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Accurate Prediction of Power Consumption in Sensor Networks University of Tubingen, Germa ny In EmNetS 2005 Presented by Han

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Page 1: Accurate Prediction of Power Consumption in Sensor Networks University of Tubingen, Germany In EmNetS 2005 Presented by Han

Accurate Prediction of Power Consumption in Sensor Networks

University of Tubingen, GermanyIn EmNetS 2005

Presented by Han

Page 2: Accurate Prediction of Power Consumption in Sensor Networks University of Tubingen, Germany In EmNetS 2005 Presented by Han

Outline

• Goal

• Approach to build AEON

• Power evaluation of TinyOS

• Comparison with PowerTossim

Page 3: Accurate Prediction of Power Consumption in Sensor Networks University of Tubingen, Germany In EmNetS 2005 Presented by Han

Goal

• To evaluate energy consumption of real codes– Algorithms and programming styles influence

power consumption– Predict network lifetime

Page 4: Accurate Prediction of Power Consumption in Sensor Networks University of Tubingen, Germany In EmNetS 2005 Presented by Han

Approach

• Build an energy model

• Implement the energy model in an emulator

• Use the emulator to analyze power consumption of real codes and verify

Page 5: Accurate Prediction of Power Consumption in Sensor Networks University of Tubingen, Germany In EmNetS 2005 Presented by Han

Building energy model

• Based on Mica2 platform

• Write special TinyOS programs to turn on each hardware component each time

• Measure the current draw

Page 6: Accurate Prediction of Power Consumption in Sensor Networks University of Tubingen, Germany In EmNetS 2005 Presented by Han

Energy model

Page 7: Accurate Prediction of Power Consumption in Sensor Networks University of Tubingen, Germany In EmNetS 2005 Presented by Han

Approach

• Build an energy model

• Implement the energy model in an emulator

• Use the emulator to analyze power consumption of real codes and verify

Page 8: Accurate Prediction of Power Consumption in Sensor Networks University of Tubingen, Germany In EmNetS 2005 Presented by Han

Implementation

• AEON is implemented on top of AVRORA

Page 9: Accurate Prediction of Power Consumption in Sensor Networks University of Tubingen, Germany In EmNetS 2005 Presented by Han

AVRORA

• Developed by UCLA (IPSN’05)

• Instruction-level simulator– Runs actual microcontroller program

• Tossim use software to model hardware components– Lose timing and interrupt properties

• AVRORA is 50% slower than Tossim

Page 10: Accurate Prediction of Power Consumption in Sensor Networks University of Tubingen, Germany In EmNetS 2005 Presented by Han

Approach

• Build an energy model

• Implement the energy model in an emulator

• Use the emulator to analyze power consumption of real codes and verify

Page 11: Accurate Prediction of Power Consumption in Sensor Networks University of Tubingen, Germany In EmNetS 2005 Presented by Han

Validation

• Average error 0.4%• deviation 0.24• Predict 172 hours for CntToLedsAndRfm

• 168 hours by Crossbow lifetime test

Blink application

Page 12: Accurate Prediction of Power Consumption in Sensor Networks University of Tubingen, Germany In EmNetS 2005 Presented by Han

Evaluation of Apps

Executed for 60 seconds

Page 13: Accurate Prediction of Power Consumption in Sensor Networks University of Tubingen, Germany In EmNetS 2005 Presented by Han

CntToLedsAndRfm

Radio interrupt (radio is not turned off between transmission)

Radio transmission

Page 14: Accurate Prediction of Power Consumption in Sensor Networks University of Tubingen, Germany In EmNetS 2005 Presented by Han

HPLPowerManagement

• Dynamically switch the CPU between six sleep modes based on the current load

Page 15: Accurate Prediction of Power Consumption in Sensor Networks University of Tubingen, Germany In EmNetS 2005 Presented by Han

Low power listening (B-MAC)

High data rate (wake up more frequently)

Low data rate (wake up less frequently)

Page 16: Accurate Prediction of Power Consumption in Sensor Networks University of Tubingen, Germany In EmNetS 2005 Presented by Han

Predicted savings

Page 17: Accurate Prediction of Power Consumption in Sensor Networks University of Tubingen, Germany In EmNetS 2005 Presented by Han

Energy profiling

• Map source code functions to the corresponding object code addresses (Surge)

Page 18: Accurate Prediction of Power Consumption in Sensor Networks University of Tubingen, Germany In EmNetS 2005 Presented by Han

PowerTossim

• Developed by Harvard (SenSys’04)

• Build on top of Tossim

• Based on nearly the same measurement

• Benefit from the scalability of Tossim

• Also lose some accuracy on capturing interrupts

Page 19: Accurate Prediction of Power Consumption in Sensor Networks University of Tubingen, Germany In EmNetS 2005 Presented by Han

Comparison

• For the same CntToLedsAndRfm application

• PowerTossim predicts 2620mJ/min

• AEON predicts 3023mJ/min

• AEON claims that the additional energy is spent on reloading counter after timer interrupt

Page 20: Accurate Prediction of Power Consumption in Sensor Networks University of Tubingen, Germany In EmNetS 2005 Presented by Han

Results from PowerTossim

Page 21: Accurate Prediction of Power Consumption in Sensor Networks University of Tubingen, Germany In EmNetS 2005 Presented by Han

Conclusion

• More accurate than PowerTossim (?)

• The energy evaluation parts give quantitatively improvement of designed protocols

• This tool would be useful in software development


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