energy metering for free: augmenting switching regulators for real-time monitoring
DESCRIPTION
Energy Metering for Free: Augmenting Switching Regulators for Real-Time Monitoring. Prabal Dutta † , Mark Feldmeier ‡ , Joseph Paradiso ‡ , and David Culler †. Computer Science Division † University of California, Berkeley {prabal,culler}@cs.berkeley.edu. The Media Laboratory ‡ - PowerPoint PPT PresentationTRANSCRIPT
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Energy Metering for Free:Augmenting Switching Regulators for Real-Time
Monitoring
Prabal Dutta†, Mark Feldmeier‡, Joseph Paradiso‡, and David Culler†
Computer Science Division†
University of California, Berkeley{prabal,culler}@cs.berkeley.edu
The Media Laboratory‡
Massachusetts Institute of Technology
{carboxyl,joep}@mit.edu
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Energy is a critical resource in this domain…
So, why don’t more publications provide empirical evidence of a change in energy usage
in situ or at scale?
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Current energy metering techniques are inadequate
cumbersome, expensive, not distributed,not scalable, not embedded
cumbersome, expensive, not distributed,not scalable, not embedded,
low resolution, low responsiveness, high quiescent power
low responsiveness, high cost, high quiescent power
DS2438ADM1191BQ2019BQ27500 [Jiang07]
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How simply can energy metering be performed?
If your platform has a PFM switching regulator…(increasingly, many do)
very simply:
iCountenergymeterdesign
• The network-wide cost of the CSMA overhearing problem• Energy division between route-through and local traffic• Energy benefits of batching or compressing data
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Outline
• Introduction• How does it work?• How well does it work?• How much does it cost?• What are its limitations?• How could it be used?
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How does it work?
Source: Maxim Semiconductor
Cin
LxVin
VinCout
Vout
Rload
iLX
Energize
Transfer
Monitor
S1
S2
VLX
E=½Li2
PFMRegulator
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The key insight: each regulator cycle transfers a fixed amount of energy to the load
ΔE=½Li2
P=ΔE/Δt
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Outline
• Introduction• How does it work?• How well does it work?
– Range– Accuracy– Resolution– Responsiveness– Precision– Stability
• How much does it cost?• What are its limitations?• How could it be used?
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A typical mote-class system exhibits a 10000:1dynamic range in current draw (5 µA to 50 mA)
iCount offers a dynamic range exceeding 100000:1
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iCount exhibits less than ±20% errorover five decades of current draw
Common Operating Points
iCount exhibits lower error over mote operating range
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A mote’s energy-consuming eventscan occur in as little as 100 µs [Jiang07]
iCount responds in less than 125 µsto sudden changes in current draw
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iCount is precise over short periods (2 sec) so one or two samples is enough to estimate the instantaneous current
All samples fall within ±2% of the median
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Outline
• Introduction• How does it work?• How well does it work?• How much does it cost?
– Hardware– Software– Energy
• What are its limitations?• How could it be used?
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Software costs include initializing hardwareand handling load-dependent counter overflows
Control
Access (15 µs)
Overflow
Initialization
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Energy costs include switching gate capacitors and handling load-dependent counter overflows
1%
0.01%
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Outline
• Introduction• How does it work?• How well does it work?• How much does it cost?• What are its limitations?
– Efficiency– Voltage dependence– Calibration
• How could it be used?
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Estimating per-component current draws from the aggregate
R G B ΔE Δt
0 0 0 8241024
1 0 0 123361024
0 1 0 188061024
1 1 0 304341024
0 0 1 149401024
1 0 1 264321024
0 1 1 328041024
1 1 1 442471024
Regression
Log
X = [ones(size(R)) R G B];p = dE ./ dt;i = p / 3;a = X\i;y = [dt transpose(a)];
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Future directions and enabled research
• Hardware profiling – estimating per-subsystem power draw
• Model validation – do theory and practice agree in practice and at scale?
• Real-time current metering – measuring the instantaneous current draw
• Software energy profiling – where have all the joules gone?
• Runtime adaptation – equal-energy scheduling by the operating system
• Gas gauging – estimating remaining battery energy
• Voltage independence – ensuring a cycle delivers the same energy independent of input voltage
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Performance summary
Performance Metric iCount
Range 1 µA – 100 mA
Accuracy ±20%
Resolution 0.1 µJ – 0.5 µJ
Read latency 15 µs
Power overhead 1% - 0.01%
Responsiveness < 125 µs
Precision ±1.5% (over 2 secs)
Stability ±1% (over 1 week)*
* Frequency averaged over 1 second