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Human Factors and User Interfaces in Energy Efficiency
Lin ZhongELEC518, Spring 2011
2
Motivation
Operating system
ApplicationSoftware
Hardware
User interface
User
Processor MemoryMassive storage
Network interface
Display & other interface hardware
3
Energy efficiency: definition
Energy efficiency = User productivity
Avg. power consumption
= (User productivity) ×(Power efficiency)
Human-computer interaction (HCI)
Low-power design
4
Limits
• Minimal power/energy requirements
• Human speeds
5
Speed mismatch
1
10
100
1000
10000
100000
1000000
1968 1972 1976 1980 1984 1988 1992 1996 2000 2004
Year
Tim
es
of
imp
rov
em
en
t
Olympic Gold Metal winner: 100m dash (men)
Olympic Gold Metal winner: 100m dash (women)
# of transistors for Intel processor
Processor performance measured in MIPS
A constantly slow user
An increasingly powerful computer
Sources: intel.com and factmonster.com
6
Slow-user problem
0
0.2
0.4
0.6
0.8
1
0 1 2 3 4 5
Time (s)
Po
we
r (W
att
)A computer spends most of its energy in interfacing
Slow-user problem cannot be alleviated by a “better” or more powerful interface
7
Model Human Processor
Cognitive process
Perceptual process
Motor process
Model Human Processor: Card, Moran & Newell’83
Three processes involved in the user reaction to a computer
Perceptual process• Fixations and saccades
– Fixation: information absorbed in the fovea (60ms)
– Saccades: quick movements between fixations (30ms)
– Each GUI object requires one fixation and one saccade
• Rauding rate– Raud: read with understanding– 30 letters/second (Carver, 1990)
8
9
Cognitive process
• Hick-Hyman Law– N distinct and equally possible choices
• Applicable only to simple cognitive tasks– Selection: menu, buttons, list
(s) 1Nlog7
1delay Cognitive 2
10
General form
• Hick-Hyman Law
– pi : the probability that the ith choice is selected
– pi can be estimated based on history
)1
(1 log7
1delay Cognitive
i1 pp
N
ii
11
Motor process
• Stylus operation
• Fitts’ Law– A: distance to move– W: target dimension along the moving direction
– Parameters adopted from (MacKenzie and Buxton, 1992)
(s) )1(log166.023.0delayMotor 2 W
A
12
0 5 10 15 20 25 30 35 40 45 50
0
5
10
15
20
25
30
35
40
45
50
Power Law of practice
• Speed on nth trial – Sn = S1 na, where a ≈0.4 – Applies to perceptual & motor processes– Does not apply to cognitive process or quality
Learning curve of text entry using Twiddler, Lyons, 2004
Power Law predictionMeasurement
13
Human capacity limitations
Human capacity
• Perceptual• Cognitive• Motor• ……
14
Cache
Frequent interactions
Frequently accessed data
Task to outsource
Interfacing energy
Memory access latency
Cost to reduce
Computer & user
CPU & memorySpeed mismatch
Interface cacheMemory cache
Alleviate slow-user problem with a “worse” or less powerful interface
15
Interface cache: examples
Flip phones
Average time spent on laptop per day declined from 11.1 hours to 6.1 hours 5 months after Blackberry deployment
-----Goldman Sachs Mobile Device Usage Study
16
Human thermal comfort
Starner & Maguire, 1999 and Kroemer et al, 1994
17
A hot case: 3-Watt Nokia 3120
Phone case temperature will be 40 deg C higher.
Every One Watt increases surface temperature by about 13 deg C
18
Minimal power/energy requirement
D
Ω
Visual and auditory output
Emin ≈ Ω·D2·10-13 (Joule)
About 10-14 (Joule) for most handheld usagePoint source
Minimal energy requirement for 1-bit changewith irreversible computing
10-21 (Joule) (Landauer, 1961)
19
Insights for power reduction
D
ΩPoint source
P∝Ω·D2
η(λ)·V(λ)
η(λ): conversion efficiency from electrical power
V(λ): relative human sensitivity factor
Reflective layer to control Ω
λ: wavelength of light/sound
20
Text entry speed (productivity)
150
2313 15
25 2212
7
0
20
40
60
80
100
120
140
160
180
Speaking mini hardware keyboard Software keyboard withstylus
Handwriting
Spe
ed (w
ords
per
min
ute) Raw speed
Corrected speed
21
Impact of human factors
0
0.2
0.4
0.6
0.8
1
0 1 2 3 4 5
Time (s)
Po
we
r (W
att
)
Length of idle periods cannot be significantly reduced
Power consumption in idle periods is dominated by interfacing devices
Using Calculator on Sharp Zaurus PDA
99% time and 95% energy spent in idle periods during interaction
22
Experimental setup
Intel Xscale 400Mhz
240X320, 16-bit color
mic., speaker & headphone jack
WindowsTransflective/back lightBluetoothSpeech recog.
Linux/QtReflective/front light
DevicesHP iPAQ 4350 Sharp Zaurus SL-5600
23
Experimental setup (Contd.)
iPAQ H3870
RsVsVdd
5V
Host machine GPIB card GPIB cable Agilent 34401A multimeter
Measurement
200 samples/second
24
0
0.4
0.8
1.2
1.6
0 0.5 1 1.5
Time (s)
Po
we
r (W
)
Experimental setup (Contd.)
0
0.4
0.8
1.2
1.6
0 0.5 1 1.5
Time (s)
Po
we
r (W
)
Extra energy/power consumption of an event is obtained through differential measurement
Extra energy consumption by writing “x”
Write “x” with stylus/touchscreen
25
Power breakdown
A handheld usually spends most time being idle but the display has to be on most time
If the display is not on, the speaker subsystem is usually on
0
1
2
3
4
iPAQ Zaurus
Pow
er c
onsu
mpt
ion
(mW
) Earphone
Speaker
Lighting
LCD
Computing
Basic idle
Computing: carrying out DCT repetitively
26
Energy characterization
• Visual interfaces– Graphical user interfaces (GUIs)– Digital camera
• Auditory interfaces– Recording/playback– Speech recognition & synthesis
• Manual text entry
27
GUIs• Stylus/Touch-screen• Most energy/time spent in idle periods
– Energy consumed by computing negligible
• Task time determines energy consumption
0
0.2
0.4
0.6
0.8
1
0 1 2 3 4 5
Time (s)
Po
we
r (W
att
)
280
0.4
0.8
1.2
1.6
2
1 207 413 619 825 1031 1237 1443 1649 1855 2061 2267
Time (1/206 s)
Po
we
r (W
)
Speech synthesis & recognition• Infer the behavior of Voice Command by
comparing voice recording and power trace
• Computing is not demanding• Used as baseline for comparison
Voice recording
Power trace
29
Comparison: Output
0
1
2
display off earphone
display on earphone
display offloudspeaker
display onloudspeaker
Different scenarios
r output
Lighting required for text
Lighting not required for text
• Speech is better only when– display is turned off – earphone is used – nighttime usage
iPAQ
spk
txt
rd
spk
P
P
R
Rr Energy efficiency
ratio
If r >1, speech output is more energy-efficient
30
Comparison: Text entry
0.1
1
10
100
0 20 40 60 80 100 120 140 160
Speech recog. input rate (cwpm)
r input
HW MKB-ideal VKB-ideal Letter Recog.-ideal
HW MKB VKB Letter
If r >1, speech recognition is more energy-efficient
State of the art
Near future
Ideal
31
Comparison: Text entry (Contd.)
0.1
1
10
100
0 20 40 60 80 100 120 140 160
Speech recog. input rate (cwpm)
r input
HW MKB-No LCD VKB-No LCD Letter Recog.-No LCD
HW MKB-No LCD/Night VKB-No LCD/Night Letter Recog.-No LCD/Night
Handwriting recognition is inferior to alternatives
Speech recognition can be the most energy-efficient
32
Comparison: Command & control• Speech vs. GUI operation
0
1
2
3
4
5
6
7
8
9
1 2 3 4 5
No. of taps
Ma
xim
al n
o. o
f wo
rds
pe
r co
mm
an
d
Ideal
95% accurate
95% accurate/No LCD
95% accurate/No LCD/LightAssume each stylus tapping takes 750ms
Single word voice command is more energy-efficient than GUI operation with 2 taps
33
Observations
• User productivity (speed) is critical – energy consumed being idle is significant
• Handwriting-based text entry is inferior• Speech-based text entry can be superior
– Turning off display is important– Accuracy
• Loudspeaker consumes significant power– Earphone incurs usability issue– Wireless audio delivery not energy-efficient
• “Computing” usually consumes trivial energy
34
Examples of energy inefficient interfaces
Kyocera KX2325 LG VX 6100 Microsoft Voice Command 1.01
35
Energy efficiency: definition
Energy efficiency = User productivity
Avg. power consumption
= (User productivity) ×(Power efficiency)
Human-computer interaction (HCI)
Low-power design
Model of Man
• Herbert Simon – Turing Award (1975) – Nobel Prize in Economics (1978)
• Human mind is simple; its apparent complexity is due to the environment’s complexity– Short-term memory is fast but small (~7)– Long-term memory is unlimited but writing takes time
(10 to 30 seconds)– Retrieval from long-term memory is associative and
depends on the storage structure
Bounded rationality
• Limitation on ability to plan long behavior sequences
• Tendency to set aspiration levels for each goal• Tendency to operate on goals sequentially
rather than simultaneously• Satisficing rather than optimizing search
behavior
http://www.princeton.edu/~smeunier/JonesBounded1.pdf