09-energy.org

Energy benchmarking

Learning outcomes

• Understand how to measure mote energy consumption
• Be able to identifier energy consumers within a mote
• Understand the start-up, nominal, and long-term aspects of energy consumption

Motivation

• Deployment of wireless motes in a real environment often requires them to be long-lived without intervention or need for battery change
• To estimate lifetime, we need to measure power consumption (although battery choice may also be a factor)

Measurement

Basic theory

Instantaneous power $P$ is a function of voltage $V$ and current $I$ \[ P = VI \]

Power varies over time and so the energy consumption is the integral of power \[ E = ∫₀^t P(t)\ \mathrm{d}t \]

However we often only have a series of measurements and thus need to estimate based on a series of measurements \[ E ≈ Δ t ∑_0^t P(t) \]

where $Δ t$ is the fixed time period between power measurements.

Why is measurement difficult for motes?

Wireless sensor devices have a mix of high current usage:

• sensing (particularly for some sensors)
• radio listening or transmission

and low or medium current usage:

• sleep
• computation

Furthermore, power consumption varies rapidly over time.

It’s often difficult to accurately characterise both types of usage with the one measurement device

Sleep current is particularly difficult since it is both instantaneously small but a big overall contributor

Using an oscilloscope

Oscilloscopes are good for accurately identifying time periods:

• how long does sensing take?

It is also possible to estimate the current draw by measuring the voltage drop for an in-series resistor

Expect, however, a +/- 10% error on this measurement

No good for measuring micro amps (e.g., sleep current)

Using a multimeter

Precision multimeters are much better for measuring microamp currents

However they tend to assume that current use is roughly constant

Accuracy thus can be improved by

1. micro-benchmarking
2. using an R-C circuit to smooth input to the multimeter

Using a power analyzer

A power analyzer, such as the Qoitech OTII, simplifies the task of assessing power consumption and will simultaneously measure voltage and current.

Power analyzers are more accurate than oscilloscopes for sleep current but a precision multimeter is the gold standard

Power analyzer output

file:figures/otii-analyze.jpg

Microbenchmarking

Consider this power consumption graph:

We can identify 5 distinct time periods:

• CJC warm-up (this is for a thermocouple sensor)
• CPU active
• transmission
• polling
• idle

Microbenchmarking targeted measurement

Microbenchmarking addresses the problem of characterising the power consumption of individual operational modes.

For each operational mode (e.g., transmitting a radio packet):

1. Program the mote to repeatedly (X times) transmit a packet
2. Measure current (e.g., with a precision multimeter)
3. Measure time period (e.g., with an oscilloscope) and divide by X

Microbenchmarking summary

We then form a table like this

Operation	Current (mA)	Time (s)	mAs
Sensing
CPU active
Radio send
Radio listen
Idle
Total			—

Note that to convert to power, we need to assume the voltage is constant (e.g., 3V)

Here’s a worked example from Klues et al.

https://ieeexplore.ieee.org/abstract/document/7471452

https://dl.acm.org/doi/pdf/10.1145/1294261.1294286?casa_token=TUXZOamkmJ8AAAAA:HAnvY8uNRzjntTuNuO34Lf9awk0dFLg3AQXWSSaHzAhsuavgZp7_xAFQK3FKbtOaXSYSFIz9qS6XS5I

Consider the larger picture

Not all behaviour will be in the short term. Consider the following graph of battery voltage state over time:

The sudden downward dips in battery voltage reflect periods when the server was unavailable. During this period, wireless nodes were retrying each transmission repeatedly and thus using more energy.

Also consider start-up energy costs

• Start-up energy consumption may be radically different and this will be an issue if you are using energy harvesting

Contiki built-in tools

Energest provides a simple way to estimate the energy use based on when the radio is being used

Typical output looks like:

Energest:
 CPU             0s LPM         9s DEEP LPM    0s  Total time 10s
 Radio LISTEN   10s TRANSMIT    0s OFF         0s

Energest:
 CPU             0s LPM        19s DEEP LPM    0s  Total time 20s
 Radio LISTEN   20s TRANSMIT    0s OFF         0s

Summary

• Microbenchmarking is a key idea for accurately measuring energy low-power motes
• Don’t just think about normal operation but also watch for exceptional behaviour occurring in the long term and during start-up