I’m working on the January 2023 Dev update and was thinking about the next priorities for the network. Mr. Kaine thinks we should focus on dynamic plasma. I came across this post in Telegram written by Henlopedia and wanted to recreate (Copy / Paste) it here for discussion.
Mr Kaine’s comments about dynamic plasma difficulty really got me thinking about Plasma-nomics.
I came up with 2 simplified models how this could look.
I’m sure there are a bunch of flaws in my thinking, I’ll try not to be too confusing.
I would like to see your opinion on this.
Assumptions
Let’s say NoM is a pipe, and we define the throughput from 1 - 10.
10 being maxed out.
Now let’s use these simple parameters to build a model and use arbitrary numbers for Plasma and QSR.
We will suppose when NoM throughput == 1 that one transaction is equal to 100 Plasma which in turn is equal to 10 QSR
So level 1 = lowest POW diff = 100 PLASMA = 10 QSR = 1 Tx ~ 100 SATS
MODEL 1
Let’s suppose this scales linear up to a threshold where it switches to exponential so that we approach infinity the closer we get to 10.
POW difficulty, PLASMA, QSR scale in the same direction
So it would look something like this
level 1 = 100 PL = 10 QSR = 1 Tx ~ 100 SATS
level 2 = 200 PL = 20 QSR = 1 Tx ~ 200 SATS
…
level 7 = 700 PL = 70 QSR = 1 Tx ~ 700 SATS
level 8 = 1400 PL = 140 QSR = 1 Tx ~ 1400 SATS
level 9 = 1960000 PL = 19600 QSR = 1 Tx ~ 196000 SATS
level 10 = infinity = 1 Tx ~ all the SATS
This sort of table would have the desired effect of curbing usage as throughput limits are approaching, transacting would become increasingly expensive.
The game theory implications:
cons:
- users will need to acquire an ever increasing amount of QSR to maintain transaction parity as the network scales
- due to usage and burn QSR scarcity increases, making QSR more expensive
- users are required to keep up with an increasingly faster spinning hamster wheel to maintain their transaction parity and ability to participate, this disincentivizes the onboarding of new users
- QSR whales are incentivized to spam the network, at zero cost of their own, to artificiality bloat the throughput, and force higher plasma thresholds. This in turn increases QSR demand as more needed to maintain parity and inflates the price.
pros:
- Network can never be maxed
- Users can transact at zero cost by locking collateral
- hamster wheel dynamic makes it probable that locked collateral increases in value over time
- Eventually a transaction equilibrium is achieved as the QSR whales disperse their stacks to the masses. As this occurs the nature of transactions shift to a utilitarian nature
Observations:
This model somewhat mirrors the POW Ethereum paradigm where miners charge an increasing rate as network usage increases. Overall the base chain becomes increasingly expensive to use and incentivizes layer 2 solutions.
MODEL 2
POW difficulty, PLASMA scale in the same direction BUT QSR scales inverse to PLASMA in the opposite direction.
(The rate of scaling can be adjusted to different values - the main point here is that it runs opposite direction to Plasma)
So it would look something like this
level 1 = 100 PL = 10 QSR = 1 Tx ~ 100 SATS
level 2 = 200 PL = 5 QSR = 1 Tx ~ 200 SATS
level 3 = 300 PL = 2.5 QSR = 1 Tx ~ 300 SATS
level 4 = 400 PL = 1.25 QSR = 1 Tx ~ 400 SATS
level 5 = 500 PL = 0.625 QSR = 1 Tx ~ 500 SATS
level 6 = 600 PL = 0.31258 QSR = 1 Tx ~ 600 SATS
level 7 = 700 PL = 0.15625 QSR = 1 Tx ~ 700 SATS
level 8 = 1400 PL = 0.078125 QSR = 1 Tx ~ 1400 SATS
level 9 = 1960000 PL = 0.00610351 QSR = 1 Tx ~ 1960000 SATS
level 10 = infinity = 0.00000372 QSR = 1 Tx ~ all the SATS
A lot of the same tenants present in this model as with model 1, but the game theory is way more interesting.
The game theory implications:
In this table there will be a point when the levels increase where QSR will be very undervalued.
Say we are at level 2, and a user has just been using POW for their daily transactions (2), it takes 5 min for each transaction.
They have a good gaming GPU so it’s no big deal they think. Now we go to level three and each transaction takes 10 min and they hear the GPU fans fire up.
They notice the QSR cost of transacting has just halved but their POW effort has increased, the market hasn’t quite caught up and the price of QSR is still the same as before the increase. So they buy 5 QSR and fuse it for their daily needs. Now demand rises and price forms a new consensus around POW value.
This would be very good incentive structuring .
In addition to this the users are even further incentivised because they are now in a reverse scenario than the hamster wheel in Model 1. They will never have to chase transaction parity after their initial acquisition unless usage dramatically drops.
Anyway these are just some initial thoughts about Plasma-nomics.
There are actually quite a few more things that I would like to add but I can’t be fucked typing anymore.
Please try to finds any holes in the logic and/or conceptual flaws. Of course this is all speculation and I have no idea what the devs actually have in mind. Nothing in the whitepaper about this. Maybe I got a bit too carried away with assumptions and speculation lol.