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GreenDroid: A Tool for Analysing Power Consumption in the Android Ecosystem
1. GreenDroid:A Tool for Analysing Power
Consumption in the Android Ecosystem
Marco Couto*¶, Jácome Cunha*§, João Paulo Fernandes‡,
Rui Pereira*¶, and João Saraiva*¶
1
Informatics ‘ 2016 – Poprad greenlab.di.uminho.pt
* HASLab/INESC ¶ Universidade do Minho, Portugal
‡ RELEASE, Universidade da Beira Interior, Portugal
§ Universidade Nova de Lisboa, Portugal
{mcouto, ruipereira, jas}@di.uminho.pt, jacome@fct.unl.pt, jpf@di.ubi.pt
3. Green Computing
Caught the attention of many companies allowing them to save:
Informatics ‘ 2016 – Poprad greenlab.di.uminho.pt
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“close to 50% of the energy costs of an organization can be
attributed to the IT departments”
- [Harmon and Auseklis, 2009]
“up to 90% of energy used by ICT hardware can be attributed to
software”
- [Standard, 2013]
4. Green Software
Reducing energy consumption through software analysis and optimization
Problem:
How to analyze
How to interpret
How to improve
In mobile devices, the interest is quite large
Battery lifetime is critical!
Informatics ‘ 2016 – Poprad greenlab.di.uminho.pt
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5. GreenDroid
Power consumption model oriented
Consumption per execution and program trace
Predicts possible power-expensive methods
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6. GreenDroid: Basic Workflow 6
Source
Code
Tests
Instrument
Source
Code
I
Tests
I
Build
APP
Tests
. Execution Trace
. Consumption
. Execution Time
*For each
Analyzer
Power Consumption
Model
Build
Informatics ‘ 2016 – Poprad greenlab.di.uminho.pt
7. Power Consumption Model – Power Tutor
Hardware components have states
e.g., CPU has different percentages of usage
Each state implies different consumptions
Idea: assign consumption to each component state
When monitoring consumption:
Check the components’ states;
Determine consumption using the power model
Informatics ‘ 2016 – Poprad greenlab.di.uminho.pt
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8. The Model as an API
Power Tutor is an Android application
Problem: cannot be invoked in other applications
Solution: transform the model into an API
Informatics ‘ 2016 – Poprad greenlab.di.uminho.pt
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1. traceMethod()
2. config()
3. start()
4. stop()
Program trace
Initializes Power Consumption Model
Starts the power monitoring thread
Stops the power monitoring thread
9. Instrumentation: Source Code
Informatics ‘ 2016 – Poprad greenlab.di.uminho.pt
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Source
Code
public class C1{
...
public void m1(){
Estimator.traceMethod(“m1”, “C1”);
...
}
...
}
public class C1{
...
public void m1(){
...
}
...
}
10. Instrumentation: Tests
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Tests
public class TestSuite1{
...
public void setUp(){
...
}
public void tearDown(){
...
}
...
...
}
public class TestSuite1{
...
public void setUp(){
Estimator.config(“package”,
_______android.os.Process.myUid(),
this.getContext());
Estimator.start();
...
}
public void tearDown(){
Estimator.stop()
...
}
...
...
}
14. Power Consumption Graphics
Informatics ‘ 2016 – Poprad greenlab.di.uminho.pt
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Method classifications and analysis
technique based on prior research
“Detecting Anomalous Energy
Consumption in Android
Applications” – SBLP’2014
15. Conclusions
GreenDroid Tool
Analyze power consumption of Android apps
Detect possible power leaks
Plan to extend GreenDroid approach to analyze other applications
Download at: https://github.com/greensoftwarelab/GreenDroid
Informatics ‘ 2016 – Poprad greenlab.di.uminho.pt
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16. GreenDroid:A Tool for Analysing Power
Consumption in the Android Ecosystem
Marco Couto*¶, Jácome Cunha*§, João Paulo Fernandes‡,
Rui Pereira*¶, and João Saraiva*¶
16
Informatics ‘ 2016 – Poprad greenlab.di.uminho.pt
* HASLab/INESC ¶ Universidade do Minho, Portugal
‡ RELEASE, Universidade da Beira Interior, Portugal
§ Universidade Nova de Lisboa, Portugal
{mcouto, ruipereira, jas}@di.uminho.pt, jacome@fct.unl.pt, jpf@di.ubi.pt
Hinweis der Redaktion
Importante dizer que:
A ferramenta Power Tutor não é nosso, e funciona como uma aplicação que monitoriza consumos de várias aplicações
Os estados dos componentes de hardware são muitas vezes associados a uma aplicação (exemplo: sabendo que o CPU está a 80%, é possível saber quanta dessa percentagem se deve à aplicação X ou Y)
Tests with consumptions above average (in the analyzed program) are considered excessive, and below average not excessive.
Using a series of thresholds we identify the methods accordingly. For example red methods are those who appear in over 60% of excessive test cases, green in 0%, and yellow otherwise.