Fine-Grained Power Modeling for Smartphones Using System Call - - PowerPoint PPT Presentation

Fine-Grained Power Modeling for Smartphones Using System Call Tracing

Damian Rodziewicz Based on paper and presentation by: Abhinav Pathak, Y. Charlie Hu, Ming Zhang Paramvir Bahl, Yi-Min Wang

Fine-Grained Power Modeling for Smartphones Using System Call Tracing

Smartphone Capabilities

Fine-Grained Power Modeling for Smartphones Using System Call Tracing

Smartphone Capabilities

Camera

Fine-Grained Power Modeling for Smartphones Using System Call Tracing Camera GPS

Smartphone Capabilities

Fine-Grained Power Modeling for Smartphones Using System Call Tracing Camera Wi-Fi GPS

Smartphone Capabilities

Fine-Grained Power Modeling for Smartphones Using System Call Tracing Camera Wi-Fi GPS Games and applications

Smartphone Capabilities

Fine-Grained Power Modeling for Smartphones Using System Call Tracing Camera Wi-Fi GPS Games and applications

Smartphone Capabilities

Fine-Grained Power Modeling for Smartphones Using System Call Tracing

• Energy – one of the most critical issues in smartphones.
• Smartphone capabilities are growing rapidly.
• Battery capacity has only doubled through 10 years.

Smartphone Constraints

"According to unpublished research by the Boston Consulting Group, the amount of energy that a battery can store (its energy density) is growing by 8% a year. Mobile-device power consumption, meanwhile, is growing at more than three times this rate, as backlit colour screens, high-speed wireless networks and more powerful microprocessors draw ever-larger amounts of power."

Fine-Grained Power Modeling for Smartphones Using System Call Tracing

Key issue

How can we measure energy consumption in our applications?

• Power meter
• Online power models for mobile devices
• Utilization-based power model
• System call tracing power model

Fine-Grained Power Modeling for Smartphones Using System Call Tracing

Measuring Energy Consumption

Power meter

• High cost (~700$)
• Requires performing surgery on your phone
• Only whole energy usage
• Stationary – cannot move with
• Very accurate (every 200 ms exact power usage)

Fine-Grained Power Modeling for Smartphones Using System Call Tracing Źródło: http://eurosys2011.cs.uni-salzburg.at/pdf/eurosys2011-pathak-slides.pdf

Online power model

Fine-Grained Power Modeling for Smartphones Using System Call Tracing

Utilization-based approach

State-of-art creating model Energy usage Ep = Energy used by 1 second of processor En = Energy used by 1 packet of data sent Ed = Energy used by writing/reading 1 byte … same for GPS, camera, and so on ...

Fine-Grained Power Modeling for Smartphones Using System Call Tracing

State-of-art predicting Read data every second (something like proc in Linux): %Up = % of used Processor Nn = number of packets sent Nd = number of bytes read / written Result = %Up * Ep + Nn * En + Nd * En

Utilization-based approach

Fine-Grained Power Modeling for Smartphones Using System Call Tracing

State-of-art wrong assumptions

• Active utilization is the only trigger of power state change
• File open/close, socket open/close also consume energy
• Several components have tail energy states (even few seconds)
• Linear estimation
• Sending 100 packets does not cost 2 as much energy as sending 50
• Quantitative utilization
• Cannot measure energy consumption of camera / GPS
• The interval can be too large to collect data,
• r the sampling can become too costly, if done at fine granularity.

Utilization-based approach

Fine-Grained Power Modeling for Smartphones Using System Call Tracing

Examples of power usage

Utilization-based approach

Źródło: http://eurosys2011.cs.uni-salzburg.at/pdf/eurosys2011-pathak.pdf

Fine-Grained Power Modeling for Smartphones Using System Call Tracing

Observations

• System calls provide the only means via which applications

gain access to the hardware (I/O) components.

• Names and parameters give clear indication of components

and level of utilization. (Encapsulation of utilization-based approach)

• System call can be naturally related back to the calling subroutine and

the hosting thread and the process.

System-call-based approach

Fine-Grained Power Modeling for Smartphones Using System Call Tracing

Problems

• Tail energy states – How much do they consume? How long do they last?
• Device drivers are closed source (no source / no information given).
• Power consumption does not add linearly.
• Energy does not scale linearly.

System-call-based approach

Fine-Grained Power Modeling for Smartphones Using System Call Tracing

Problems – non linear additivity

System-call-based approach

Fine-Grained Power Modeling for Smartphones Using System Call Tracing

Problems – non linear scalability

System-call-based approach

Fine-Grained Power Modeling for Smartphones Using System Call Tracing

Idea

• Use system calls as triggers in power modelling.
• Reverse engineer power logic in device drivers.
• Use Finite-State-Machine (FSM) to model the power states

and transitions between them in components.

• Nodes: Power States (Either productive state or tail state)
• Edges: Transitions between states
• Can be system call, timeout, other condition.
• We assume that these drivers implement very simple logic
• We use Linear Regression to connect workload with power usage in states.

System-call-based approach

Fine-Grained Power Modeling for Smartphones Using System Call Tracing

Creating FSM

• Create an FSM for one system call.
• Model all system calls for one component.
• Shuffle the system calls in a C program, look for new power states.
• Model one huge FSM for the phone from the components.

System-call-based approach

Fine-Grained Power Modeling for Smartphones Using System Call Tracing

Finite State Machine – step 1

System-call-based approach

Fine-Grained Power Modeling for Smartphones Using System Call Tracing

System-call-based approach

Creating FSM – step 2 - Wi-Fi

Fine-Grained Power Modeling for Smartphones Using System Call Tracing

System-call-based approach

Creating FSM – step 3

Fine-Grained Power Modeling for Smartphones Using System Call Tracing

System-call-based approach

Combinatorial issue

• Usualy one component has about 2 productive states and 1 tail state.
• It is done manually at this time.
• Applications are run, FSM models are created.
• States are binded together manually.
• Soon the process will be automated.

Fine-Grained Power Modeling for Smartphones Using System Call Tracing

System-call-based approach

Evaluation – CPU, Disk, Wi-Fi

Fine-Grained Power Modeling for Smartphones Using System Call Tracing

System-call-based approach

Evaluation – Entire Phones

Fine-Grained Power Modeling for Smartphones Using System Call Tracing

System-call-based approach

Implementation

• Tracing system calls in whole phone, to predict energy usage.
• Windows Mobile 6
• CeLog – logging mechanism for CPU, memory, TLB, interrupt.
• Wrappers that log system calls in libraries.
• Thunking – system call made to invalid address – prefetch abort trap.
• Android
• Three levels – kernel, Dalvik Virtual Machine, framework.
• SystemTap – logging system calls in kernel.
• Logging library from Android to log framework calls.

Fine-Grained Power Modeling for Smartphones Using System Call Tracing

System-call-based approach

Implementation - Eprofiler

• Currently being worked on.
• Mannualy annotating system calls in the source code to log the entry and exit points.

Fine-Grained Power Modeling for Smartphones Using System Call Tracing

System-call-based approach

Estimation

Fine-Grained Power Modeling for Smartphones Using System Call Tracing

System-call-based approach

Estimation

Fine-Grained Power Modeling for Smartphones Using System Call Tracing

System-call-based approach

What is next?

• Implementing eproof
• Releasing modified Android image to public
• Releasing tools for Android to predict energy usage
• Detailed classification of power behaviour of different OSes and handsets

Fine-Grained Power Modeling for Smartphones Using System Call Tracing

Thank You