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all right uh thanks a lot for
coming thanks a lot to Devcon for having
me um first things first this is my
understanding it's not the official IBM
line and I'll be talking about the
exploration project MTN it's not a
product it's a research
project and this is basically how it
mostly
looks so the team MTM is uh sponsored by
MC Divine who's the vice president for
cloud Innovation at IBM and it's run by
Egan Ford a distinguished engineer who's
uh working 24/7 in the moment um pushing
this and also pushing this within IBM
that's that's the important part to
understand there and uh with r lme um
driving the bus and 12 Engineers that
are working on this
project I'm Henning d uh I'm a senior
programmer at the blockchain group at
IBM and I have prior experience for
example in distributed databases which
come in quite handy sometimes in this
particular field but also with high
velocity and scalability as these
problems are of course nothing new in
the world of distributed
databases so MTN is an acronym for
multiplying things
needlessly and uh this was a pun a
little bit of how blockchain works and
maybe it's not quite that needless right
uh and it's really about Aon processing
communication and coordination between
the edge and the
cloud so where we're at we saw this
diagram before today even I think uh
we're at at a historic explosion of
calculation power of processing power
and this is of course driving the
internet of things because more and more
small devices are becoming more and more
intelligent iot as a phomen is actually
already here
um there are huge success stories in the
industry for example jet engines the way
that they are checked every second and
uh traced and tracked and uh the way
that uh a new business model basically
has evolved from the way that they are
constantly online that is something that
is a reality now there are also
disappointments where for example in the
consumer sector things didn't pick up
the way that they might have been
expected for example you would uh still
not see too many uh TVs that actually
are used to uh use the internet
with the motivation for MDM is that as
more and more devices around us become
more and more
intelligent um the digital experience is
going to be changing and more and more
of these devices will be connected
directly to each other peer-to-peer uh
instead of to centralized Cloud just
because they
can so what's emerging there is uh has
been called a devis
democracy in the best case where the
power in the internet of of things will
actually shift from the center to the
edge and while that
happens what can happen there is that a
liquid Market can emerge where devices
are dealing directly with each
other and this will hopefully lead to
products that we can't even imagine
right
now obviously to make that happen the
blockchain can be a really strong
component and uh the needs that we
identify for this new world of device
democracy are um to large degree exactly
what what a blockchain can
offer so if we look at the actual
requirements and needs of the Internet
of Things realm today we see a couple of
roadblocks one of them is that the
architecture that we have today that's
highly centralized won't necessarily
scale over the next couple years we now
have an internet of things that is uh
having a certain topology and we will at
any rate uh want to find a new way of
connecting
devices
then these connections have to be
maintained they have to be uphold and
this is going to be creating some
expense and somehow that has to be
justified and it's not quite clear that
the business business models that we
have today are actually doing that what
we also are going to realize is that um
the internet of trust that we had some
decades ago without spamming everything
is not a reality anymore we can be
certain that any um system that we're
deploying today is going to be attacked
and his vulnerabilities are going to be
exploited so security has a very high um
priority right now we also won't have be
seeing people accepting their toast or
spying at them so that's another
dimension of security where people will
want to have some control over what the
devices are doing and the way that for
example the smartphone is completely
owned by the um producer of the
smartphone today is probably not how
it's going to be
continued now coming back to the toaster
people
expect 20 years or more as a LIF span
for a
toaster if you have a centralist model
with a toaster that's somehow useful
because it's connected um then you have
to maintain that for 20
years is that even viable or are people
going to be very very frustrated with um
producers going out of business which is
kind of likely within 20 years not every
company gets to 100 like IBM and then
fin
the business models that we're seeing
today uh sorry uh the business models
that we're seeing today
are very much focus on information for
advertisement and that is probably not
going to scale because there's only so
much data that you can actually get out
of a household and as more and more
devices compete to collect the same data
then probably the value of the data is
going to go
down so the motivation here is that when
we see um uh the possibilities that we
have here today can we have a
userdefined algorithm can we have a
customized experience that is not based
on what we have in the moment and the
iot today where we have
uh new possibilities that are going to
be used either for mischievous stuff if
security is not high enough or for
exciting new stuff that we might not
even imagine right now
when we see at the bottom line though uh
it's important to always remember that
in the end it's about making the
experience
better it's not maybe worthwhile to have
the toaster printing advertisement on
your toast but you will want to have
something that really makes
sense and the whole on the whole what we
are having today is the cloud as a
centralized very powerful control
mechanism so to say of devices that's
less centralized than we had before but
it's also not probably how it's going to
stay when we going to more and more peer
and peer
architectures that this kind of
development is uh happening no matter
whether you are Imagining the blockchain
here or some other peer-to-peer
mechanism that's that is pretty
clear so if you look at this
requirements what emerges as um basic
foundation so to say has a very large
overlap with what blockchain can offer
and uh in this regard except for
identity all three of the first all
three bullet points over that are
exactly what a blockchain can offer you
you will have um a very interested
interesting uh convergence here where
you can see that ethereum for example is
uh implementing whisper now um there are
efforts to uh create swarm that is going
to add exactly um what is needed to have
file transfer and messaging where uh
fascinatingly in earlier Explorations
that were done at IBM um Tash and bitter
rent were used um that are now um or at
least part of them part of uh whisper
and
swarm so the internet of things as it
stands now is at probably 9 billion
devices and what we thinking about and
talking about is when it goes to 100
billion devices which is the future
nobody might say exactly when it is
maybe it's 2020 or 20 25 but it's going
to go there that's pretty clear and the
mission that we put ourselves for MTN is
analytics at the
edge analytics at the edge means if you
have a sensor that is picking up data
then you might not be able to ship it
fast enough to the cloud and have it
analyzed with um high capacity computers
but it's possible that this data has to
be selected before it can even be
shipped and it seems to be that in the
moment
60% of all the data that is collected at
the edge loses its value within
milliseconds and so 90% of the data that
is collected is never actually used and
this is what we wanted to address with
the exploration
MTN and what we used for that
um and what we looked at here is how we
can use um technical
um behaviors that we see now that how we
have real time processing at the edge
and how we in the end um can have
security containers in a hostile
environment and how we have a bottom
line that gives us better quality of
experience hopefully
so this is how it looks like this is a
um software defined radio and it has 5
megabits a seconds of data that it
collects and that volume is enough that
you cannot actually ship it from our
experimental Raspberry Pi setup to uh a
central Cloud to have it analyzed so
what has to happen is um create an
infrastructure so that we can use these
little devices where we have raspberry
pies that end points that are our
sensors in this um exploration and these
software um radio devices uh attached to
them and then use um the plethora of
data that's out there terabytes actually
that you have access to this is the
United States frequency allocation and
zoom in into some frequency where we can
find interesting data for example um we
have Smart Meters at some point we also
have other stuff like aircraft radio
navigation where you can track aircraft
of course mobile and FM is taking up big
swaths of this but um we are focusing on
something simple and that is just the
water and power meter output and this is
how it actually looks if you read that
out um interestingly in America there
seems to be no protection at all you can
read all the meters of all your
neighbors in the moment um maybe that's
not going to stay like that but uh for
experimental purposes that uh may be
quite
interesting um you can also track flight
data um that is is another possibility
this is how this looks if you read it
out of the uh radio
frequencies so for our um experimental
setup we have a couple of personas here
um we have the device itself that's the
Raspberry Pi we have the device contract
that is um the contracts that are
actually that ethereum contracts that
are actually entered in between the
devices and a central token Bank
contract we have the device registry
that basically knows everything about
all the devices in the system for our
setup and then we have glansen which is
a producer of Docker containers that are
actually shipped out to the devices that
those devices employ deploy and that are
then having basically the entire logic
that is needed to ship to make to enter
into negotiations and to ship the data
home to a
consumer this is how um the
infrastructure
looks um up on the top you have the uh
raspberry pies um down here in the
middle you have the um Contracting
server that is the consumer of the data
that actually is willing to pay for the
data and wants the data to be to um to
have the data delivered from the
raspberry
pies oops
sorry oh sorry it's out of power for
good somebody can help me
I have one it's fine there's one on the
ground ready plug in oh
not okay
so the main aspect um what ethereum is
actually used for and that's that's the
important thing here because I I've
often encountered the question why do
you need blockchain for iot and the main
aspect is really the negotiation
to negotiate between devices and
endpoints in an untrusted environment
that is what we're using ethereum for
and that is the whole mechanism of the
devices offering their data the central
consumer of the data accepting that
offer um creating an escra where the uh
the future payment is put uh for the
devices then to ship the data um which
is out of Bend uh and then and in the
end to pay out of the ES
when the data has been shipped so and
that is basically the main um point of
the whole experiment to see whether that
in a fashion that scales sufficiently um
can actually be done using ethereum and
at this point I would say um it is a
success so this is how a proof of
concept uh looked like it's actually
emulated uh simulated we didn't have
quite as many points there but we zeroed
in
on some that that were actually running
then you could see what data um was
actually there to and what connections
were endpoints were actually there to be
consumed you could have a device
registration where a device can be
registered um so that it can be in take
part in the
marketplace we then have uh the view
here of the blockchain how it looks when
these devices actually starting to
communicate with each other and and
starting to enter contracts with each
other and this is how um the actual flow
within the different players in the
system worked I I won't go through it
step by step in the moment here but
um it's just I you you're getting the
idea it's it's quite straightforward
actually and in the end this is the this
was the bootstrapping flow actually to
enter into the um to get a container to
a device so the whole system can start
and this is the flow um when the
container actually runs where you're um
making a proposal and uh in the end the
execution when it's done is wound
down
so there are a couple of risk and
opportunities um that that are obvious I
mean uh that we haven't looked into one
is the question about a spot Market how
can that look um what is not clear to us
in the moment is how do you actually
control access to the whole Market how
to control access to the sensors it's
basically out of the scope of the
experimentation that we did but it's not
something um that we consider
unsolvable um there's also the question
how would actual vendors how would
actually participants in such a
Marketplace like to uh access and
process and analyze and filter this kind
of data and um what kind of arbitrary
code can you allow in this this kind of
environment
um the next steps for us and it's it's
still ongoing um what is what is
happening there and again this is an
internal experimentation so to say where
that we use also um to convince people
that this is uh the way to forward
and we are
looking uh where we're just hoping that
A Thin Client is going to be in the
cards very soon to have a good um road
towards scalability for this model
where as far as I can see we are going
to have not too many validators but a
lot of thin cines and that would be a
good answer to how this can
scale um there should be some kind of an
exchange and directory that we will uh
look at how this could look where um the
entire Marketplace can can be driven
through um and then we're going to have
a push uh internally to try to uh find
20,000 people um that are interested to
sign up for this have raspberry ties
connecting into the system and making a
large scale real test testing the whole
ethereum installation um uh how fast it
can really how how big it can really
scale uh a big Thanks goes to the go
team at this point and I've been asked
specifically but even forward to extend
that um Jeff Felix goph Victor uh you
really helped us a lot I hope we also
were able to contribute because we
actually did ran some large scale tests
with hundreds of devices or at least 100
devices uh running through containers
running unusual devices like arms um
raspberry pies who are slower and might
have different kinds of race conditions
as a result and uh we ran into a bug
here and there and it was just amazing
how this week uh we've been able to work
together and and fix the stuff the IBM
guys were very tired and overworked so
they were grumpy and brief sometimes um
but it was great support that came from
here and big thanks for that so thank
you
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