June 2015
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will involve varying the simulated radio net-
work conditions. In a simulator, it is trivial to
impose particular signal strengths between
any pair of nodes, and to implement rules that
randomly drop packets as signal strength goes
down. e con guration can be varied during
a test, to check how nodes behave when con-
ditions change, such as when a train passes
across the line of sight between two nodes
and interrupts radio communications for
a short while. Best of all, such tests are pre-
cisely controllable and repeatable, unlike in
the real world where trying to impose radio
conditions is di cult at best. Testing can also
scale out horizontally, as shown in gure 3. It
is easy to build many variants of networks to
test the so ware with di erent ways to deploy
the same number of nodes. Di erent balances
between gateways and sensor nodes can be
tested, as well as di erent network topologies.
Figure 3 also shows how simulation lets you
run many di erent tests in parallel, which
makes the total time to run a set of tests much
lower than if they had to be run serially on
hardware.
But can it really work in practice to simulate
hundreds or thousands of nodes on a single
host computer? e answer is yes. IoT sensor
nodes typically have a very low duty cycle. e
sensors do not sense the world continuously,
but rather, wake up regularly to take a sam-
ple and report it. Each sample run might take
a second or just a few milliseconds, and then
the system can be idle for minutes or even
hours. is saves power, and makes it possi-
ble to have nodes deployed in the real world
for extended periods of time without having
to service them to change batteries.
us, there is a large amount of idle time in
the system, idle time that can be exploited to
accelerate the simulation by using hyper simu-
lation. Rather than playing out idle time cycle
by cycle, a simulation solution like Simics
jumps straight to the next interesting event
that would wake up a sleeping node. at
means that a system that is mostly idle can
be simulated many times faster than real time,
which is a property that is exploited in large
IoT simulations. I actually did this myself a
decade ago, when we ran 1000 IoT nodes on
a single-core Windows XP 32-bit host faster
than they would have in the real world. At the
time, that seemed insane, but today it sounds
like business as usual.
In the end, physical labs are needed to per-
form nal testing on your system. You have
to test what you ship and ship what you test.
However, using simulation to augment the
physical test lab to cover more test cases and
run more test variants is necessary to ensure
that quality is maintained and that the system
is robust across a wide variety of situations.
With simulation, you will be able to build a
better IoT system in a better way.
n
Figure 2. Scaling up the network provides to ability to simulate large networks.
Figure 3. Parallel simulation of di erent tests
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GreenPeak: Smart PIR sensor for smart home applications
GreenPeak Technologies announced a new addition to its Smart Home
portfolio with the launch of a reference design for a low cost Passive
Infra-Red (PIR) sensor with outstanding performance. e reference
design of the PIR motion detector can enable application developers
to quickly build a ZigBee enabled motion sensor that is ready to be
produced with GreenPeak’s quali ed ODMs and can be integrated in
Smart Home applications like home monitoring, senior lifestyle, smart
HVAC or smart lighting.
n
Imagination: Ensigma Whisper cores for wearables and IoT
Imagination Technologies announces the rst members of its Ensigma
Whisper exible connectivity IP family, designed speci cally to enable
the integration of ultra-low power communications in SoCs target-
ing wearables, IoT and other connected devices that require extended
battery life and low cost points. With the new Ensigma Whisper radio
processing units, customers can choose to integrate Wi-Fi 802.11n,
Bluetooth Smart, or a combination of the two standards, depending on
their speci c application.
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