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[Music]
so so is this device service available
times and I've been implementing this
model in the GUI theory also called
alias but it's also applicable in any
model or any for any photos
wetness those turns out to be workable
than it could also serve as a proof of
concept for our future Network protocols
so what I was trying to realize is a
truly needy surprise the service found
the very presence of the server's can do
resource allocation and vocalizing based
purely on market signals can take care
of their own interests and putting
themselves against attackers at the
course and force because and so the most
obvious issues such a system has to
solve is that in a peer-to-peer network
promises are nothing forcible so anyone
can get away at any point including
server-side after receiving payment so
we can have some kind of verification
mechanism and then in this case in this
followed this will look like so servers
have to first provide the pre-service
and after there's a high demand for the
pre-service and try to touch the server
they can start operating the money in
order to
also the market mechanism themselves are
time dependent and what works on a
longer time scale might not work people
evolve the short of time still simply
because the information that actors are
trying to base the decision stone might
need some time to become a reliable like
service quality age and responsibility
stakes and service difficulty
measurements are very nice things and
you just have to collect a certain
amount of data in order to able to make
good decisions and I have problems in
not high-frequency trading which I do
every day disconnect from any market
fundamentals
stuff that he provided activity bags to
price fluctuations so this would also
like to avoid a food price preparations
because surprises I believe are
practically meaningless on a net short
enough time scale prestigious and so in
order to make things a bit more stable
and predictable in this talk I will show
you how the server's camera but I happen
to be to allocating their serving
capacity and how science can do load
balancing based on a server feedback and
also the longer time scale can evaluate
server performance and choose the best
service for the money
so for toaster let's look at how these
servers and manage their own serving
capacity and the response times servers
so the server still have their own token
accounting and so they they have been of
service tokens which are meant to be
based on the actual physical serving
request and they should be unrelated to
any market the prices or conditions and
the universe the costs are always
dominated in the service topaz and
basically usually the server's can
freely decide is the cost of any
individual request but there are
previously announced the maximum cost of
is electric
Rufus time and we also defined capacity
as a service to answer spendable a time
unit and we assign a capacity to each
client which basically means a request
rate limiting and we also set an upper
limit on the total capacity of all
connected clients and this is the
drinkie goal of this is to avoid the
transient overlords by which I'm in a
situation where we have a lot of
requests in the same time and the
response time start to rise very quickly
and so maybe set up some criteria for
detecting this and we can maybe not
always avoid this part they reduce its
frequency of its consistently adjusting
the total capacity llamas so the real
frustration within method of attack in
ESS for the price side of control and as
I said it's based on the
capacity to each client that also
requests butter and the server to assist
request it can remove the cost of the
request from the buffer and also reach
out to buffer at the rate that's
proportional to the capacity and in
every very bind and it also includes the
interpreter tables and this is what the
clients can use as a feedback for know
that I'm saying because if they have
multiple server connections I can always
send a text request to a server but it
may have the best value and yeah now a
few words about how service tokens are
being so so so basically we belong to a
service to be able to sell some of them
they have tokens in advance but not too
many of them because the spending the
selling rate of the tokens it's also
limited and it is always the service
interested in the answer there stability
of the consciousness power of its own
organs because as we will see later that
the clients will pay attention to this
and and the service will do the
reputation it so what is a service
should I do to do is limit the total
outstanding about its service to ants by
controlling the selling price of tokens
so there's a base price and
as issues Morimoto castle can arise of
the total price if we are limiting the
amount of tokens we should also enforce
spending of little pants by sending an
expiration time on them or by making
them inflationary was some combination
of these and this was important mention
here that whenever a currency transfer
is accepted by the server it's not
automatically converted to service
tokens
that's something the client has to
explicitly explicitly initiate and and
this is also when the expiration starts
to Kingdom so it's always optional to
buy a significant amount of service
tokens in advance that's an option for
clients that has a national course but
it also has a benefit one benefit is
that they eat or is a further price to
fluctuations of even more importantly
that this is a commitment to spending
the tokens and using the service in the
near future and the server this is a
very valuable information for the server
and the server will deliver this by it
not being they're more stable
connections of how it's done so so we
are going to the client connection
priority model the service obviously the
number of clients to be connected cycle
there is limited so Victor have some had
priorities and the private dividing
using this model is a token balance /
requested capacity and I'm not going to
explain missing
the nice property of this is that it
rewards commitment commitment so the
client promised to use the service in
the near future that the server is to
let the client use this service in the
near future and another nice property is
that it lets us integrate the free
service very nicely and smoothly into
the whole model and this is all
something that already works in their
big night servers that even plants we
don't have a token palace
they have a virtual negative balance
which is associated to IP address also
it's a expire this one actually over
along another kind but so this is to
ensure that three clients can it's also
know the client who has used the service
lesson recently and has a higher chance
to connect so tree service is also
important and the server also has to
ensure that the free service is a
regular did not always but regular
regularly available for two reasons one
of them is that this is what helps
reputation building
new customers and the other one is at
the same condition that allows free
service to be unavailable it also
ensures that the service demands are all
spendable in a limited time frame so
there's another control mechanism healed
that controls the base token price based
on whether the service free service is
possible or not if it is possible then
it reduces the price and other I say it
is slowly exponentially increases the
base price yeah this is about it for the
server mechanism and now let's take a
look at the right hand side so this is
going to be going to every individual
here but there's a subjective value
measurement from the find side which is
ideally it should be a mirror of the
server side token accounting so
basically the clients will try to
somehow put a number on how much service
they receive and this is also based on
serve the requests and currently
capacities and it also modified by a
service quality factor which is based on
which response times and how response
times are probably per serving but it
depends on the expectations of response
times which depends on price factors and
everything so basically it's possible to
if they find has to make a decision on
who to pay for it can map out the whole
available market as a price versus every
expected response time and function
which is nice and if you
easy to understand for human users so if
we have a regular groom and we have an
expected response time then we can
convert our quality statistics into a
single scalar value and I'd like to
mention here that the various constants
can even about as a negative by for
clients because we have to incentivize
reliably with response times and this
service value is what we kind started up
trying to get all their money basically
and finally there's the tricky part of
this because if the fight wants to make
a statement about who to pay for than
what it really was like to do is predict
the service value received after making
the payment and before the next payment
is requested
so so theoretically if they can trust
the server this is not so hard because
we expect the service against purchasing
power to be more or less stable and the
client has an idea of how well your the
service service depends were in the past
and there's a token price at the moment
so it should be predictable but of
course the client cannot blindly trust
any server so this is how the
recognition building magnesium works we
have three predictors we have a base
value which is a very simple as paranoid
and all uses by the things that the
Defiant knows for sure so it's basically
takes the service value received so far
and the payments and so far and the
payment expected currently and it just
does a linear extrapolation which is
which converges to something
over the long term is not very good but
also not suitable and as the trusted by
a predictor it does what I already
described it believes the server and
this token accounting at token prices
and the stability of these tokens and to
make the final judgment there's a third
a superb predictor which initially takes
for it returns the predictions of the
base predictor and the overtime is the
trusted predictor process and they gives
the better estimates of service value
received after making a payment then it
will allow more and more deviation from
the whispered base with predictors value
in the direction of the attractive
predictors prediction and so this is
this
this allowed deviation this represents
the reputation of the server and this
job is going to be ruined if the server
doesn't all these promises and doesn't
keep its service and buy a device table
and yeah I feel thanks so now just just
just about few words about the current
state of implementation and the roadmap
so as I already said the most of the
most of the components
living material and I so far mostly
focused on implementing the server-side
because that's what the first that's
what we first need in order to even
start experimenting and recently and
server India has been implemented it's
going to come out in one of the
subsequent get releases and this with
this you can already play with the
client priorities and you can assign
priorities to your own or your friends
or customers nodes and there's the outer
conceal mechanism is working progress
but I really hope I can finish it and we
can release it and by the end of this
year and this will mean that by the end
of this year we are going to have a thin
and fully booking payment enabled light
servers and which anyone can start up
and start earning money and on the tight
side there's going to be some manual
have maybe like a revised list for
servers who we can pay for but the the
client side side it's also already
partially implemented and I really hope
that by the middle of next year we are
going I'm going to be able to show some
results that you can try of course this
is going to be an ongoing research and
yeah so if you if you have any feedback
contact me I'm going to
they're pretty the community man's about
the details of this model because I
heard that I didn't answer and an
advocate questions it is short talk but
I'm going to put up to that when you
documents to my github page and I'm
going to announce them on Twitter and
everywhere and I would really like to
make this model usable vote for for
going to even the Gateway plant and also
for our future light bands of material -
and that was it thank you for your
attention
one thread I do a mystery how the
payments work well so this business
model is so it had worked with any kind
of payment technologies I was looking
into using radar and now this whole team
also has a base web protocol that's also
a an interesting dimension of technology
but I think we can even start is because
I said simple payments which are really
easy to do and yes also the model
doesn't depend on the payment technology
just service to testament and notes also
every server has also spoken and they
are only a country locally on the server
and I'm not sure yet whether they should
be tradable transferable
that's what's that yes so the server
will so if you stand either to a server
or die or whatever but this are we want
to accept that then we are going to have
an ether or die or the server and as I
said you have to explicitly say okay now
I have eaten with you and I want to work
some of it
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you