/A CF digital camera

Audio Integrated mic., speaker & headphone jackSpeech recog. Voice

Command [28]N/A

sense resistor in series with the 5V power supply cord.The measurement system consists of a Windows XP PCwith a GPIB card and an HP Agilent 34401A digitalmultimeter. A program, developed with Visual C++,runs on the PC and controls the digital multimeter tomeasure the voltage value. The value is sampled about200 times per second.

Basic power breakdown: We first characterize thepower consumption due to hardware activities initiatedby user interaction. We use the power consumption ofidle PDAs (in the IDLE mode) with the display offas the baseline, and present the power consumption ofadditional hardware activities as extra power consump-tion relative to the baseline. The extra power/energyconsumption [36] of an event is obtained through twomeasurements: one for the system power/energy con-sumption during the period an event of interest occurs;the other for the system power/energy consumptionduring the same period when the event does not occur.For example, the extra power consumption of the LCDis obtained by subtracting the system power when thesystem is idle and the LCD is off from that whenthe system is idle and the LCD is on. The powercharacterization results are presented in Fig. 1. In thisfigure, “BT Trans.” refers to Bluetooth transmitting dataat 9.6 Kbps; “BT Paging” refers to Bluetooth seeking aconnection with another device, and “Comp.” refers tomeasurements when the system is executing a discrete-cosine transform (DCT) application repeatedly.

B. Visual Interfaces

We first examine visual interfaces.Graphical user interface: In [36], we presented

a comprehensive analysis of the system energy con-sumption required for GUI manipulations. In [37], we


47084

383

985

44482

189

244

295

1540

0 400 800 1200 1600

iPAQ

Zaurus

Power/Extra Power (mW)

BaselineLCDLightingComp.BT PagingBT Trans.

Fig. 1. Baseline power and extra hardware power consumption

showed, however, that most of the system energy isconsumed when the system waits for the next user input.If we ignore the extra energy consumed by the systemto generate a GUI response, GUI manipulation-basedinterfaces basically consume energy through a staticdisplay and an idle system. As pointed out in [36],the most effective system energy reduction strategy isto improve user productivity so that more tasks canbe accomplished given the same battery lifetime. InSection IV, the energy efficiency of GUIs is comparedwith other interfacing technologies based on the lengthof the corresponding GUI operation.

Visual input: Gesture recognition and lip-readinghave been proposed as possible techniques for multi-modal human-computer interaction. Both require videoor image input. We used a CF digital camera card onZaurus to obtain its power cost. When the camera isturned on with a 480×320 resolution and faces a staticobject, the system consumes about 1.35W . When theobject moves, the power consumption increases slightlyto about 1.36W . This is close to the power consumptionwhen the user is preparing for a shot, e.g., adjusting thefocus and view. Also, it takes about 0.33J to capture a480×320 picture. Since a user usually takes more thana few seconds to prepare a shot, it is obvious that itis more important to reduce the user’s preparation timeand system power consumption during that time thanreduce these for actually capturing the picture.

C. Auditory Interfaces

We next examine the auditory interfaces available oniPAQ and Zaurus.

1) Direct recording and playback: An auditory sig-nal can be directly recorded and played back for inter-facing purposes. Direct recording is often used for note-taking and direct playback for short sound responsesfrom the computers such as warnings and notifications.If there are too many sound responses to be feasible fordirect playback, speech synthesis is required.

Direct recording: iPAQ provides a hardware buttonto start recording (11KHz 16-bit Mono), which is veryuseful for audio note-taking. The recording consumes525mW . The extra power consumption is thus 199mW .

Zaurus draws about 198mW extra power consumptionwhen recording (16KHz 16-bit Mono).

Direct playback: A WAV sound clip (32KHz 16-bitmono) was played on both iPAQ and Zaurus. To separatethe power consumption of the speaker subsystem, theclip was played at different volumes. Table III showsthe power consumption under various scenarios. “Half”volume assumes that the volume controller is set at thehalf mark on each system. In this scenario, the clip is notcomfortably enjoyable on either system, even in a quietoffice environment, if the system is about two feet fromthe user head. All the system power numbers includethat consumed by the LCD.

The extra power consumption of the speaker sub-system is obtained by comparing the system powerconsumption before and after the system is muted. Thishas a significant impact on system power efficiency ifthe auditory output is used. Notably, using an earphoneinstead of the built-in loudspeaker reduces power bymore than 300mW and 410mW for iPAQ and Zaurus,respectively. The data also indicate that using a sim-pler audio format (WAV as opposed to MP3) reducespower consumption at the cost of increasing the storagerequirement. Since the extra power consumption of thespeaker subsystem for playing MP3 is similar to that forplaying WAV, the power consumption for playing MP3at different volumes is not presented.

2) Speech recognition and synthesis: We next ex-amine the Microsoft Voice Command [28] on iPAQto obtain its power for a speech recognition-basedinterface. Voice Command is similar to the MiPadTap & Talk system [22] except that synthesized speechis used as feedback to the user. Not having a detailedknowledge of its implementation, we adopted a black-box approach. We recorded both the power trace and theaudio input/output and then aligned them to divide thepower trace into meaningful segments. We fed differentinputs to Voice Command to elicit certain behaviorsfrom it.

Speech acquisition without speech being de-tected: We first evaluated Voice Command underno sound. Hence, the speech detection module doesnot detect any speech. A reasonable speech recogni-tion implementation will discard most of the acquiredspeech without performing feature extraction under thisscenario. Therefore, the power consumption can beattributed to the microphone subsystem and speechdetection module. From the power trace, we observedthat Voice Command calls the speech detection moduleabout every 250ms. Each call contributes to a peakin the power trace, leading to an average extra powerconsumption of 126mW .

Speech acquisition with speech being detected: Wenext evaluated Voice Command when fed with irrel-


TABLE IIIPOWER CONSUMPTION FOR DIFFERENT AUDITORY OUTPUTS

iPAQ (mW ) Zaurus (mW )Format Volume System Extra Speaker System Extra SpeakerWAV Max. 747 420 367 1,030 546 422

Half 552 232 172 637 153 29Muted 380 53 0 608 124 0

Earphone Max. 445 118 65 619 135 11MP3 Earphone Max. 476 149 N/A 632 148 N/A

evant utterances, which are detected as speech butnot recognized. The power trace generated was verysimilar to the one when there was no speech exceptthat the peaks became wider when the input utterancesbecame more continuous. These wider peaks can beattributed to feature extraction performed immediatelyafter speech is detected and recognition decoding aftera certain amount of speech is detected. The typicalpower consumption for processing a continuous irrel-evant utterance is about 780mW . Interestingly, if theutterance is relevant or recognizable, the average powerconsumption is actually much lower. For all the traceswe obtained with a valid command, the power consump-tion is usually about 680mW in this case. The higherpower consumption with irrelevant utterances may beintroduced by a larger search space. For valid utterances,the search space can be significantly pruned becausesome very promising search paths can be identifiedearly.

Speech synthesis: We recorded the power tracefor iPAQ when it synthesized the speech output forspeech recognition. The extra power consumption forthe speaker subsystem at maximum volume is 181mW ,which is significantly smaller than that shown in Ta-ble III. This is due to the fact that the sound clipused for generating the table is a continuous flow ofmusic while the synthesized speech output only usesthe speaker subsystem intermittently, leading to a muchlower duty-cycle. The non-speaker subsystem powerfor speech synthesis is about 75mW . Compared to the383mW extra power required for performing DCT (seeFig. 1), such a speech synthesis is not computationallydemanding on iPAQ at all.

It is worth noting that for many voice commands, thedisplay need not be on. This means that 82 to 526mW(82 + 444) power reduction is possible (see Fig. 1).As we will see in Section IV, speech recognition-basedinterfaces are more energy-efficient in many scenariosonly if the display is turned off compared to severalother interfacing technologies.

D. Manual Input Techniques

We next characterize the extra energy consumptionfor various manual input techniques for text entry. Forletter-based input, such as letter recognition and virtualkeyboard, we examine the extra energy consumption

for inputting a letter; for word-based input, such asTranscriber, we examine the extra energy consump-tion for inputting words of different lengths. Table IVpresents the extra energy consumption for inputting aletter. Fig. 2 presents the extra energy consumption forinputting words of different lengths using Transcriberon iPAQ. The energy consumption per letter increasesslightly as the word becomes longer due to a largerrecognition effort.

0

0.1

0.2

0.3

0.4

0.5

1 2 3 4 5

No. of letters per word

Ene

rgy

(Jo

ule

) Energy per word

Energy per letter

Fig. 2. Extra energy per word/letter for Transcriber

The above text-entry methods consume energythrough touch-screen usage and related CPU activities.However, the energy thus consumed is insignificantcompared to that consumed by the LCD, which needs tobe on during text entry. Therefore, the energy cost perletter is not the only indicator of the energy efficiencyof a text entry method. What matters more is the entryspeed, as we will see in Section IV.

TABLE IVEXTRA ENERGY CONSUMPTION FOR INPUTTING A LETTER

Input method Extra energy (mJ)iPAQ Zaurus

Hardware keyboard ∼30 ∼50Virtual keyboard ∼10 ∼80Letter recognition ∼30 ∼330

IV. A Comparative StudyBased on the discussion of interaction speeds and

energy characterization presented in Sections II and III,we next compare the energy efficiency of differentuser interfaces. As speech-based interfaces are gainingground, we use such an interface as the baseline.

A. OutputWe first examine the energy efficiency for presenting

language-based information through speech or text.


When the information to be presented is long enough,the reading/speaking rate determines the duration of pre-sentation. Let Rspk denote a comfortable speaking rateand Rrd a comfortable reading rate in wpm. Let Ptxt

denote the system power consumption for presentingtext. For simplicity, we assume that Ptxt is roughlyconstant for presenting any text. We ignore the energyconsumed to render the GUI for the text. The computeris basically idle after the text is presented on the display.On the contrary, the computer has to be active whenthe text is spoken back to the user. Let Pspk denote thecorresponding system power consumption.

The ratio of energy consumption for text and speechoutputs is therefore

routput =Rspk

Rrd· Ptxt

Pspk

The following techniques can impact routput: Pspk

can be changed drastically by turning the display on oroff or by using an earphone instead of the loudspeaker;Ptxt can be reduced by employing aggressive powermanagement [2], [37]. Fig. 3 gives different valuesof routput for iPAQ and Zaurus under some possiblescenarios based on data presented in Section III. Weassume Rrd = 250wpm and Rspk = 150wpm. “Light”indicates that the back light or front light is on and“PM” or “NPM” refers to whether aggressive powermanagement [2], [37] is employed or not. The X-axisdenotes whether the display, together with lighting for“Light,” is on or off and whether the built-in loudspeakeror earphone is used for speech output. For Zaurus, thedirect playback power consumption is used as Pspk.Note that the speech output is more energy-efficient ifand only if the ratio is greater than 1.

For iPAQ, when the back light is on for night-timetext reading, a synthesized speech output through anearphone with the display off would be more energy-efficient than a text output. For Zaurus, a speech outputconsistently consumes more energy for day-time usagewhen the front light is not needed. It is more energy-efficient only when the display does not need to be on.Its advantage primarily comes from the fact that thespeech output does not mandate that the power-hungrydisplay be on. On the other hand, it consumes twoto three times more energy if the loudspeaker is usedand the display is left on. The key to improving energyefficiency for a speech output is therefore to turn off thedisplay and adopt a low-power audio delivery methodother than a loudspeaker.

When the information is very short, such as shortmessages and notifications, the presentation durationis not primarily determined by the reading/speakingrate but other time overheads for eye/hand movementsand distraction. Therefore, speech and audio delivery

0

1

2

3

displayoff/earphone

displayoff/loudspeaker

displayon/earphone

displayon/loudspeaker

r out

put

Light/NPM-iPAQ

NPM-iPAQ

Light/PM-iPAQ

Light/NPM-Zaurus

NPM-Zaurus

Light/PM-Zaurus

Fig. 3. Ratio of system energy consumptions for text output overspeech output under different scenarios

can be very energy-efficient [11], [31] since it is notvisually intrusive and persistent. Such short messagesand notifications, if delivered as GUI presentations,could interrupt user’s ongoing work and require useraction to respond, e.g., to close the popup message box,leading to a larger energy overhead.

B. Input

Next, we compare the energy efficiency of differentinput methods. There are two types of input, namely,text and control.

Text entry: In Section III-D, we derived the extraenergy consumption for inputting a letter under differenttext-entry methods. As pointed out in Section II-B,the corresponding input speeds vary a lot. Let Rentry

denote the typical input speed in wpm. Let e denote theextra energy consumed for inputting one letter using themethod characterized in Section III-D and Pidle denotethe system idle-time power consumption. We assume anaverage word requires six letter inputs [5], including aspace. On the other hand, let Rspk denote a comfortablespeaking rate for recognition-based input and Precog thesystem power consumption during speech recognition.If we ignore the energy consumed during the delaybetween the end of speech and the end of speechrecognition, the ratio of the energy consumptions formanual text entries and speech-based text entries isgiven by

rinput =

PidleRentry

· 60 + e · 6Precog

Rspk· 60

=Rspk·Pidle

Rentry·Precog+

e·Rspk

10·Precog

Obviously, the energy efficiency of an input method isprimarily determined by its input speed.

Although Voice Command is not intended for textentry, we assume speech recognition-based text entrywould have similar power characteristics and thereforeuse the power consumed by the Voice Command recog-nition process (Precog). Fig. 4 plots the rinput for thehardware mini-keyboard (HW MKB), virtual keyboard(VKB), and letter recognition (Letter Recog.) usingdata from Sections II and III. For each method, fourcases are shown. “ideal” refers to typical input speed


0.1

1

10

100

0 20 40 60 80 100 120 140 160

Speech recog. input rate (cwpm)

r inpu

tHW MKB-ideal VKB-ideal Letter Recog.-idealHW MKB VKB LetterHW MKB-No LCD VKB-No LCD Letter Recog.-No LCDHW MKB-No LCD/Light VKB-No LCD/Light Letter Recog.-No LCD/Light

Fig. 4. Ratio of system energy consumption for different text-entrymethods over speech-based text entry

without considering error correction; “No LCD” refersto comparisons to speech recognition with the displayoff; “No LCD/Light” refers to night-time usage withthe back light on as compared to speech recognitionwith the display off. Except for “ideal,” input speedsare expressed in cwpm. The break-even line with rinput

equal to 1 is also shown. For any point above thisline, the speech recognition-based input is more energy-efficient. From Fig. 4, the potential energy advantagesfor speech recognition-based text input are obvioussince speech is potentially much faster than any othertext input method. However, a recognition-based inputmethod usually incurs much higher input errors, leadingto a much lower speed in cwpm. For example, thespeed of handwriting recognition is about half the speedof handwriting. Studies in [8] have shown that speechrecognition speeds of 17cwpm are already availableand may reach 45 to 50cwpm in the near future. Ifthe power consumption for correcting errors in speechrecognition is about the same as the power consumptionduring recognition, Fig. 4 shows that speech recognitionis already more energy-efficient than letter recognitionand also the virtual keyboard for night-time usage ifthe speech recognition-based interface does not requirethe display to be on. Moreover, when a speed of 45 to50cwpm is achieved by the speech recognition-basedinterface, it will be more energy-efficient than most text-entry methods, even the hardware mini-keyboard.

Command and control: Error correction drasticallydecreases the input speed for speech recognition-basedtext entry, leading to a much lower energy efficiency.For command/control applications such as Voice Com-mand, however, errors can be corrected much faster,e.g., by reissuing the command. Moreover, for suchapplications, the recognition accuracy is usually muchhigher. This leads to a higher throughput and thus ahigher energy efficiency. For a command/control task,let us assume it may take M stylus taps or it may

0

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imal

no

.ofw

ord

sp

ercm

man

d

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Fig. 5. The maximal number of words per command for better energyefficiency

take a W -word voice command. Let N denote thespeaking rate in cwpm. Based on the traces collectedfor PDA usage [37], we assume each stylus tap isaccompanied by a 750ms user delay, which is mostlyan underestimation for typical menu selections on iPAQ.Moreover, we assume that the energy consumed bythe GUI response can be ignored compared to thatconsumed during the user delay. Therefore, rcc, whichrepresents the ratio of the energy consumptions by GUI-based and speech-based command/control, is given by:

rcc =Pidle

Precog· M ·N ·0.75

60·W

Obviously, the shorter a voice command, the moreenergy-efficient it is. Fig. 5 shows the maximal num-ber of words per command required so that speech-based command/control is more energy-efficient thanGUI operations with different numbers of taps undervarious scenarios. 100% accurate speech recognitionwith N = 150 is used to draw the “ideal” line. Notethat 150wpm is regarded as the conversational Englishspeaking rate. In other cases, 95% speech recognitionaccuracy is used with N = 100, assuming 10 timesmore energy/time required to correct an error comparedto speech recognition. Such an assumption is pessimisticsince most errors can be corrected by simply reissuingthe command. “No LCD” and “No LCD/Light” havethe same meaning as in Fig. 4.

Fig. 5 shows that a one-word voice command is moreenergy-efficient than GUI operations with two or moretaps. If the display can be turned off for speech-basedcommand/control, its advantage is higher.

Taking notes: Speech and handwriting recognition-based text entries are mostly hindered by their lowaccuracy and high cost for correcting errors. However,if text transcription is not needed in real-time, e.g.,when using audio recording or handwriting to take anote, it is most energy-efficient to use speech sincespeaking is much faster than any other input method.However, if the note has to be retrieved in the formatthat it was recorded before recharging, there is a tradeoffbetween the energy consumptions for taking a note and


for retrieving it, especially when it has to be retrievedmultiple times.

C. Observations

The energy characterization and comparison pre-sented so far have provided concrete and practicaljustifications for defining system energy efficiency as

User productivityAverage power consumption . Based on such a characterizationand comparison, we can make the following observa-tions for improving energy efficiency.

Speed matters: The faster a task is accomplishedand the higher the user productivity, the more energy-efficient the system usually is. From this perspective,interface designers share a significant responsibility fordesigning an energy-efficient system. In most cases,improving user productivity may incur average powerconsumption increase. As long as the productivity im-provement percentage is larger than average powerincrease percentage, the system energy efficiency isimproved.

In terms of the specific interfacing methods, speech-based input stands out since speech is inherently muchfaster than other input methods. For recognition-basedinput, such as handwriting and speech recognition,accuracy is important due to the high cost of correctingerrors. Thus, accuracy is also important for systemenergy efficiency.

Display matters: The energy efficiency for adisplay-based interface suffers a lot since its averagepower consumption includes that of the display, whichis large. Touchscreen/stylus-based interaction basicallyintegrates the input hardware with the output hardware,leading to a high power consumption even for makingan input, especially for night-time usage. When thepower-hungry display has to be on with a slow inputrate, e.g., for all the manual text-entry methods, energyefficiency is drastically reduced. Speech-based inter-faces again may enjoy an energy efficiency advantagesince their display usage can be carefully avoided.

The power consumption landscape, however, is likelyto change in a few years due to progress in new displaytechnologies. OLEDs [10] promise high-quality low-power flexible displays for mobile computers. Moreimportantly, bistable display technologies [21], [35] willreduce the static power consumption to nearly zero. Thiswill significantly reduce the energy that a system spendsin waiting for user inputs.

Audio matters: Surprisingly, our energy character-ization results showed that the speaker subsystem isalso power-hungry, drawing as much as 367mW and422mW of power for iPAQ and Zaurus, respectively.This power consumption can be drastically reduced byusing earphones instead of loudspeakers. However, thewires connecting the earphones may impact other usage

Fig. 6. The prototype of a watch as the interface cache for iPAQ

issues. Since Bluetooth consumes more than 470mWextra power when actively transmitting data (see “BTTrans.” in Fig. 1), a Bluetooth headset is unlikely toreduce the audio delivery power consumption. There-fore, for better exploiting the speed of speech-basedinterfaces, low-power wireless voice stream deliverybetween the user and computer is critical.

V. Interface CacheIn the previous sections, we investigated how human

factors limit energy efficiency for handheld computerinterfaces, characterized different interfacing methods,and presented a comparative study for them. Since thecomputer responds to the user much faster than thelatter responds to the former, an increasingly powerfulcomputer, in terms of display and processor, has tospend most of its time and energy waiting for a consis-tently slow user. Such a speed mismatch is essentiallyimposed by human capacity and is growing, leading toa bottleneck in energy efficiency even for a system witha perfect user interface. The cache solution to addressthe speed gap between the processor and memory inconventional architectures [15] motivated us to design alow-power wireless device, to which the host computercan outsource simple interactive tasks. As an interfacingsolution to alleviate the energy efficiency bottleneck dueto a slow user, such a device functions like a cachefor more expensive interfaces on the host, reducinginterfacing energy requirements without sacrificing userproductivity much. Its design and prototype are dis-cussed next.

A. Wireless Cache for Interfacing

The cache device we designed and prototyped takesthe form of a wrist-watch that communicates with ahandheld computer wirelessly. The watch prototype andits host, the iPAQ used in the characterization, are shownin Fig. 6.

As an interface cache, the watch provides the hostcomputer with a limited display. It provides two dif-ferent services: active and passive. The watch stays


connected with the host and waits for user input forthe active service. The user input can be echoed onthe watch in real-time. For passive service, the watchcommunicates with the host from time to time to receivedata. The connection can be closed after data transmis-sion but the user can still access the data cached on thewatch. The watch provides its services through a simpleapplication-layer protocol, called the synchronizationprotocol. It is up to the host computer to determinewhat and how to display and how the connection ismanaged using the protocol. The watch simply followsinstructions from the host computer as a slave.

Hardware components: The watch consists ofthree major components: a Microchip PIC16LF88 mi-crocontroller, a 2 × 8 monochrome character LCD,and a Bluetooth-RS232 adapter (Promi-ESD class II)from Initium [17]. One MAX604 linear regulator isalso used. The system is powered by a 3.6V supplywith three 800mAh rechargeable AAA batteries. Themicrocontroller is run at a 10MHz clock frequency,drawing a current of less than 0.6mA. It drives theLCD module directly but controls the Bluetooth adapterthrough a 9.6Kbps serial port. The LCD module drawsa current of about 1mA. There is no lighting for theLCD module in the prototype, a limitation of the currentimplementation that can be easily alleviated. Therefore,we assume that the LCD module can be used at nighttime in the following discussion.

The Bluetooth-RS232 adapter implements the sim-plest Bluetooth application profile, the Serial Port Pro-file (SPP). Two devices with Bluetooth SPP can commu-nicate in the same way they would with an RS232 serialport connection. The Bluetooth adapter has a number ofoperational modes. When it is not connected or seekingconnection, it is in the STANDBY mode, drawingabout 6mA current, but can be turned off for moreenergy savings. In the following discussion, we use theSTANDBY mode to refer to both situations. When theBluetooth adapter is seeking connection through a Page-Scan session, it is in the PENDING mode, drawingabout 19mA current. In the PENDING mode, it doesPage-Scan for Tps ms every Tpc ms. Tps must be amultiple of a 625µs slot. Both Tps and Tpc can beconfigured through commands from the RS232 serialport, leading to different average power consumption.When the Bluetooth adapter is connected, it is in theACTIVE mode, drawing about 9mA current for nodata transmission and about 28mA during active datatransmission at 9.6Kbps.

Communication design: Since the data for thepassive service are not time-critical, the host buffersdata for a certain period of time and a connectionto the host is required only from time to time. Thecommunication between the watch and its host com-

puter is not data-intensive and communication occursonly sporadically. Therefore, energy consumption dueto data communication is very small compared to thatrequired to establish a connection. However, based onour energy characterization data presented in Section V-B, it is more energy-efficient to disconnect and thenreestablish a connection in a cooperative fashion whenthe connection is required more than 30 seconds later.By “cooperative,” we mean that both the watch and thehost enter the PENDING mode at the same time.

When the host is connected to the watch, it sched-ules the next communication with the watch accordingto prior-history-based prediction. It then determineswhether the current connection should be maintained orclosed based on when the connection will be requiredthe next time. If the connection needs to be closed, thehost notifies the watch when it will seek connectionnext time. After receiving such a notification, the watchshuts down its Bluetooth adapter and forces it backinto the PENDING mode when the specified time haselapsed. This ensures that a connection is established ina cooperative fashion, and keeps the watch and the hostsynchronized with a relatively low energy overhead,as we will see in Section V-B. If the watch losessynchronization with the host, they enter the PENDINGmode to re-synchronize.

Software design: The software on PIC is developedusing PicBasic Pro. In the main loop, PIC reads itshardware UART and interprets the data according to thesynchronization protocol. Following instructions fromthe host or user, PIC can send AT commands to changemodes for the Bluetooth adapter.

Software on the iPAQ, called watch manager, wasdeveloped using Embedded Visual C++ and built uponthe BTAccess library [3]. The watch manager functionslike a device driver. On the one hand, it implements thesynchronization protocol. On the other hand, it collectsinformation from different application software, suchas Outlook, according to the user configuration. Theinformation is buffered in the watch manager and thensent to the watch when it connects to the host. Eachtime it is connected to the watch, the manager schedulesthe next connection and notifies the watch through thesynchronization protocol.

Interface design: For this prototype, we used verysimple interfaces to support the targeted services: a 2×8monochrome LCD and three tact buttons, Buttons 1,2, 3. The user can change the watch service mode byclicking Button 3. When the watch is in the passiveservice mode, a Button 3 click puts the Bluetoothadapter into the PENDING mode unless the connectionwith the host is established. When the watch is in theactive service mode, a Button 3 click simply closes theconnection and brings the Bluetooth adapter back to


Auto Manual

Button 1 and 2

Button 1 or 2

OffButton 1 or 2

Button 1 double-click or time-out

Button 2double-clickor Button 1or Button 2

Fig. 7. State-machine description of the watch interface

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Fig. 8. Power consumption for the watch in different modes

the STANDBY mode to wait for the next scheduledconnection.

In the active service mode, a Button 1 click clearsthe display and sends a negative confirmation back tothe host, while a Button 2 click simply sends a positiveconfirmation. In the passive service mode, the user canuse Buttons 1 and 2 to browse the text messages cachedin the watch. The interface is better represented as afinite-state machine, as shown in Fig. 7. In the Autostate, the watch displays valid message entries in itsmessage cache by rolling the text messages through thefirst line of the LCD. Each message is rolled accordingto its meta-data, which specify its priority in terms ofhow many times it has to be repeated with each displaycycle. In the Manual state, the user can use Buttons 1and 2 to browse valid entries. Clicking Button 1 inducesa skip to the next valid entry whereas clicking Button2 rolls the current message on the LCD by one letter.Double-clicking Button 2 marks the entry currently onthe LCD as invalid and confirmed, which is conveyedto the host next time the watch gets connected to thehost.

B. Evaluation

We evaluated the prototype watch device as thewireless cache for iPAQ in order to see whether orby how much it would improve the battery lifetimeof iPAQ. Instead of using user studies and subjectivemetrics, we focused on evaluating the design withrelated objective metrics. We first present the energycharacterization results and then an analysis of energy-efficiency improvement.

Since the non-Bluetooth components on the watchare not power-managed, they draw about 2mA currentall the time. Fig. 8 presents the power consumptionfor the watch in terms of current consumption at 3.6V

when the Bluetooth adapter is in different modes. Fig. 9shows how the watch battery lifetime changes when theaverage communication interval changes. Most of the

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Fig. 9. Watch battery lifetime for different average communicationintervals

time, the watch stays disconnected from iPAQ and thereis no energy cost for Bluetooth. Assuming a typical1KB data exchange each time a connection is made,the time for data exchange is about 0.118 second. Thecorresponding energy cost for iPAQ is 84.2mJ (basedon a power consumption of 470+244 = 714mW fromFig. 1). Let Tp denote the time it takes the watch andiPAQ to establish a connection cooperatively and Ts

denote the average interval between two communicationevents. Note that when iPAQ is in the PENDING modedoing Paging, the power consumption is Phost = (84+244) = 328mW (see Fig. 1). On the other hand, weassume that if the watch is not used, the user has toaccess iPAQ directly at a frequency f with averageduration of Taccess (f < 1/Taccess). The averagepower consumption, Ph, of iPAQ during usage, is about(244+82+444) = 770mW and (244+82) = 326mWwith and without the back light, respectively. Let ∆fdenote the reduction in the iPAQ access frequency fdue to the use of the watch. Therefore, using the watchimproves the energy efficiency of iPAQ if

84.2 + Phost·Tp

Ts + 0.118 + Taccess< Ph·∆f ·Taccess (2)

where the left hand side gives the extra power consump-tion in iPAQ due to Bluetooth activities and the righthand side gives the power reduction due to reducediPAQ accesses. Fig. 10 plots the minimal frequencyreduction in terms of number of accesses per hour forthe cache device to improve the iPAQ energy efficiencywith different average communication intervals (Ts)and average access durations (Taccess). Based on ourmeasurements, Tp = 2.5s is used. It presents the resultsfor day-time (without the back light) and night-time(with the back light) access. Different lines representdifferent average access durations from 8 to 60 seconds.The figure clearly shows how many accesses per hourhave to be outsourced to the cache device to improvethe host computer energy efficiency. For day-time usage,


Different access durations (s)

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Fig. 10. Minimal frequency reduction for improving energy efficiency

if the cache communicates with the host every 30minutes on an average, the host energy efficiency willbe improved even if only two 30-second accesses orthree 15-second accesses can be outsourced in a day.For night-time usage, even half the number of suchoutsourcings will still improve energy efficiency.

C. Design Issues

We have shown how the watch can improve theenergy efficiency for the host with objective measures.Such a watch is one example of wireless interface cachedevices. In the following discussion, we highlight theimportant issues involved in the design of such devices.

Wireless communication: In terms of form factor,wireless communication between the host and cachedevices is almost mandatory. There are several wirelesspersonal-area network (PAN) technologies intended fordifferent data rate and application scenarios. We usedBluetooth in the current watch prototype because itsavailability on iPAQ and in the market facilitates pro-totyping. Unfortunately, Bluetooth, especially the iPAQBluetooth, imposes a high energy overhead for iPAQto establish a connection with the watch. This issuecan be addressed by implementing the iPAQ Bluetoothin a separate hardware system. In fact, IEEE 802.15.4or customized radio modules with a lower power con-sumption, shorter connection establishment time or con-nectionless communication may be employed to replaceBluetooth since the required data rate is not high. This,however, requires extra hardware to be added to iPAQ.

Tasks for outsourcing: User studies will be criticalfor determining which tasks should be outsourced toobtain the best tradeoff between the energy efficiencyof the host computer and complexity/cost of the cachedevice. First, instead of determining which tasks shouldbe outsourced, the cache device designer should insteaddetermine which input/output services the cache deviceshould provide. For example, the watch exports itsdisplay services through the synchronization protocoland any iPAQ application can utilize such services

by specifying what to display. This gives applicationdevelopers and users most flexibility. Second, even if atask itself suffers productivity degradation after beingoutsourced to a cache device, system energy efficiencyand overall productivity may still be improved. Forexample, browsing a text message from the watch willbe slower than reading it directly from the iPAQ display.However, if the overhead for the user to take out theiPAQ and power it on/off is considered, obtaining infor-mation from the watch may even be faster. As anotherexample, laptop usage has been shown to decreasewhen a BlackBerry smartphone is used [13] becausea user can better utilize downtime for productivity,e.g., reading/writing emails with the smartphone whilewaiting in a line.

Battery partition: A simple question for our in-terface cache proposal would be: what if we just givethe extra battery capacity of the cache device to thehost. In the prototype, such an extra battery capacitywill give iPAQ an extra operating time of about twohours. The rationale behind a cache device is that wecan achieve a longer system operating time by givingsome battery capacity to a low-power interface cachedevice. Therefore, when designing an interface cachedevice, we must consider the usage patterns of both thecache and host devices and user’s expectations of theirbattery lifetimes to achieve the best system operatingtime. Again, user studies will be extremely important.

D. Related Devices

Similar wrist-worn devices have been designed in-cluding the IBM Linux Watch [16] and MicrosoftSPOT watch [26]. They were intended to be a self-contained computer system. If viewed as cache devicesfor interfacing, they lie on the other extreme of thespectrum, embracing a feature-rich and power-hungrydesign. Indeed, the author of [14] blamed the highprice and short battery lifetime for the lackluster marketreception of the Microsoft SPOT watch. They differdrastically from our design of the interface cache device,


which emphasizes a low-power minimalist approach.The TiltType wrist device demonstrated in [9] displaystext messages from the computer using an XML-likeprotocol. With a similar minimalist approach, it wasinvestigated primarily as an input device based on Tilt-Type. None of these devices was proposed to improvethe energy efficiency of the host computer.

Related to the philosophy of using a low-powerinterface cache device, Intel’s personal server projectenvisions that the personal server, a handheld computer-like device, utilizes wall-powered displays in the en-vironment [34]. Since it can be much more energy-efficient to transmit user interface specifications wire-lessly than rendering and presenting the user interfaces,such a parasitic mechanism can be another user interfacesolution to overcome the energy efficiency bottleneckdue to a slow user.

VI. Related WorkLow-power research so far has offered many solutions

centered around the computer without much regard tothe way it interacts with the user, except a statisticalrequest model. Only recently, works have been reportedfor interface devices such as displays [6], [7], [18],[30], [36]. Also, human factors and user interfaces arerecognized as having a significant impact on systemenergy efficiency. Lorch and Smith [24] pointed out theimportance of using user interface events for dynamicvoltage scaling. In [36], we characterized the energyconsumption of different graphical user interface (GUI)features on handheld computers. We pointed out theimportance of idle time and user productivity in systemenergy efficiency. In [37], we also proposed techniquesto aggressively power-manage the system during idleperiods based on user-delay predictions. In [2], theauthors implemented an aggressive OS-based powermanagement scheme for exploiting idle periods on anItsy system. Similar techniques were also implementedon the IBM Linux watch [19].

VII. ConclusionsIn this work, we presented a comprehensive treat-

ment of energy efficiency considerations for handheldcomputer interfaces. We showed how human capacitiesimpose limits on system energy efficiency and charac-terized the energy cost for interfaces on two commercialhandheld computers. Based on energy characterization,we presented a comparative study of different interfac-ing technologies. Specifically, we found that speech-based input has a large potential for outperforming otherinput methods due to the fact that a human can speakmuch faster than write or type. On the other hand, aspeech-based output suffers from high power consump-tion required for audio delivery without enjoying a sig-

nificant speed advantage over text-based output. We alsopointed out that the speed mismatch between users andcomputers and power-hungry interfacing componentsintroduce a bottleneck in system energy efficiency. Tosolve this problem, we proposed a low-power low-costdevice to which a host computer outsources simple, yetfrequent, tasks. Such a device, serving a similar goalas the cache does for memory, is called the interfacecache. We designed and prototyped a Bluetooth wrist-watch as the interface cache for an HP iPAQ handheldcomputer. While most other digital watches were de-signed as complete stand-alone computer systems, ourwatch is designed purely to serve the host computer.The system functionality is carefully partitioned so thatonly minimal functionality is placed on the watch. Ourexperiments and analysis show that such an interfacecache will be able to improve the energy efficiency ofits host computer significantly.

AcknowledgmentsThe first version of the Bluetooth wrist-watch was

designed/prototyped by Lin Zhong with Mike Sinclairwhile at Microsoft Research as a summer research in-tern. The watch was designed to form a PAN of wirelessinterfacing devices to provide pervasive interfacing fora handheld device like iPAQ. The authors would liketo thank all the anonymous reviewers and the papershepherd, Dr. Mark Corner, for their suggestions thatsignificantly improved the paper.

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