Energy efficient algorithms and techniques for wireless mobile clients 0

ENERGY EFFICIENT ALGORITHMS AND
TECHNIQUES FOR WIRELESS MOBILE CLIENTS
BHOJAN ANAND
(Ph.D.), NUS
A THESIS SUBMITTED FOR THE DEGREE OF DOCTOR OF PHILOSOPHY
DEPARTMENT OF COMPUTER SCIENCE
SCHOOL OF COMPUTING
NATIONAL UNIVERSITY OF SINGAPORE
2012

DECLARATION
I hereby declare that the thesis is my original work and it has been written by me in
its entirety. I have duly acknowledged all the sources of information which have
been used in the thesis.
This thesis has also not been submitted for any degree in any university previously.
———————————–
Bhojan Anand
8 August 2012
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ACKNOWLEDGEMENTS
First of all I would like to thank my supervisor Professor A.L.
Ananda. I appreciate his guidance and support not only my research but
also my life. After four years of his supervision, his impressive
leadership becomes a big milestone in my life.
I am indebted to the coauthors of several papers included in this thesis.
The coauthors are Associate Professor Chan Mun Choon, Associate
Professor Rajesh Krishna Balan, Associate Professor Ooi Wei Tsang,
Associate Professor Chang Ee Chien, Mr Pravein Govindan Kannan,
Mr Karthik Thirugnanam, Mrs Jeena Sebastien, Mr Le Thanh Long, Mr
Pham Duc-Dung, Mr Soh Yu Ming and Mr Chong Lee Kee.

A special thanks to Associate Professor Ooi Wei Tsang and Associate
Professor Roger Zimmerman for their productive comments for my thesis
proposal and research. I am also particularly grateful to Associate
Professor Chan Mun Choon for his constructive comments and support
throughout the research period.
I appreciate to all fellow Ph.D. students and friends at the
Communication and Internet Research Lab for making the supportive
work environment. My deepest gratitude goes to my wife Florence Anand
and sons Mikhil Anand and Sashil Anand for their unflagging love and
support throughout my life; this dissertation is simply impossible without
them.
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TABLE OF CONTENTS
Page
DECLARATION . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . iii
ACKNOWLEDGEMENTS . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . v
SUMMARY . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . xii
LIST OF TABLES . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . xv
LIST OF FIGURES. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . xvi
LIST OF PUBLICATIONS . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . xxix
CHAPTER
1. INTRODUCTION . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 1
1.1 Mobile Clients Space . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 1
1.2 Mobile Applications . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 3
1.3 Saving Energy . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 4
1.3.1 Why is saving energy in mobile clients important? . . . . . . . . . . . . . . 6
1.3.2 Current Status & Challenges . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 9
1.3.2.1 Display Power Conservation . . . . . . . . . . . . . . . . . . . . . . . . 10
1.3.2.2 Wireless Interface Power Conservation . . . . . . . . . . . . . . . 12
1.4 Thesis Contribution . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 13

1.5 Thesis Organisation . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 16
2. RELATED WORK . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 18
2.1 LCD Power Conservation . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 18
2.2 OLED Display Power Conservation . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 33
2.3 Network Interface Power Conservation . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 43
2.4 Processing Unit Power Conservation . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 61
2.5 Summary . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 63
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3. DISPLAY POWER MANAGEMENT (LCD) . . . . . . . . . . . . . . . . . . . . . 65
3.1 LCD Display Technology . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 65
3.2 Tone Mapping Technique & Its Advantages . . . . . . . . . . . . . . . . . . . . . . . . . 68
3.3 Using the Gamma Function for Tone Mapping . . . . . . . . . . . . . . . . . . . . . . . 70
3.4 System Design . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 73
3.4.1 Backlight Power Measurement . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 75
3.4.2 Gamma to Backlight Relationship . . . . . . . . . . . . . . . . . . . . . . . . . . . 76
3.4.2.1 Analysis of Gamma to Backlight Relationship . . . . . . . . 77
3.4.3 Measuring Image Quality . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 78
3.4.3.1 Using the Image Quality Metrics . . . . . . . . . . . . . . . . . . . . 81
3.4.4 Computing Image Brightness . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 82
3.4.5 Human Calibration of Gamma Thresholds . . . . . . . . . . . . . . . . . . . . 83
3.4.5.1 Objective . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 83
3.4.5.2 Methodology and Setup . . . . . . . . . . . . . . . . . . . . . . . . . . . . 83
3.4.5.3 Results . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 85
3.4.6 Objective Analysis of Gamma Thresholds . . . . . . . . . . . . . . . . . . . . 86
3.4.7 Run-time Algorithm . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 87
3.5 Implementation . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 88
3.5.1 Selection of Games . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 88
3.5.2 Changing Backlight Level and Gamma . . . . . . . . . . . . . . . . . . . . . . . 90
3.6 Evaluation Methodology . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 90
3.6.1 Power Measurement Testbed Setup . . . . . . . . . . . . . . . . . . . . . . . . . . 91

3.6.2 Power Measurement - Methodology . . . . . . . . . . . . . . . . . . . . . . . . . . 93
3.6.3 User Study - Methodology, Participants, and Setup . . . . . . . . . . . . 94
3.7 Evaluation Results . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 96
3.7.1 Baseline Measurements . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 96
3.7.2 Measured Analytical Results . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 99
3.7.3 User Study Results . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 100
3.7.4 Overall Result: System Works Very Well . . . . . . . . . . . . . . . . . . . . 100
3.7.5 Summary . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 102
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4. DISPLAY POWER MANAGEMENT (OLED) . . . . . . . . . . . . . . . . . . . 103
4.1 OLED Display Technology . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 104
4.2 Key Observations on OLED Displays . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 105
4.3 Power Optimisation for Webpages - Texts . . . . . . . . . . . . . . . . . . . . . . . . . . 110
4.3.1 Colour Harmony . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 111
4.3.2 Brand Colour & Brand Identity . . . . . . . . . . . . . . . . . . . . . . . . . . . . 113
4.3.3 Chromatic and Achromatic Contrast & Colour Mapping . . . . . . . 120
4.4 Power Optimisation for Webpages - Images . . . . . . . . . . . . . . . . . . . . . . . . 124
4.4.1 Luminance Adaptive Colour Transformation . . . . . . . . . . . . . . . . . 126
4.4.2 HVS based Colour Transformation Algorithm . . . . . . . . . . . . . . . . 131
4.4.2.1 Algorithm Alternative . . . . . . . . . . . . . . . . . . . . . . . . . . . . 134
4.4.3 Adapting to Other Contents . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 138
4.5 System Implementation . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 139
4.6 Evaluation Methodology . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 141
4.6.1 Quality Measurements - Objective Metrics . . . . . . . . . . . . . . . . . . . 142
4.6.2 Quality Measurements - Subjective User Study . . . . . . . . . . . . . . . 142
4.7 Evaluation Results . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 145
4.7.1 Evaluation Results of Colour Transformed Webpages . . . . . . . . . . 145
4.7.2 Evaluation results of HVS based Image Manipulation
Algorithm . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 146
4.7.3 Overall Result (Combined) . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 150

4.7.4 Summary . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 151
5. POWER MANAGEMENT AT NETWORK INTERFACE
LEVEL . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 152
5.1 Mobile Games and Game Maps . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 153
5.1.1 Binary Space Partitioning . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 154
5.1.1.1 Potentially Visible Set . . . . . . . . . . . . . . . . . . . . . . . . . . . . 155
5.1.1.2 Limitations . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 158
5.1.2 Quadtree and Octtree . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 158
5.2 Distance Based Approach . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 161
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5.2.1 Game State Estimation . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 161
5.2.2 Macro Power Management . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 162
5.2.3 Micro Power Management . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 166
5.3 Visibility Based Approach . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 169
5.3.1 Dynamic Lookahead . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 172
5.3.2 Determining Sleep Times and Intervals . . . . . . . . . . . . . . . . . . . . . . 175
5.4 3D Renderer’s View Based Approach . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 176
5.4.1 Visibility and Spatial Subdivision Scheme . . . . . . . . . . . . . . . . . . . 177
5.4.2 Two-Level Scan Algorithms . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 178
5.4.2.1 Macro Scanning Algorithm . . . . . . . . . . . . . . . . . . . . . . . . 179
5.4.2.2 Micro Scanning Algorithm. . . . . . . . . . . . . . . . . . . . . . . . . 182
5.5 Wireless Interface Control at Client Side . . . . . . . . . . . . . . . . . . . . . . . . . . . 183
5.6 Algorithm Selection . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 184
5.7 Implementation . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 185
5.7.1 Network Characteristics of FPS and MMOG Games . . . . . . . . . . 185
5.7.2 Sleep Command . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 187
5.8 Evaluation Methodology . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 188
5.8.1 Evaluation Objectives. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 191
5.8.2 Defining a Quality & Power Metric . . . . . . . . . . . . . . . . . . . . . . . . . 192
5.8.3 Small Scale User Study - Methodology . . . . . . . . . . . . . . . . . . . . . . 195

5.8.4 Experiments . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 197
5.8.5 Additional Evaluations - Visibility Based Approach . . . . . . . . . . . 198
5.8.5.1 Using Traces for Repeatability . . . . . . . . . . . . . . . . . . . . . 198
5.8.5.2 Running the Simulations . . . . . . . . . . . . . . . . . . . . . . . . . . 199
5.8.6 Additional Evaluations - Renderer’s View Based
Approach . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 199
5.8.6.1 Using AMID for Error Control . . . . . . . . . . . . . . . . . . . . . 200
5.9 Evaluation Results . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 203
5.9.1 Distance Based Approach . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 203
5.9.1.1 Sparse Environment - Low player Density . . . . . . . . . . . 204
5.9.1.2 Dense Environment - High Player Density . . . . . . . . . . . 205
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5.9.1.3 Contribution from Micro and Macro Power
Management . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 205
5.9.2 Visibility Based Approach . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 205
5.9.2.1 Baseline - No Prediction . . . . . . . . . . . . . . . . . . . . . . . . . . 206
5.9.2.2 Experiments over Various Networks . . . . . . . . . . . . . . . . . 208
5.9.2.3 Effect of Velocity . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 210
5.9.2.4 Effect of Different Sleep/Wakeup Intervals . . . . . . . . . . . 212
5.9.2.5 Effect of player density . . . . . . . . . . . . . . . . . . . . . . . . . . . 213
5.9.2.6 Benefit of Our Dynamic Algorithm . . . . . . . . . . . . . . . . . 214
5.9.2.7 Real Power Measurements . . . . . . . . . . . . . . . . . . . . . . . . . 215
5.9.2.8 Another Perspective of Power Savings . . . . . . . . . . . . . . . 216
5.9.2.9 Impact of Errors on Perceived Quality . . . . . . . . . . . . . . 217
5.9.3 3D Renderer’s View Based Approach . . . . . . . . . . . . . . . . . . . . . . . 218
5.9.3.1 Effects of Map Type . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 219
5.9.3.2 Effects of Energy Threshold . . . . . . . . . . . . . . . . . . . . . . . 220
5.9.3.3 Effects of Player Density (number of Players) . . . . . . . . 221
5.9.3.4 Effects Error Controller on Optimising Algorithm
Parameters . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 222

5.9.3.5 Effects Error Controller on Average Error Rate . . . . . . 224
5.10 Summary of all Results . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 226
6. CONCLUSIONS AND FUTURE WORK . . . . . . . . . . . . . . . . . . . . . . . . 227
6.1 Conclusions . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 227
6.1.1 Conserving LCD Energy . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 228
6.1.2 Conserving OLED Display Energy . . . . . . . . . . . . . . . . . . . . . . . . . . 229
6.1.3 Conserving Wireless Network Energy . . . . . . . . . . . . . . . . . . . . . . . 229
6.2 Directions for the Future Research . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 230
BIBLIOGRAPHY . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 235
APPENDICES
A. GAMMA CALIBRATION (FOR LCD) - SURVEY FORM . . . . . . . 259
B. DISPLAY POWER MANAGEMENT (LCD) - SURVEY
FORM . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 265
C. DISPLAY POWER MANAGEMENT (OLED) - SURVEY
APPLICATION AND FORM . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 273
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D. NETWORK INTERFACE POWER MANAGEMENT -
SURVEY FORM . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 280
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SUMMARY
ENERGY EFFICIENT ALGORITHMS AND
TECHNIQUES FOR WIRELESS MOBILE CLIENTS
BHOJAN ANAND
(Ph.D.), NATIONAL UNIVERSITY OF SINGAPORE
Directed by: Professor Dr. A.L. Ananda
In this thesis we present a suite of algorithms and techniques for conserving energy
in battery operated smartphones. In modern smartphones, the three main sources of
power consumption are, 1) the display, 2) the network interfaces, and 3) the CPU.
We found that the wireless interface and display components dominate the power
consumption in current generation of smartphones.

Firstly, we focus on an adaptive backlight controlling algorithm which uses tone
mapping techniques intelligently for managing LCD display power of these devices.
The uniqueness of our work is the use of an efficient tone mapping operator γ (Gamma
Correction) to brighten the content. γ is implemented in hardware level for modern
smartphones and hence, it is efficient. However, due to its non-linearity, we conducted
set of well controlled experiments to get the relationship between γ and brightness.
In addition, we found that the contents which are brighter tend to loose more global
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contrast than darker contents when same amount of γ is applied. The effect of contrast
loss fostered us to develop an algorithm for dynamic application of gamma controlled
by contrast loss that can save up to 68% of energy.
Secondly, we describe colour transformation service, which transforms the colours
of web contents to power efficient colours for OLED displays. We found that power
consumption of OLED displays in smartphones depends on the colour and intensity of
the contents. We used the principle of colour theory (in particular, colour harmonic-
ity) and the characteristics of human visual system (in particular, eye’s non-liner
sensitivity to visible light spectrum and luminance levels) for colour transformation
and found that we can generate webpages with good colours (sometimes, even better
than the original colours of the webpage) that are power efficient and pleasing for
eyes. We show that with our approach we can save more than 60% of energy while
ensuring pleasant reading experience.
Thirdly, we discuss our algorithms which use three different approaches to manage
power at network interface level and a scheme for selecting the algorithms based on
the game genre and game map. The three approaches are, distance based approach,
visibility based approach and 3D renderer’s view based approach. The key goal of
all these algorithms is to predict the importance of client’s game state for next t
milliseconds. If a client has no chance for interacting with other player’s for next t
milliseconds the wireless interface is put into low power mode. We found that distance
based algorithm is efficient for huge open maps with few occlusions and the other two
are good for highly occluded maps. It is interesting to find that games with highly

occluded maps such as first person shooting games give more chances for sleeping. We
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can save about 57% of wireless interface energy with highly occluded maps without
affecting the quality of game play adversely. Renderer view based approach gives the
most efficient result provided the map is highly occluded and supportive occlusion
culling algorithm is already a part of the game engine.
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LIST OF TABLES
Table Page
1.1 Battery Lifetime in Modern Smartphones . . . . . . . . . . . . . . . . . . . . . . . . . . . . 5
2.1 Power consumption (in Watts) for various modes of Intel (3x3
MIMO) and Atheros (2x2 MIMO) NICs . . . . . . . . . . . . . . . . . . . . . . . . . 52
3.1 Demographics Statistics for the User Study . . . . . . . . . . . . . . . . . . . . . . . . . 97
3.2 Baseline Power Consumption of the Laptop . . . . . . . . . . . . . . . . . . . . . . . . . 98
3.3 Baseline Power Consumption of the HTC Magic . . . . . . . . . . . . . . . . . . . . . 98
3.4 Power-Savings Measurements . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 99
4.1 Demographics Statistics for the User Study . . . . . . . . . . . . . . . . . . . . . . . . 143
5.1 Map Size of MMOG games . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 158
5.2 Power Characteristics of Different Interfaces . . . . . . . . . . . . . . . . . . . . . . . . 184
5.3 Selection of Algorithms . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 186
5.4 Power characteristic of the card used . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 189
5.5 Effects of Map Type - Experiment Variable Setup . . . . . . . . . . . . . . . . . . . 219
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LIST OF FIGURES
Figure Page
1.1 Backlight level vs Power for HTC Magic Android Phone [1] . . . . . . . . . . . . 6
1.2 Component Power Consumption (HTC Magic) [1] . . . . . . . . . . . . . . . . . . . . 9
2.1 Structure of a Transmissive TFT LCD . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 19
2.2 Visibility of the Image in a Transmissive TFT in some Environment
Luminance Condition [2] . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 20

2.3 Image and its Discrete Histogram . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 21
2.4 Luminance as a function of Backlight and Transmissivity . . . . . . . . . . . . . 24
2.5 Visual Effects of Adjusting Brightness (b), Contrast (c), and Both (d)
when the Backlight is Dimmed to 50% . . . . . . . . . . . . . . . . . . . . . . . . . . 25
2.6 Luminance as a function of Backlight and Transmissivity [3] . . . . . . . . . 27
2.7 Luminance vs Perceived Brightness . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 28
2.8 Relation Between MSE and Backlight Level . . . . . . . . . . . . . . . . . . . . . . . . . 32
2.9 Energy plot of the hues of 6 categorical colours (from left to right:
blue, red, purple, orange, green, yellow). Evergy (E) vs Lightness
(L
∗
) [4] . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 35
2.10 Categorical colours of varying lightness sorted by increasing energy
cost [4] . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 35
2.11 Tooth Dataset Coloured with Traditional Colours (Original) and
Energy Efficient Colours [4] . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 36
2.12 Unstructured Transformed GUIs with Different Settings . . . . . . . . . . . . . . 38
2.13 Colour Transformed ESPN Webpage . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 39
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2.14 Colour Quantizing an Image to N = 32 Colours . . . . . . . . . . . . . . . . . . . . . . 40
2.15 Colour Quantizing an Image to N = 512 Colours . . . . . . . . . . . . . . . . . . . . . 42
2.16 Power Consumption of Images Generated using Different
Algorithms . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 43
2.17 Power-constrained LMHE . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 44
2.18 802.11 State Transition . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 46
2.19 Client Listening Intervals in BSD . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 48
2.20 Drop Rate vs Energy Metric (Real player format at 512 Kbps) [5] . . . . . . 51
2.21 Split Communication for Multimedia Streaming . . . . . . . . . . . . . . . . . . . . . 53
2.22 Cell-to-Notify Protocol . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 56
2.23 Suspension Period . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 60

2.24 Suspension Period . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 61
3.1 Transmissive LCD Displays . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 66
3.2 Reflective LCD Displays . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 67
3.3 The Effect of Gamma and Linear Transformations. The Amount of
Power Saved is the Same for Both Approaches . . . . . . . . . . . . . . . . . . . . 71
3.4 Global Contrast Loss vs Gamma . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 73
3.5 Global Contrast Change vs Image Brightness for γ = 3 . . . . . . . . . . . . . . . 74
3.6 Power vs Backlight level . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 75
3.7 Backlight level vs Gamma value . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 77
3.8 Effect of Gamma Increase and Compensation . . . . . . . . . . . . . . . . . . . . . . . . 78
3.9 Gamma and Backlight Adjusting Tool . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 84
3.10 User-Perceived Acceptable Gamma Levels. . . . . . . . . . . . . . . . . . . . . . . . . . . 86
3.11 Contrast Loss vs Adaptive Gamma . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 87
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3.12 Flowchart of our System . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 89
3.13 Testbed . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 92
3.14 Setup for Laptop Power Measurement (Overall). [Note: Lenovo
Thinkpad W500 Laptop Adapter outputs 20V DC] . . . . . . . . . . . . . . . . 92
3.15 Results of the User Study for all 3 Maps. All Versions of the Game
were Deemed Playable by the Participants. . . . . . . . . . . . . . . . . . . . . . . 101
4.1 OLED Energy Consumption vs Screen Brightness . . . . . . . . . . . . . . . . . . . 106
4.2 OLED Energy Consumption vs Gamma Value . . . . . . . . . . . . . . . . . . . . . . 107
4.3 AMOLED sub-pixels close-up . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 108
4.4 Energy Vs RGB Sub-Pixel Values . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 110
4.5 Colour Wheel in RGB Colour Space . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 112
4.6 Colours Wheel Types . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 114
4.7 Colours - Associated Words - Sample Logos . . . . . . . . . . . . . . . . . . . . . . . . 115
4.8 Webpages designed using Brand Colours available in their Logos . . . . . . 116
4.9 Logos are Used as Favicons . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 118
4.10 Colour Extraction and Ranking from NUS favicon . . . . . . . . . . . . . . . . . . 119

4.11 Colour Extraction and Ranking from INTEL favicon . . . . . . . . . . . . . . . . 119
4.12 Background vs Text Area (After Excluding Images) - Sample
Webpages . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 123
4.13 Background vs Text Area . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 124
4.14 Change in Contrast vs Gamma . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 126
4.15 Effects of basic approaches on Image Contrast . . . . . . . . . . . . . . . . . . . . . . 127
4.16 Pixel power models of Goole Nexus One, Samsung Galaxy S and
Nokia N85 OLED displays. Axis X represents gamma-corrected
linear RGB values [6] . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 129
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4.17 Human Visual System Sensitivity . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 130
4.18 Local Contrast vs Brightness . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 131
4.19 An Image and its Contrast Map . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 132
4.20 Image Colour Transformation Process . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 134
4.21 Centralised Colour Transformation . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 140
4.22 Distributed Colour Transformation . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 141
4.23 Study on Readability and Colour Harmonicity . . . . . . . . . . . . . . . . . . . . . . 144
4.24 Study on Image Quality . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 145
4.25 Web Page Transformation with El-pincel. . . . . . . . . . . . . . . . . . . . . . . . . . . 147
4.26 Web Page Transformation - User Study . . . . . . . . . . . . . . . . . . . . . . . . . . . . 148
4.27 Power consumption and quality measurements . . . . . . . . . . . . . . . . . . . . . . 149
4.28 Image Transformation - User Study . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 150
5.1 Renderer’s view of world . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 156
5.2 A Cluster Divided into Areas . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 157
5.3 MMOG Map Sizes - A Graphical Comparison . . . . . . . . . . . . . . . . . . . . . . 159
5.4 Level of Detail . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 160
5.5 AoI - Dynamic Hexagonal Tile Distance/Visibility . . . . . . . . . . . . . . . . . . 165
5.6 Distance Based Approach . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 168
5.7 Inter-player Visibility With Obstacles . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 169
5.8 Possible Locations After Three Time-steps . . . . . . . . . . . . . . . . . . . . . . . . . 171

5.9 Basic Grid Weights (One Time-Step) . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 172
5.10 Scaling Grid Weights (Three Time-steps) . . . . . . . . . . . . . . . . . . . . . . . . . . 174
5.11 BFS follows the Path Distance of each Cluster . . . . . . . . . . . . . . . . . . . . . . 180
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5.12 Setup for Wireless Interface Power Measurement . . . . . . . . . . . . . . . . . . . . 189
5.13 PCMCIA Extender card (Accurite Technologies) . . . . . . . . . . . . . . . . . . . . 190
5.14 PCMCIA NEC PA-WL/54AG WiFi card used in the
Experiments . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 190
5.15 Screen Short Measuring MPD . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 196
5.16 Error Control Loop with AMID . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 202
5.17 Energy saving in sparse environment . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 204
5.18 Energy saving in dense environment . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 205
5.19 Distance (Macro) and Angle (Micro) based algorithms
composition . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 206
5.20 Results with no Prediction (q3dm1 Map) . . . . . . . . . . . . . . . . . . . . . . . . . . 207
5.21 Power Savings (3.5G Networks) . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 208
5.22 Power Savings (WiFi Networks) . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 209
5.24 Effect of Different sleep intervals . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 211
5.23 Effect of Velocity . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 211
5.25 Effect of Player Density . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 213
5.26 Dynamic Versus Static Algorithms . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 214
5.27 Actual Versus Simulation Results . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 215
5.28 User Study - Quality Loss Versus Alpha . . . . . . . . . . . . . . . . . . . . . . . . . . . 217
5.29 MapType vs. Energy Saved . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 220
5.30 Error Threshold vs. Energy Saved . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 221
5.31 Number of Players vs. Energy Saved . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 222
5.32 Fixed Sleep Time of Micro Scan varies over Time . . . . . . . . . . . . . . . . . . . 223
5.33 Error Convergence Over the Game Play Time for ET=5% . . . . . . . . . . . 223
xx
5.34 Error Convergence Over the Game Play Time for ET=3% . . . . . . . . . . . 225

5.35 Error Convergence Over the Game Play Time for ET=1% . . . . . . . . . . . 225
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NOMENCLATURE
ACC Achromatic Contrast
AER Average Error Rate
AIMD Additive Increase Multiplicative Decrease
AMOLED Active-matrix Organic Light Emitting Diode
AP Access Point
BL Backlight Level
BS Base Station
BSD Bounded Slowdown Protocol
CAM Constantly Awake Mode
CBCS Concurrent Brightness and Contrast Scaling
CBL Content Brightness Level
CBVLC Constant Backlight with Video Luminosity Compensation
CC Chromatic Contrast
CCFL Cold Cathode Fluorescent Lamps
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CPSM Centralised Power Save Mode
CTM Converse Tone Mapping
CTS Clear To Send
DAQ Data Acquisition Equipment
DBA Distance Based Approach
DBP Dynamic Beacon Period
DCA Dual-Compensation Approach
DCF Distributed Coordination Function
DLS Dynamic Backlight Luminance Scaling
DRA Dual Ring Algorithm
DTM Dynamic Tone Mapping
DVFS Dynamic Voltage and Frequency Scaling

ESD Effective Sleep Duration
ESPN Entertainment and Sports Programming Network
FPS First Person Shooting Game
FST Fixed Sleep Time
GCL Global Contrast Change (Loss)
GOP Group of Pictures
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GOS Group of Scenes
GUI Graphical User Interface
HAL Hardware Access Layer
HD High Definition - Resolution (1280 x 720)
HEBS Histogram Equalization for Backlight Scaling
HSV Colour Space based on Hue, Saturation, Value or Lightness
HVS Human Visual System
JND Just Noticeable Deference
LC Liquid-Crystal Cells
LCD Liquid Crystal Display
LED Light Emitting Diode
Li-Ion Lithium-Ion
Li-Po Lithium-Polymer
LMHE Log-Modified Histogram Equalisation
LMS Least Mean Squares
LWM Low Water Mark Level
MAC Media Access Control
MIMO Multiple Input Multiple Output
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MMOG Massively Multiplayer Online Game
MPD Vertically Integrated Approach
MPEG Moving Picture Experts Group
MPSM Mobility Aware Power Saving Mode

MSE Mean Square Error
MSSIM Mean Structural SIMilarity Index
NAPman Network-Assisted Power Management
NI National Instruments
Ni-Cd Nickel-Cadmium
Ni-MH Nickel-Metal Hydride
OIA Open Innovation Approach
OLED Organic Light Emitting Diode
OS Operating System
PB Perceived Brightness
PCI Peripheral Component Interconnect
PDVS Practical Voltage Scaling
PID Proportional Integral Derivative
PLRD Programmable LCD Reference Driver
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