연세대학교 컴퓨터과학과 모바일 임베디드 시스템 연구실
윤찬민 ([email protected])
DEVIEW 2013 2013.10.14
Energy Management for Mobile Devices: Power Es8ma8on Technique for Modern Smartphones
Mobile Pla@orms
Mobile Embedded System Lab., Yonsei University 2
Feature Phone Galaxy S Galaxy S2 Galaxy S3
Cellular Bluetooth WiFi NFC
1GHz Single core GSM/HSDPA
480x800 Display, 4.0 inch 1500 mAh baWery
1.2GHz Dual core GSM/HSDPA
480x800 Display, 4.3 inch 1650 mAh baWery
1.4GHz Quad core GSM/HSDPA/LTE
720x1280 Display, 4.8 inch 2100 mAh baWery
Camera Mic.
Accel Compass
Light GPS
Proximity
Thermometer Gyroscope Barometer
FM Radio
GSM
240x320 Display
Galaxy S4
1.6GHz Octa core GSM/WCDMA/LTE
1080x1920 Display(Full HD), 5.0 inch 2600 mAh baWery
IrDA
Gesture
Energy Management for Mobile Devices
Mobile Embedded System Lab., Yonsei University 3
𝛼
Energy Management Techniques
Mobile Embedded System Lab., Yonsei University 4
• 단말/응용 가용시간 예측 • 사용자 요구 및 컨텍스트 반영 • 사용자중심 Energy-aware UX
• 실시간 응용프로그램 에너지 bug/hog 감지
• 응용프로그램의 에너지 특성에 따른 에너지 bug 및 hog 원인 분석 및 리포팅 시스템
Battery Lifetime; User Interaction; Requirement; User Experience; Personalization; Quality of Service; User Context; Spatiotemporal Context, …
Application; Energy Anomaly; Energy Bug; Energy Hog; Energy Leakage; Wakelock; Non-Sleep; Anomaly Detection; Debugging;
Anomaly Reporting, …
사용자 응용 프로그램
• 응용프로그램의 전력 소모 특성 정보 수집 관리 기술
• 가상 배터리 관리 기법 • Energy-aware OS
• 하드웨어 전력프로파일링 및 모델링 • 하드웨어 컴포넌트 전력 최적화 • DevFreq를 이용한 종합적 전력관리
Energy Usage; Application Energy Estimation; Process Energy Estimation; Virtualization; Battery Segmentation; Resource Management, …
하드웨어 시스템 소프트웨어
Hardware Component; Homogeneous; Heterogeneous;
Multicore System; Dynamic Voltage and Frequency; Devfreq Framework; Component Power
Management, …
Researches
Hardware-‐level Power Management (1)
Mobile Embedded System Lab., Yonsei University 6
Frequency Scaling GPU
Dynamic Voltage & Frequency Scaling
CPU
Brightness Level Control Display
Opportunisac Sensing Scheduling Sensors
Adapave Clock Rate Control Network
RGB Level Conversion
Hardware-‐level Power Management (2)
• DVFS (Dynamic Voltage and Frequency Scaling) – Voltage and frequency scaling are oden used together to save power in mobile
devices including cell phones.
• DVFS in Android/Linux (Power Governor)
Mobile Embedded System Lab., Yonsei University 7
Ondemand Performance Powersave Hotplug PegasusQ
Features ü DVFS only ü Set the CPU sta
tically to the highest frequency
ü Set the CPU statically to the lowest frequency
ü Dual-core ü Based on Onde
mand
ü Multi-core ü Based on Onde
mand
Frequency Control
ü Utilization ü CPU Frequency ― ― ü Utilization
ü CPU Frequency ü Utilization ü CPU Frequency
Multi-core Management ― ― ― ü Average CPU U
tilization ü CPU Frequency ü # of Processes
Hardware-‐level Power Management (3)
• Is DVFS really (or always) energy-‐efficient? – “DVFS scheme reduces power consumpaon, which can lead to significant
reducaon in the energy required for a computaaon, paracularly for memory-‐bound (I/O-‐bound) workloads” *
* Le Sueur, and Heiser, G., “Dynamic Voltage and Frequency Scaling: the Laws of Diminishing Returns,” HotPower’10
CPU-‐bound
I/O-‐bound
8 2
5 5
2 8 ame
10
16 2
10 5
18
15
CPU jobs I/O (memory) jobs
4 8 12 ame
900 J
1080 J
900 J
900 J
10
10
900 J
720 J
Inefficient
Efficient
Performance loss in every case
Mobile Embedded System Lab., Yonsei University 8
Hardware-‐level Power Management (4)
• OLED – OLED display power model is a linear funcaon of linear RGB intensity levels. – Different OLED displays have different power models
• Chameleon*
* M. Dong and L. Zhong, “Chameleon: a color-‐adapave web browser for mobile OLED displays”, MobiSys 2011.
25%ê 34%ê 72%ê 66%ê
Mobile Embedded System Lab., Yonsei University 9
Hardware-‐level Power Management (5)
B. Anand et al., “Adapave display power management for mobile games”, MobiSys 2011.
About 21% reducaon of power consumpaon with almost same UX as original image
• LCD (and OLED) – Reducing brightness level without UX-‐loss
Mobile Embedded System Lab., Yonsei University 10
Energy Bugs/Hogs (1)
• Some running instance of the app drain the baWery significantly faster than other instance of the same app
• Cause -‐ Coding error -‐ Rare configuraaon -‐ Unusual user behavior
• Remedy -‐ Restart the energy bug app -‐ Kill the energy bug app
Energy Bugs
• The app drains the baWery significantly faster than the average app
• Cause -‐ Coding error -‐ Using large amounts of energy to serve its funcaon (ex, device resources..)
• Remedy -‐ Kill the energy hog app
Energy Hogs
A. J. Oliner, A. Iyer, E. Lagerspetz, S. Tarkoma and I. Stoica, “Collaboraave Energy Debugging for Mobile Devices,” in Proc. of the 8th USENIX conference on Hot Topics in System Dependability, Berkeley, CA, USA, October 2012.
Mobile Embedded System Lab., Yonsei University 11
Energy Bugs/Hogs (2)
• Diverse causes of Energy Bugs – An error in the system, either applicaaon, OS, hardware, firmware or external that
causes an unexpected amount of high energy consumpaon by the system as a whole
A. Pathak, Y. C. Hu and M. Zhang, “Bootstrapping energy debugging on smartphones: a first look at energy bugs in mobile devices,” in Proc. of the 10th ACM Workshop on Hot Topics in Networks, Cambridge, MA, USA, November 2012.
Mobile Embedded System Lab., Yonsei University 12
Energy Bugs/Hogs (3)
• Managing Energy Bugs/Hogs – Diagnose: compare normal baWery drain and abnormal baWery drain – Suggest appropriate repair soluaons based on the diagnosis results
Informa8on Collector
Resource Usage
User Changes
Data Analyzer Phase
Idenaficaaon Per-‐applicaaon usage paWerns
System wide usage paWerns
Configuraaon paWerns
Diagnosis Engine Anomaly Detecaon
Suspicious Resource Usage
Suspicious Events
Repair Advisor
Delete Apps
Revert Apps
Terminate Apps
Revert Configs
* X. Ma, P. Huang, X. Jin, P. Wang, S. Park, D. Shen, Y. Zhou, L. K. Saul, and G. M. Voelker, “eDoctor : Automaacally Diagnosing Abnormal BaWery Drain Issues on Smartphones,” in Proc. of the 10th USENIX Symposium on NSDI’ 13, Berkeley, CA, USA, April 2013.
Mobile Embedded System Lab., Yonsei University 13
Sampling during discharging
Compare reference and subject
eDoctor* : Phase Analysis
Carat : Comparison Analysis
Energy Bugs/Hogs (4)
• Default power management policy for mobile device (new paradigm) – OS uses aggressive sleeping policies – Every component, including the CPU, stays off or in an idle state, unless the app
explicitly instructs the OS to keep it on!
• “No-‐sleep” Energy Management – Aggressive sleeping may severely impacts smartphone apps – Power encumbered programming : Androids “Wakelock” API
New Energy Bug* à “No-‐sleep” bug : 70% (applica8on)
* Pathak, Abhinav, et al, “What is keeping my phone awake?: characterizing and detecang no-‐sleep energy bugs in smartphone apps,” in Proc. of the 10th internaRonal conference on Mobile systems, applicaRons, and services (MobiSys 2012), ACM, 2012.
Mobile Embedded System Lab., Yonsei University 14
Energy Bugs/Hogs (5)
Mobile Embedded System Lab., Yonsei University 15
• WakeScope (mobed.yonsei.ac.kr/wakescope) – A runame WakeLock anomaly management scheme for Android plauorm
SCREEN FULL PARTIAL PARTIAL …
WakeLock Anomaly
WakeLock Anomaly Detector
Process Running State
CPU Usage
Applicaaon & Android system stop state checking
WakeLock release checking
WakeLock Anomaly checking
Screen state Light off ame
SCREEN FULL PARTIAL
WakeScope Applica8on
Handling of WakeLock Anomaly
Kill Applicaaon
Reboot Smartphone
Applica8on Android System
Linux Power Management
“PowerManagerService”
PARTIAL “…..”
PARTIAL …
Applica8on Android System
WakeLock behavior tracking
PARTIAL SCREEN FULL Applicaaon Android System
SCREEN FULL
WakeLock behavior tracking Android System
PARTIAL
WakeLock Behavior Tracker
Binder
Android Framework
PARTIAL SCREEN FULL
PowerManagerService
Android Power Management
Energy-‐aware UX (1)
• Beder energy-‐related understandings à energy-‐efficient behavior
• Task-‐centered Badery Interface* – Support users’ mental models on fully understanding what is happening on
their devices *K. N. Truong, et al. "The Design and Evaluaaon of a Task-‐Centered BaWery Interface,“ UbiComp 2010.
Mobile Embedded System Lab., Yonsei University 16
TCBI* Android BaWery Informaaon 1.6 Donut 4.1.1 Jellybean
Energy-‐aware UX (2)
• HCI-‐based Display Control – Reduce display power by dimming the parts of an applicaaon or game that are of
low interest
Wee, Tan Kiat, et al. "DEMO of Focus: A Usable & Effecave Approach to OLED Display Power Management,“ HotMobile 2013.
Brighten user-‐interest area
Dim less important area
Mobile Embedded System Lab., Yonsei University 17
Energy-‐aware UX (3)
• Ac8ve User Involvement – User is a main actor for energy management
M. Marans and R. Fonseca "Applicaaon Modes: A Narrow Interface for End-‐User Power Management in Mobile Devices,“ HotMobile 2013.
Mobile Embedded System Lab., Yonsei University 18
Energy-‐aware UX (4)
• Badery Virtualiza8on – Virtualizaaon of the baWery resource across applicaaon classes
N. Zhang et al. “PowerVisor: a baWery virtualizaaon scheme for smartphones,“ MCS 2012.
Physical Badery
Virtual BaWery 1
Virtual BaWery 2
Virtual BaWery 3
App Class 1
App Class 2
App Class 3
Mobile Embedded System Lab., Yonsei University 19
Badery Saving
Energy-‐aware UX (5)
• Context-‐based Badery Management: BaderyGuru (Qualcomm) – Extends baWery performance and improves overall user experience by
intelligently making changes that opamize device funcaonality
Mobile Embedded System Lab., Yonsei University 20
• Manage applicaaon’s update points • Control WiFi on/off
Preferred Applicaaons Preferred/Available WiFi regions
Automaac learning
Es8ma8on
Power Modeling & Energy Es8ma8on (1)
• Why applica8on/component energy informa8on is valuable?
Applica8on/Hardware Energy Metering
App. Developer
System Developer
End User Mobile Embedded System Lab., Yonsei University 22
Power Modeling & Energy Es8ma8on (2)
Challenges: how to estimate application’s energy consumption?
Mobile Embedded System Lab., Yonsei University 23
CPU
GPS
Cell
WiFi
Display
GPU 𝑃↓𝐶𝑃𝑈 = 𝛽↓𝑓 ⋅𝑈↓𝐶𝑃𝑈 + 𝛽↓𝑖𝑑𝑙𝑒 ⋅(1− 𝑈↓𝐶𝑃𝑈 ) 𝑃↓𝑂𝐿𝐸𝐷 =𝑓(𝑅,𝐺,𝐵) ⋅
(𝛽↓𝑅 𝑅↓𝑖 + 𝛽↓𝐺 𝐺↓𝑖 + 𝛽↓𝐵 𝐵↓𝑖 ) 𝑃↓𝐺𝑃𝑈 = 𝛽↓𝑓 ⋅ 𝑈↓𝐺𝑃𝑈 + 𝛽↓𝑏𝑎𝑠𝑒 𝑃↓3𝐺 = 𝛽↓3𝐺 , 3𝐺={𝑈𝑀𝑇𝑆,𝐻𝑆𝑈𝑃𝐴,𝐻𝑆𝑃𝐴𝑃}
𝑃↓𝐺2𝐷𝑋 = 𝛽↓𝐺2𝐷𝑋 ⋅ 𝑃𝑖𝑥𝑒𝑙𝑠↓𝐺2𝐷𝑋 + 𝛽↓𝑏𝑎𝑠𝑒 …
Acave cores Frequency
Ualiza
aon
Colors/ Brightness
Display occupancy ame
3G/LTE
RRC state
Connected ame
High/low Power state
TRX packets
Device Power Modeling (1)
Mobile Embedded System Lab., Yonsei University 24
CPU
DISPLAY
GPU
𝑃↓𝑡↑𝑖 = 𝛽↓𝑖 ⋅ 𝑥↓𝑖↑𝑡
Component behavior and usage
𝑃↓𝑡↑𝑡𝑜𝑡𝑎𝑙 = 𝑃↓𝑏𝑎𝑠𝑒 +∑𝑖=1↑𝑛▒𝑃↓𝑡↑𝑖 + 𝜖↓𝑡
Total Power
Base Power
Error, Leakage
Component Power
Maximum power consumption of
component 𝑖
Device Power Modeling (2)
• Issues – Component-‐specific ualizaaon metric
• uame/same, cores, frequency, color/brightness, packet, tail state, temp, …
– Base power esamaaon • System base power, component base power
– Isolated control of hardware component • Isolaang CPU influence from component power monitoring
Mobile Embedded System Lab., Yonsei University 25
Base power ?
How to fix the 𝑷↓𝒄𝒑𝒖 ?
Acave cores Frequency
Ualiza
aon
TRX packets
Colors/Brightness
Power of component 𝐶
Device Power Model: Example
Mobile Embedded System Lab., Yonsei University 26
Power Analysis
Conven8onal Power Measurement
Mobile Embedded System Lab., Yonsei University 28
External Power Monitor
Job 1
Job 2
Job 3
triggering?
frequency?
acave core? temperature?
base?
governor?
Job 1
Job 2
Job 3
Nonintrusive Power Measurement (1)
Fuel-gauge IC
DevScope
Component Controller
TimingController
Fuel-‐gauge IC Event
Monitor
Power Model
Generator
H/W Components
…CPU Display Wi-‐Fi Cellular GPS
Battery
Component Power Model • Power modeling process – Component-‐specific training set
generaaon • Workload, Control scenario
– Probe OS, H/W component – Monitor fuel-‐gauge IC
• Concepts – Use built-‐in fuel-‐gauge IC – Assume specific H/W power
model – Online and non-‐intrusive power
modeling
Mobile Embedded System Lab., Yonsei University 29
Nonintrusive Power Measurement (2)
• Badery Monitoring Unit (BMU, BMIC, Fuel-‐gauge IC, SBS, …) – Internal measurement device for supply voltage, baWery capacity, discharge
current, temperature, ...
• BMIC types
• Example: Maxim DS2784 (HTC Nexus One) – Measuring voltage, current, and temperature – Current sensing
• Resoluaon: 104uA • Sensing range: -‐3430mA ~ 3430mA (±1%) • Sampling rate: 18.6KHz / Update rate: 0.28Hz
BaWery Monitoring Unit (Maxim DS2784)
Type Current + voltage Voltage only
IC Maxim DS2760, Maxim DS278X, TI UCC3926, …
Ti BQ27X00, WM97XX, …
Model Sony-Ericsson Xperia Series, HTC NexusOne/Desire Series, Samsung Galaxy S3/S4(?)
Samsung Galaxy Series, LG Optimus Series(?), …
Mobile Embedded System Lab., Yonsei University 30
Nonintrusive Power Measurement (3)
Hardware
Android
DevScope
System Configura8on
-‐ CPU frequencies -‐ BMU types -‐ Hardware component types -‐ Network se|ngs
Android API
-‐ CPU control -‐ 3G/LTE/WiFi networking -‐ Display control -‐ GPS control
Component Power Models
-‐ CPU: 𝑝= 𝛽↓𝑓𝑟𝑒𝑞 ×𝑢
-‐ WiFi: 𝑝= 𝛽↓𝑇𝑋 ×𝑝𝑝𝑠+ 𝛽↓𝑖𝑑𝑙𝑒 -‐ 3G/GPS: 𝑝= 𝛽↓𝑝𝑜𝑤𝑒𝑟_𝑠𝑡𝑎𝑡𝑒 -‐ LCD: 𝑝= 𝛽↓𝑏𝑟𝑖𝑔ℎ𝑡𝑛𝑒𝑠𝑠
BMU Report
Measurement Data
Ini8aliza8on
Workload Genera8on
BMU Ac8vity
Reporang Rate
Workload Tuning
& Probing Power behavior analysis
Coefficient Values CPU LCD WiFi 3G GPS
245 368 238 268 0
998 854 247 519 354
Hardware Components CPU LCD WiFi Cellular GPS
BMU
Mobile Embedded System Lab., Yonsei University 31
U8liza8on
Hardware component usage
Applica8on Energy Es8ma8on (1)
𝐸↑𝐴𝑝𝑝 =∑𝑖=0↑#𝑜𝑓𝐶𝑜𝑚𝑝▒(𝛽↓𝑖 × 𝑥↓𝑖↑𝐴𝑝𝑝 )× 𝑑↓𝑖↑𝐴𝑝𝑝
𝑥↓𝑖↑𝐴𝑝𝑝
𝑑↓𝑖↑𝐴𝑝𝑝
𝛽↓𝑖↑ Power coefficient value
Utilization
Activated duration Limitations Accuracy/Granularity/Real-‐time
• Conven8onal methods – HPC (hardware performance counter) – Linux “procfs/sysfs” – Android “BaYeryStats” – Basically “polling”
• Problems – Dependency on processor – Update rate problem – Granularity problem (per-‐process info)
Mobile Embedded System Lab., Yonsei University 33
Challenges: how to estimate application’s energy consumption?
Applica8on Energy Es8ma8on (2)
• How to detect hardware component opera8on? – Event-‐driven kernel acavity monitoring
t
Event of component opera8on
Dura8on/U8liza8on of opera8on
Mobile Embedded System Lab., Yonsei University 34
Applica8on Energy Es8ma8on (3)
Estimation Result
Event DetectorApplication KernelAndroidprocess 1
process 2
process n
...
binder
c/c++ libraries
H/W drivers
binderdriver
Android API call
Binder IPC data
Request to use H/W by system call
Kernel Activity Monitoring
binder_ioctl(), ioctl(), socket(), read(), write(), ...
1
Hardware Component Usage Analyzer
2Application Energy Estimator
3
Energy Consumption
…CPU Display Wi-Fi Cellular GPS
Component Power Models
Fuel-gaugeIC
External Devices
Device power model
𝑖
Mobile Embedded System Lab., Yonsei University 35
Event detector
• binder_ioctl() • binder_transacRon() • cpufreq_cpu_put() • sched_switch() • dev_queue_xmit() • neRf_rx() • …
Kernel path
Hooking Point
Probe Handler
0x81808c144
End
Instrumentaaon rouane
Return to original path����������� ������������������
Hardware Component Usage Analyzer
• CPU frequency/ualizaaon • WiFi transmission packet r
ate • LCD display duraaon • GPS acavated duraaon • 3G network connecaon ty
pe • …
• System calls • Kernel funcaons • Binder calls
Component Usage Monitoring (1)
Mobile Embedded System Lab., Yonsei University 36
“Kprobes”
INT03:Break����������� ������������������
Component Usage Monitoring (2)
Pac
ket
trans
mitt
ing
dev_queue_xmit()/netif_rx()
Time(s)
Time (tick)
Event Detector Kernel function calls
cpufreq_cpu_put()
245.0 MHz614.4 MHz806.4 MHz998.4 MHz
sched_switch()
Freq
uenc
ych
angi
ng
Pro
cess
switc
hing
Time (tick)Timing synchronization
Utilization (%)
AppScopeKernel
Process 1
Process 2
Process 3
H/W ComponentUsage Analyzer
Mobile Embedded System Lab., Yonsei University 37
Component Usage Monitoring (3)
• Display (OLED) – (R, G, B) and brightness
– Accurate OLED energy esamaaon by Framebuffer Analysis
– Event-‐based acavity transiaon monitoring • Applicaaon-‐specific
display power esamaaon
𝑃=𝐵𝑟×𝑓(𝑅,𝐺,𝐵) ×(𝛽↓𝑅 𝑅↓𝑖 + 𝛽↓𝐺
𝐺↓𝑖 + 𝛽↓𝐵 𝐵↓𝑖 )
Mobile Embedded System Lab., Yonsei University 38
Applica8on Energy Es8ma8on: Overall Framework
Device Power Modeling (Training)
Energy Es8ma8on System Evalua8on
Mobile Embedded System Lab., Yonsei University 39
Kernel source Behavior analysis Power Analysis Formulaaon
Error Analysis External Power Monitor
AppScope
The AppScope Project (1)
Power Models (DevScope/Vendor)
AppScopeViewer
App. Developer System Sooware Developer
Energy Bug Report / Energy Consump8on Sta8s8cs
End User
AppScopeViewer I/F
AppScope
CPU Display Wi-‐Fi Cell GPS
Simple On/Off States
Component X
Applica8ons
AppScope Library Single Core LCD OLED USPA LTE Mul8 Core …
C. Yoon, D. Kim, W. Jung, C. Kang, H. Cha, "'AppScope: Applicaaon Energy Metering Framework for Android Smartphone using Kernel Acavity Monitoring," USENIX Annual Technical Conference (USENIX ATC'12), 2012
W. Jung, C. Kang, C. Yoon, D. Kim, H. Cha, "DevScope: A Nonintrusive and Online Power Analysis Tool for Smartphone Hardware Components," InternaRonal Conference on Hardware/So_ware Codesign and System Synthesis (CODES+ISSS'12), 2012
Mobile Embedded System Lab., Yonsei University 41
Demo (AppScope/AppScopeViewer)
Mobile Embedded System Lab., Yonsei University 42
hdp://mobed.yonsei.ac.kr/appscope
Current Status of AppScope
Mobile Embedded System Lab., Yonsei University 43
Snapdragon QSD8250(1GHz)
Exynos-‐5410
Media processor(MFC) SGX 544 GPU 1.6GHz Octa. big.LITTLE
Media processor
Snapdragon 600
1.9GHz Quad.
Adreno 320 GPU 1.4GHz Quad.
2D graphics
Mali-‐400 GPU
Exynos-‐4412 3G
SKT HSDPA
WiFi
GPS
3G HSPA+
Tail Power 4G LTE
Camera
Galaxy S3
Galaxy S4 Nexus One
VEGA IRON
AMOLED Display LCD Display
AppScope Remaining Challenges
Mobile Embedded System Lab., Yonsei University 44
Autonomous power modeling
Thermal power modeling More components
Signal-‐strength-‐aware modeling
Sensors Touch screen Bluetooth NFC …
WiFi
4G LTE
3G HSPA+
AppScope Capabili8es & Poten8als
Energy Bugs/Hogs Detec8on
• User behavior monitoring • Anomaly detecaon • Debugging frameworks
Energy Mgmt.
• Energy management API • BaWery virtualizaaon • Remain capacity predicaon
• Workload characterizaaon • Load monitoring • Detecang workload unbalance
Program bugs Wakelock Handover
Signal strength
• CPU power governor • DEVFREQ (OPP) • Mula-‐core task scheduling
Power Mgmt.
big.LITTLE
GPU
MFC
Multicore
Task scheduling
100%
30%
30%
40%
• Interacave UX • Lifeame predicaon • App. running state analysis
Energy-‐aware UX
Workload Analysis
Mobile Embedded System Lab., Yonsei University 45
Our Researches
Work @ Yonsei
• Energy usage profiling • Energy habit monitoring • Energy bugs/hogs detecaon • EMSOFT2013, …
• Component usage monitoring • Applicaaon energy esamaaon • System energy esamaaon • USENIX ATC’12
• Component power modeling • Mula-‐core CPU, GPU, OLED, … • Online power modeling • CODES+ISSS2012, DATE2013
AppScope
Network Env.
User Interac8on
Network Serv.
Badery State
Calling Serv.
…
…
UserScope WakeScope …
CPU Display Wi-Fi Cellular GPS
Power Management
• Mula-‐core CPU governor • DEVFREQ frameworks • Personalized energy mgnt. • Adapave duty cycling • SenSys’11, ... Fuel-gauge IC
H/W Components
…CPU Display Wi-‐Fi Cellular GPS
BatteryDevScope
Base
p
3R 4R
Hidden State1Active State
Hidden State2
HiddenState 1
Active State
Hidden State 2
Mobile Embedded System Lab., Yonsei University 47
FIN
hWp://mobed.yonsei.ac.kr/
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