klem: a method for predicting user interaction time and system energy consumption during application...
TRANSCRIPT
KLEM: A Method for Predicting User Interaction Time and System Energy Consumption during Application Design
CHRISTIAN DZIUBAILYAS DASKAYA
Ubiquitious ComputingWS-2009TU-BRAUNSCHWEIG
Lu Luo and Daniel P. Siewiorek1-4244-1453-9/07©2007 IEEE.
Intro
Motivation and Goals KLM in Brief KLEM – an overview
Modelling Process Energy Characterizing Process
Interaction Benchmarks An Experiment Setup Results & Model Verification Conclusion
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Motivation & Goals
Energy consumption from user interaction– Wide variety of user interaction methods– Highly interactive tasks– Unavailability of application at design time– High cost to conduct user study
Keystroke-Level Energy Model (KLEM)– Keystroke-Level Model (KLM) extended– Predicts expert user task time– Predicts system energy consumption of task
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What is “KLM”? (Keystroke Level Model)
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Created by Card, Moron, and Newell in 1980Based on GOMS (goals, operators, methods, selection rules)Describe a task by placing operators in a sequence
•K –keystroke•P –point with mouse•H –homing (move hand from mouse to keyboard)•D (takes parameters) –drawing•R (takes parameters) –system response time•M –mental preparation
There are heuristic rules to insert candidate Ms into the sequenceTask execution time = Σall operators involvedKLM for pen-based handheld user interfaces
Physical Operators
Mental Operator
KLEM as an extension to KLM
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Given: a task, the methods to execute the task, the design, and a target platformPredict: user time and task energy
KLEM – Modelling Process
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Using CogTool http://www.cs.cmu.edu/~bej/cogtool/Support touch-screen and voice-based interfacesCreate KLM by demonstrating task on storyboardsSample model trace created by ACT-R
KLEM – Modelling Process
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We can define various types of widgets in CogTool which is supported by the respective hardware (eg. PalmTungsten 5)
Interaction Benchmarks
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After the user selects an item, the application records the selection,updates a small area of the display to look responsive to user operation, and goes back to the waiting/idling state for the next user operation. We define this kind of system activity “Small”. As for “Medium” and “Large” system activities, for example, if a “next” button is pressed to open a new window, the consequent system activity is defined “Medium”, while an “open” button that reads a 1MB file is considered “Large” system activity.
KLEM - Energy Characterizing Process
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Measurement based approachPower state correspondence of KLM operators“Busy”(K, D, R): MOTOR, WAIT-FOR-SYSTEM…“Idle”(M): VISION, PROCEDUAL…Operator time decided by KLM and benchmarks
Button Press Display Update
(more states can be added)
An Experiment Setup
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Platforms:•Windows Mobile (iPaq) •Palm OS (Tungsten)
Method 1: map navigation interface
Method 2,3,4: scroll list interface
Model Verification - user time
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User study:•10 participants•Two platforms•12 tasks in total
Measurement:•Total task execution time•Prediction error:5.6% for iPaq 8.8% for Tungsten
Model Verification – task energy
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Measurement:•System energy consumption during task
Prediction error: •4.4% for iPaq 8.4% for Tungsten
Conclusion
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A methodology based on well-established HCI theory and practices is introduced to make design-time prediction on interactive task energy consumption
The energy efficiency of different user interaction methods on the same task is compared and analyzed. Author show when using different interaction modalities, the energy consumption can vary by a factor of three in achieving the same user goal.
Future work is to extend KLEM to other interaction modalities such as speech recognition for input and speech synthesis and speech playback for output.