The document discusses current and future trends in Android power management. It summarizes the Android power management architecture, including wake locks and power drivers. It also reviews present research on power consumption analysis and management, such as reducing power usage from connectivity features like Wi-Fi and GPS. The document surveys existing power saving Android apps and their limitations. It proposes future directions for more intelligent power management apps using monitoring and learning techniques while addressing privacy and security concerns.
Understanding, debugging and fixing power bugslittleeye
The talk covers how to understand and debug your app's power consumption and covers optimization techniques that can be used to create efficient apps, that customers love!
How to Lower Android Power Consumption Without Affecting Performancerickschwar
Most mobile apps waste power because they do not manage the processor, cellular radio and Wi-Fi network properly. Excess power consumption can lead to bad reviews and poor ratings. This session will teach you how to determine whether your app consumes too much power. You'll also learn how to resolve the most common power-related problems.
Make sure to watch the video that goes along with these slides. You can view it here: https://www.parleys.com/tutorial/how-lower-power-consumption-your-app-without-affecting-performance
Topics Discussed
• Why mobile power consumption has increased so much
• What are the top 5 power-related problems?
• How to determine how much power your app consumes when it’s idle and active
• How do you know if an app consumes too much power?
• How to quickly test an app’s performance in 25 key areas
• How to pinpoint the causes of power spikes in your code
• Why it's so important to manage the cellular radio effectively
• How to power and performance profile your app without leaving your IDE
• Using software to determine whether you are managing the cellular radio properly
• Best Practices for connectivity, performance and power measurement
• How much power can you save when your port code to run on a DSP?
• How to get early access to development smartphone and tablets with next generation mobile processors up to 6 months before they appear in commercial devices
• How to see where the power is going by measuring individual rails including CPU, GPU, display, memory, Wi-Fi, sensors and more
• An introduction to automated power testing and more.
About the Author
Rick is a senior product manager at Qualcomm. His team creates next-gen smartphones and tablets that are made available to software developers. He also manages Qualcomm’s power and performance profiling software.
#DV15 #BatteryOptimization #Android #perfmatters @mostlytech1
Samsung Developer's Conference - Maximize App Performance while Minimizing Ba...rickschwar
Trepn Profiler was recently showcased at the Samsung Developer's Conference in a session titled:
Maximize App Performance while Minimizing Battery Drain
You can view the full video of this event here: https://www.youtube.com/watch?v=SR_1WGD88Pw
Here is the outline of the entire session:
· 0:00:00 – Agenda – Rick Schwartz
· 0:01:32 – The challenge – Mobile trends
· 0:04:50 – Does your app consume too much power?
· 0:10:48 – Software power measurement Best Practices
· 0:14:17 – Demo: Using Trepn to profile your mobile processor
· 0:27:06 – Per-rail power measurements
· 0:30:48 – Demo: Power profiling in Eclipse
· 0:50:10 – How to efficiently use your cellular radio
· 0:54:50 – Trepn Profiler Deep dive – Eugene Kolinko
· 0:55:24 – How to insert markers in your code to identify power spikes
· 1:00:44 – How to: perform automated testing with Trepn Profiler
· 1:14:34 – Common causes of excessive power consumption – Rick Schwartz
· 1:21:44 – Recap of power saving tips
· 1:24:47 – Qualcomm Snapdragon Performance Visualizer overview – Kevin Sapp
· 1:29:59 – What can Snapdragon Performance Visualizer do?
· 1:35:25 – Live View demo
· 1:40:29 – Adding Custom Data to Snapdragon Performance Visualizer
· 1:47:42 – Statistical profiling with Snapdragon Performance Visualizer (OProfile)
· 1:50:44 – Tracing with Snapdragon Performance Visualizer
· 1:52:11 – Profile View demo
· 2:03:40 – Qualcomm Embedded Power Monitor demo
· 2:12:30 – Graphics and gaming overview – Manish Sirdeshmukh
· 2:27:08 – OpenGL ES optimizations - Dave Astle
· 2:33:53 – Adreno software tool and SDK overview – Manish Sirdeshmukh
· 2:38:04 – Adreno profile demo - Dave Astle
This PPT presentation will explain you how you can reduce the battery optimization for Android Phones. It show you step by step process to reduce consumption of battery while using your application
Even though android is powerful mobile operating system platform still there are few pitfalls. One of them is memory optimization to ensure user never run out of space and do you know how to do it.
iOS application put unnecessary burden on battery of iPhone. Optimizing it for minimum burden on device battery life is necessary for smooth user experience
Understanding, debugging and fixing power bugslittleeye
The talk covers how to understand and debug your app's power consumption and covers optimization techniques that can be used to create efficient apps, that customers love!
How to Lower Android Power Consumption Without Affecting Performancerickschwar
Most mobile apps waste power because they do not manage the processor, cellular radio and Wi-Fi network properly. Excess power consumption can lead to bad reviews and poor ratings. This session will teach you how to determine whether your app consumes too much power. You'll also learn how to resolve the most common power-related problems.
Make sure to watch the video that goes along with these slides. You can view it here: https://www.parleys.com/tutorial/how-lower-power-consumption-your-app-without-affecting-performance
Topics Discussed
• Why mobile power consumption has increased so much
• What are the top 5 power-related problems?
• How to determine how much power your app consumes when it’s idle and active
• How do you know if an app consumes too much power?
• How to quickly test an app’s performance in 25 key areas
• How to pinpoint the causes of power spikes in your code
• Why it's so important to manage the cellular radio effectively
• How to power and performance profile your app without leaving your IDE
• Using software to determine whether you are managing the cellular radio properly
• Best Practices for connectivity, performance and power measurement
• How much power can you save when your port code to run on a DSP?
• How to get early access to development smartphone and tablets with next generation mobile processors up to 6 months before they appear in commercial devices
• How to see where the power is going by measuring individual rails including CPU, GPU, display, memory, Wi-Fi, sensors and more
• An introduction to automated power testing and more.
About the Author
Rick is a senior product manager at Qualcomm. His team creates next-gen smartphones and tablets that are made available to software developers. He also manages Qualcomm’s power and performance profiling software.
#DV15 #BatteryOptimization #Android #perfmatters @mostlytech1
Samsung Developer's Conference - Maximize App Performance while Minimizing Ba...rickschwar
Trepn Profiler was recently showcased at the Samsung Developer's Conference in a session titled:
Maximize App Performance while Minimizing Battery Drain
You can view the full video of this event here: https://www.youtube.com/watch?v=SR_1WGD88Pw
Here is the outline of the entire session:
· 0:00:00 – Agenda – Rick Schwartz
· 0:01:32 – The challenge – Mobile trends
· 0:04:50 – Does your app consume too much power?
· 0:10:48 – Software power measurement Best Practices
· 0:14:17 – Demo: Using Trepn to profile your mobile processor
· 0:27:06 – Per-rail power measurements
· 0:30:48 – Demo: Power profiling in Eclipse
· 0:50:10 – How to efficiently use your cellular radio
· 0:54:50 – Trepn Profiler Deep dive – Eugene Kolinko
· 0:55:24 – How to insert markers in your code to identify power spikes
· 1:00:44 – How to: perform automated testing with Trepn Profiler
· 1:14:34 – Common causes of excessive power consumption – Rick Schwartz
· 1:21:44 – Recap of power saving tips
· 1:24:47 – Qualcomm Snapdragon Performance Visualizer overview – Kevin Sapp
· 1:29:59 – What can Snapdragon Performance Visualizer do?
· 1:35:25 – Live View demo
· 1:40:29 – Adding Custom Data to Snapdragon Performance Visualizer
· 1:47:42 – Statistical profiling with Snapdragon Performance Visualizer (OProfile)
· 1:50:44 – Tracing with Snapdragon Performance Visualizer
· 1:52:11 – Profile View demo
· 2:03:40 – Qualcomm Embedded Power Monitor demo
· 2:12:30 – Graphics and gaming overview – Manish Sirdeshmukh
· 2:27:08 – OpenGL ES optimizations - Dave Astle
· 2:33:53 – Adreno software tool and SDK overview – Manish Sirdeshmukh
· 2:38:04 – Adreno profile demo - Dave Astle
This PPT presentation will explain you how you can reduce the battery optimization for Android Phones. It show you step by step process to reduce consumption of battery while using your application
Even though android is powerful mobile operating system platform still there are few pitfalls. One of them is memory optimization to ensure user never run out of space and do you know how to do it.
iOS application put unnecessary burden on battery of iPhone. Optimizing it for minimum burden on device battery life is necessary for smooth user experience
Faststream Technologies’s Driver Monitoring System, using a single low-power in-vehicle camera and advanced vision technologies, provides reliable detection of driver drowsiness and distraction, alerting the driver to reduce the chances of serious accidents and thus providing a safer and comfortable drive. Our solution is offered to OEMs and Tier1s for pre-installment into their cars and trucks.
When a driver doesn’t get proper rest, they fall asleep while driving and this leads to fatal accidents. This particular issue demands a solution in the form of a system that is capable of detecting drowsiness and to take necessary actions to avoid accidents.
The detection is achieved with three main steps, it begins with face detection and facial feature detection using the famous Viola Jones algorithm followed by eye tracking. By the use of correlation coefficient template matching, the eyes are tracked. Whether the driver is awake or asleep is identified by matching the extracted eye image with the externally fed template (open eyes and closed eyes) based on eyes opening and eyes closing, blinking is recognized. If the driver falling asleep state remains above a specific time (the threshold time) the vehicles stops and an alarm is activated by the use of a specific microcontroller, in this prototype an Arduino is used.
Drowsiness is a critical factor impairing drivers’ performance in driving safely. There are several approaches in dealing with this issue based on human-machine interaction to detect drivers’ dozing off state, and then alert them to keep awake by sound or visual. These techniques fundamentally measure driver’s physical changes such as head angle, fatigue level and eyes states which are the indicators of drowsy state. However, they are limited in providing accurate and reliable results. Therefore, the project aims to achieve higher accuracy rate of drowsiness detection by using a very potential technology, electroencephalography (EEG) which is used widely in medical areas. Other than providing reliable result, the final product would bring more conveniences for customers with portability, easy-to-deploy and multi-device compatibility feature. In this project, its methodology first shows the strong correlation between drowsy state with brainwave frequency. Then a proposed system and testing plan are suggested based on the project objectives and available technologies. The final product is simply comprised of a hat with attached small electronic package used to record brainwave and a handheld device placing on dashboard of the car with an installed app. Finally, project management section will present in detail the human resources, scheduling, budget plan and risk analysis to show how it will be going to complete the project in six months.
Real Time Eye Blinking and Yawning Detectionijtsrd
Detecting eye blink and yawning is important, for example in systems that monitor the vigilance of the human operator, eg Driver's drowsiness. Driver fatigue is one of the leading causes of the worlds deadliest road accidents. This shows that in the transport sector in particular, where a driver of heavy vehicles is often open to hours of monotonous driving which causes fatigue without frequent rest periods. It is therefore essential to design a road accident prevention system that can detect the drivers drowsiness, determine the drivers level of carelessness and warn when an imminent danger occurs. In this article, we propose a real time system that uses eye detection techniques, blinking and yawning. The system is designed as a non intrusive real time monitoring system. The priority is to improve driver safety without being intrusive. In this work, the blink of an eye and the drivers yawn are detected. If the drivers eyes remain closed for more than a certain time and the drivers mouth is open to yawning, the driver is said to be fatigue. Ohnmar Win "Real Time Eye Blinking and Yawning Detection" Published in International Journal of Trend in Scientific Research and Development (ijtsrd), ISSN: 2456-6470, Volume-3 | Issue-5 , August 2019, URL: https://www.ijtsrd.com/papers/ijtsrd28004.pdfPaper URL: https://www.ijtsrd.com/engineering/electrical-engineering/28004/real-time-eye-blinking-and-yawning-detection/ohnmar-win
Driver drowsiness detection is a car safety technology which helps prevent accidents caused by the driver getting drowsy. Various studies have suggested that around 20% of all road accidents are fatigue-related, up to 50% on certain roads
Vision based system for monitoring the loss of attention in automotive driverVinay Diddi
This is a real time driver drowsiness detection system is used to alert the driver when he is drowsy. It consist of raspberry pi and OpenCV image processing library.
Power Management from Linux Kernel to
Android
For normal desktop computer, power management (PM) is used to reduce power
consumption and reduce cooling requirements. Lower power consumption means
lower heat dissipation, which increases system stability, and less energy use, which
saves money and reduces the impact on the environment. For mobile device and
embedded system device, it’s much more important because the battery power is very
limited. Nowadays, android phone and iPhone are more and more pervasive. There
are more and more sensors and I/O in mobile device that can be used to improve the
effectiveness of PM. The PM needs to be tuned for new mobile device’s need. In this
survey, we want to not only know the power management system used before, but
also want to compare them with the design of Android PM.
Presented by Brian Gupta (brian.gupta@brandorr.com) and Nathan Freitas (nathan@olivercoady.com)
Learn more at http://tinyurl.com/androidfaq
Android is a fully integrated and open source bundle of software significantly lowers the current costs of developing mobile devices (currently runs on a cellphone (the HTC Dream/T-Mobile G1), and a number of unofficial "ports". It consists of an operating system, middleware, a user-friendly interface and powerful applications.
The talk will start with a review of the internal architecture of the Android platform, breaking down the various components, and examine how they work. Then we will review the latest status of the open source project, including how to get and build the source code, and how to get involved.
Faststream Technologies’s Driver Monitoring System, using a single low-power in-vehicle camera and advanced vision technologies, provides reliable detection of driver drowsiness and distraction, alerting the driver to reduce the chances of serious accidents and thus providing a safer and comfortable drive. Our solution is offered to OEMs and Tier1s for pre-installment into their cars and trucks.
When a driver doesn’t get proper rest, they fall asleep while driving and this leads to fatal accidents. This particular issue demands a solution in the form of a system that is capable of detecting drowsiness and to take necessary actions to avoid accidents.
The detection is achieved with three main steps, it begins with face detection and facial feature detection using the famous Viola Jones algorithm followed by eye tracking. By the use of correlation coefficient template matching, the eyes are tracked. Whether the driver is awake or asleep is identified by matching the extracted eye image with the externally fed template (open eyes and closed eyes) based on eyes opening and eyes closing, blinking is recognized. If the driver falling asleep state remains above a specific time (the threshold time) the vehicles stops and an alarm is activated by the use of a specific microcontroller, in this prototype an Arduino is used.
Drowsiness is a critical factor impairing drivers’ performance in driving safely. There are several approaches in dealing with this issue based on human-machine interaction to detect drivers’ dozing off state, and then alert them to keep awake by sound or visual. These techniques fundamentally measure driver’s physical changes such as head angle, fatigue level and eyes states which are the indicators of drowsy state. However, they are limited in providing accurate and reliable results. Therefore, the project aims to achieve higher accuracy rate of drowsiness detection by using a very potential technology, electroencephalography (EEG) which is used widely in medical areas. Other than providing reliable result, the final product would bring more conveniences for customers with portability, easy-to-deploy and multi-device compatibility feature. In this project, its methodology first shows the strong correlation between drowsy state with brainwave frequency. Then a proposed system and testing plan are suggested based on the project objectives and available technologies. The final product is simply comprised of a hat with attached small electronic package used to record brainwave and a handheld device placing on dashboard of the car with an installed app. Finally, project management section will present in detail the human resources, scheduling, budget plan and risk analysis to show how it will be going to complete the project in six months.
Real Time Eye Blinking and Yawning Detectionijtsrd
Detecting eye blink and yawning is important, for example in systems that monitor the vigilance of the human operator, eg Driver's drowsiness. Driver fatigue is one of the leading causes of the worlds deadliest road accidents. This shows that in the transport sector in particular, where a driver of heavy vehicles is often open to hours of monotonous driving which causes fatigue without frequent rest periods. It is therefore essential to design a road accident prevention system that can detect the drivers drowsiness, determine the drivers level of carelessness and warn when an imminent danger occurs. In this article, we propose a real time system that uses eye detection techniques, blinking and yawning. The system is designed as a non intrusive real time monitoring system. The priority is to improve driver safety without being intrusive. In this work, the blink of an eye and the drivers yawn are detected. If the drivers eyes remain closed for more than a certain time and the drivers mouth is open to yawning, the driver is said to be fatigue. Ohnmar Win "Real Time Eye Blinking and Yawning Detection" Published in International Journal of Trend in Scientific Research and Development (ijtsrd), ISSN: 2456-6470, Volume-3 | Issue-5 , August 2019, URL: https://www.ijtsrd.com/papers/ijtsrd28004.pdfPaper URL: https://www.ijtsrd.com/engineering/electrical-engineering/28004/real-time-eye-blinking-and-yawning-detection/ohnmar-win
Driver drowsiness detection is a car safety technology which helps prevent accidents caused by the driver getting drowsy. Various studies have suggested that around 20% of all road accidents are fatigue-related, up to 50% on certain roads
Vision based system for monitoring the loss of attention in automotive driverVinay Diddi
This is a real time driver drowsiness detection system is used to alert the driver when he is drowsy. It consist of raspberry pi and OpenCV image processing library.
Power Management from Linux Kernel to
Android
For normal desktop computer, power management (PM) is used to reduce power
consumption and reduce cooling requirements. Lower power consumption means
lower heat dissipation, which increases system stability, and less energy use, which
saves money and reduces the impact on the environment. For mobile device and
embedded system device, it’s much more important because the battery power is very
limited. Nowadays, android phone and iPhone are more and more pervasive. There
are more and more sensors and I/O in mobile device that can be used to improve the
effectiveness of PM. The PM needs to be tuned for new mobile device’s need. In this
survey, we want to not only know the power management system used before, but
also want to compare them with the design of Android PM.
Presented by Brian Gupta (brian.gupta@brandorr.com) and Nathan Freitas (nathan@olivercoady.com)
Learn more at http://tinyurl.com/androidfaq
Android is a fully integrated and open source bundle of software significantly lowers the current costs of developing mobile devices (currently runs on a cellphone (the HTC Dream/T-Mobile G1), and a number of unofficial "ports". It consists of an operating system, middleware, a user-friendly interface and powerful applications.
The talk will start with a review of the internal architecture of the Android platform, breaking down the various components, and examine how they work. Then we will review the latest status of the open source project, including how to get and build the source code, and how to get involved.
Android Accessibility - The missing manualTed Drake
Android provides great accessibility support, but finding that information can sometimes be difficult to impossible. This presentation gathers some hard to find information on Android Accessibility and gives additional links to resources for making your application accessible.
Please visit the accessible version of this presentation for slide details: http://www.last-child.com/android-a11y-missing-manual/
Introduces Mobile Operating Systems and goes deeply on Android OS presenting the different layers, developing basics and boot process. Also presents some hardware related topics.
Why Smart Meters Need Informix TimeSeriesIBM Sverige
Informix Update - Denna presentation hölls på IBM Data Server Day den 22 maj i Stockholm av Simon David, Technical Product Manager, Competitive Technologies & Enablement, Informix Development
Data center and industrial IT infrastructure monitoring practicesTibbo
AggreGate Platform solves all typical tasks of data center and industrial IT infrastructure monitoring, provides fault and performance control, configuration management, monitoring networks, servers, applications, DBMS, virtualized environment, telephony, and more.
Developing Multi-Agent Based Micro-Grid Management System in JADEVimukkthi Vithanage
This paper presents an implementation of a MultiAgent based Energy Management System for a micro grid with JADE (Java Agent Development Framework). The MAS is applied for a micro grid consisting of different distributed energy sources such as solar PV system, wind power system, diesel generator system, storage system, and critical and noncritical loads. Different agents are developed on JADE framework and they are given responsibilities of relevant DES’s (Distributed Energy Source) and loads. A runtime environment for Agents are created and a dynamic simulation model developed through JADE considering the intermittent qualities of renewable energy sources. The case studies presented on this paper are modeled on JADE platform. Developing MAS in JADE runtime environment using AOP (Agent-Oriented Programming) helps agents to operate with all their autonomous, rational, reactive, and proactive qualities. The use of MAS concept in micro grids improves its efficiency in various aspects. The MAS based micro grid management system implemented in JADE platform and can be used to carry out various simulations to study about agent behaviors in different environments and different system objectives. The main purpose of the paper is to prove the possibility of using multiagent concept in micro grid energy management systems.
For more information : https://www.researchgate.net/publication/339981129_Developing_Multi-Agent_Based_Micro-Grid_Management_System_in_JADE
Course Overview
Smart Meters and Smart Meter Systems are being deployed throughout the world, and utilities are continuing their efforts to improve grid reliability and promote energy efficiency while providing improved services to their customers.
This training will build skills on the required actions for Smart Meter deployment, adaptation and the role that Utility
plays in tackling solving energy cost, integrating renewables and energy efficiency issues. It will explain the underlying
concepts and the role that a wide range of stakeholders can play in developing the business case, policies, technologies
and standards that will improve energy efficiency and reduce future cost of energy through a range of Smart Meter
technologies with a focus on benefits for all stakeholders, and how to achieve success. Participants will benefit from
learning “Regulator Ready” business case from around the world. Participants will also receive a working version of the
business case in Microsoft Excel.
Learning Outcome
1. How to get the stakeholders involved
2. Organic relationships between AMI and Smart Grid
3. Emerging concepts in Smart Meters
4. Emerging technology options in Smart Meter deployment
5. Security Layers for AMI
6. Applications of Smart Meters and Energy Efficiency
7. How to develop detailed cost / benefit analysis
8. Explore solutions that are offered by smart metering technologies
9. Challenges in switching over to smart meters
10. Advanced metering infrastructure & Meter Data Management
11. Benefits to Consumer, Regulators and the Utilities
12. How to minimize Energy Theft
13. International Case studies
Kent Melville and Annie Wise from Inductive Automation, and water/wastewater controls professionals Henry Palechek and Jason Hamlin, cover 10 steps for building a sustainable SCADA system that survives and even thrives using only your operational expenditure budget.
You'll learn about:
• What type of hardware and operating systems to use
• Utilizing smart devices and MQTT
• The advantages of server-centric architecture and web-based deployment
• Rapid development with templates and UDTs
• Powerful alarming and reporting tools
• And more
Home automation using IoT literature review pptTanujkumar101
This ppt has covered through 5 research paper (1 base paper + 4 research paper) .there each paper have its marit and demerits . first paper based on raspberry Pi , second one is on Arduino, third one is on esp8266 and forth one on PLC and conclusion have comparison part .
Kent Melville and Annie Wise from Inductive Automation, and water/wastewater controls professionals Henry Palechek and Jason Hamlin, cover 10 steps for building a sustainable SCADA system that survives and even thrives using only your operational expenditure budget.
You'll learn about:
• What type of hardware and operating systems to use
• Utilizing smart devices and MQTT
• The advantages of server-centric architecture and web-based deployment
• Rapid development with templates and UDTs
• Powerful alarming and reporting tools
• And more
Similar to Android power management, current and future trends (20)
2. Projet : « Smart 4G Tablet»
LPCIM : Laboratoire de Physique des
Interfaces et des Couches Minces
3. Contents
• Introduction
• Android power management architecture
• Present research on power consumption &
management
• Survey on power saving Android apps
• Future directions
• Privacy & security concerns
• Conclusion
18/06/2012 ETSIoT 2012, Seoul 3
4. Introduction
• Smart device features that consume power
– CPU, Wi-Fi, GPS, colorful bright display, 3G, auto
sync, Bluetooth etc.
– third party advertisements shown in free Android
apps
• Many power saving apps written
– control Wi-Fi, 2G and 3G connections, brightness
level, CPU frequency, GPS etc.
18/06/2012 ETSIoT 2012, Seoul 4
5. Contents
• Introduction
• Android power management architecture
• Present research on power consumption &
management
• Survey on power saving Android apps
• Future directions
• Privacy & security concerns
• Conclusion
18/06/2012 ETSIoT 2012, Seoul 5
6. Android Power Management
• Power driver addition to Linux kernel.
• Wake Locks
– It prevents the system from entering suspend or other
low-power states.
– Android apps are required to request CPU resources
with wake locks.
18/06/2012 ETSIoT 2012, Seoul 6
8. Contents
• Introduction
• Android power management architecture
• Present research on power consumption &
management
• Survey on power saving Android apps
• Future directions
• Privacy & security concerns
• Conclusion
18/06/2012 ETSIoT 2012, Seoul 8
9. Power consumption of connectivity
features
• Reducing power dissipation in Wi-Fi, 3G/4G,
GPS
• Location Based Apps (LBA)
– Social networking, weather, traffic, ad etc.
– Adaptive location sensing framework
18/06/2012 ETSIoT 2012, Seoul 9
10. Context Aware PM
• Employs several monitoring system to extract
contexts (CABMAN)
– Location
– Battery
– Process
– Call
• Can predict the next charging opportunity
18/06/2012 ETSIoT 2012, Seoul 10
11. Power Model Generation
• PowerBooter technique & PowerTutor app is
introduced in [].
• Monitoring & recording battery consumption.
• Each hardware element has several states and
power consumption depends on the states.
• Power consumption is correlated with the
hardware elements of the smartphones.
18/06/2012 ETSIoT 2012, Seoul 11
12. Other Approaches on PM
• Analysis using smartphone usage pattern
– An Android app ‘battery logger’ is used to collect
usage pattern and send it to a server.
• Internal energy consumption of apps
• Human Battery Interaction
18/06/2012 ETSIoT 2012, Seoul 12
13. Contents
• Introduction
• Android power management architecture
• Present research on power consumption &
management
• Survey on power saving Android apps
• Future directions
• Privacy & security concerns
• Conclusion
18/06/2012 ETSIoT 2012, Seoul 13
14. Approach for power saving
Primary Approach Secondary Approach App Example
CPU frequency
scaling
Toggling other
features
Setcpu, cputuner
Control
smartphone
features
CPU frequency
optimization
Juice defencder,
extended control
and more
18/06/2012 ETSIoT 2012, Seoul 14
15. Increasing power efficiency
• Toggle control on Wi-Fi, Bluetooth, GPS, auto sync,
airplane mode, auto screen lock, USB mass storage,
screen-always-on, torch, 2G, 3G, 4G/Wimax (if present)
and mobile data (APN).
• Change brightness level of display.
• Volume and vibration control.
• Alter screen timeout value.
• Scheduling – night, weekend, peak.
• Setting Wi-Fi timeout.
• Setting dark home screen wallpaper for OLED display.
18/06/2012 ETSIoT 2012, Seoul 15
16. Root Access
Select CPU Governor
Advanced
Options
Condition Monitor
Appropriate
Profile
System Info
Battery Monitor
Priorit
y
Smartphone features
are controlled
Required for CPU
freq. scaling
Ondemand
Conservativ
e
interactive
Advanced
Monitoring
Single condition
Several conditions
Primary focus is CPU
freq. scaling
Example: setcpu
Overall Architecture for CPU frequency
scaling approaches
18/06/2012 ETSIoT 2012, Seoul 16
17. Condition
Monitor
Appropriate
Profile
System Info
Battery Monitor
Smartphone features
are controlled
Context Monitor
Decision
Location
Time
Battery
LevelPhone Idle
Triggers
1. Predefined
2. Customized by user
Toggle connectivity
Keep on some apps
CPU freq. scaling is
secondary focus
Example:
Juicedefender
Not used for any
learning
Overall Architecture for Control
Smartphone Features Approaches
18/06/2012 ETSIoT 2012, Seoul 17
18. Limitations of studied apps
• Static profiling (one customizable profile)
– Not customized for specific user
• “Controlling” – not intelligent
• Requirement for root access
– For CPU freq. scaling
• No focus on power consumption pattern (except power
tutor)
• Context information is not used for any learning purpose
• Do not focus on learning the power consumption pattern of
users.
• In-app advertising: waste of energy
18/06/2012 ETSIoT 2012, Seoul 18
19. Contents
• Introduction
• Android power management architecture
• Present research on power consumption &
management
• Survey on power saving Android apps
• Future directions
• Privacy & security concerns
• Conclusion
18/06/2012 ETSIoT 2012, Seoul 19
20. Apps for Power Management
• Monitoring subsystem
– Extracts several
information like
location, date & time,
battery discharge
behavior, apps running
[usage pattern]
• Controlling subsystem
– Control
smartphone/tablet
features based on
usage pattern
18/06/2012 ETSIoT 2012, Seoul 20
• Two types of
architectures
• Client server
• Learning engine
22. Advantages of Client Server
Architecture
• Generation of smartphone usage pattern
• The context in which most power is spent
• Clustering similar usage pattern at the server
– Derive power saving profiles based on clusters
• Evolution of clusters
• Network usage pattern
– Useful for service providers
• But threat to privacy
18/06/2012 ETSIoT 2012, Seoul 22
23. Advantages of Learning Engine
• Intelligent learning engine
• Usage pattern and power saving profile are
generated locally
• No threat on private data
• But network usage pattern could not be
known
18/06/2012 ETSIoT 2012, Seoul 23
24. Other Avenues
• Adding a photovoltaic cell to generate
additional power
– WYSIPS has introduced this
• Adaptive display
– Shorten the display screen when battery level falls
below a predefined threshold
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25. Contents
• Introduction
• Android power management architecture
• Present research on power consumption &
management
• Survey on power saving Android apps
• Future directions
• Privacy & security concerns
• Conclusion
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26. Privacy Concerns
• Today’s smart devices contain user sensitive
information.
• Usage pattern is mutually exclusive.
• Collecting usage logs to interpret usage pattern
raises the issue of privacy.
• Generation of usage pattern must be privacy
aware
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27. Privacy Concerns
• Raw usage data User behavior
• App stores info in a log file another app could
access it and send to other remote server
• Location information 3rd party ad and Location
privacy is compromised
• Some app with similar approach could also collect
– MAC address of Android device
– IP address
– Account credentials
– Phone number
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28. Solutions
• Store monitoring info in a secure database instead of writing
into a file.
• Encrypt the collected information.
• The app randomly decides when to send the database dump
to the remote server.
• Database dump is sent over a secure connection.
• The user should be given some control over how much usage
information is to be sent to the remote server.
• The remote server must employ some privacy preserving data
mining algorithm to generate the usage patterns.
• Such patterns should never be revealed to any third party.
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30. Contents
• Introduction
• Android power management architecture
• Present research on power consumption &
management
• Survey on power saving Android apps
• Future directions
• Privacy & security concerns
• Conclusion
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31. Conclusions
• Highlighting the need of efficient power
management for Android devices
• Different research directions are discussed.
• Survey on power saving apps
• Future direction on power management
• Privacy threats & repackaging attack
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