Note: I (Onur) am a mentor at the Token Engineering track, and am here to present challenges to hackers who would like to work on existing problems on Ethereum. Join the Telegram group to get involved; you can also contact me directly.
Demand for cryptocurrencies has a heterogeneous distribution around the globe, causing 2-3x the change in gas price every day. See this ethresearch post.
The challenges presented in the Token Engineering track involve designing complex systems to model and simulate the economic phenomena described above. To this end, possible challenges can be separated into two parts:
- Modeling the problem: The goal is to capture the phenomena with models, so that their reaction to real life input is as close to reality as possible. You must have a good model of the complex system before you have any chance of testing a possible solution.
The first part of the challenge is to model an agent based model with an accurate global distribution of circadian rhythms. The agents should have distribution of willingness-to-pay that results in a reasonable demand curve. They should submit transactions based on a daily schedule, with a higher probability during the most active hours corresponding to their timezone. The baseline rate of incoming transactions should be close to Ethereum’s capacity, in order to simulate the current situation realistically. With these initial conditions, the load profile seen above should emerge.
- Modeling the solution: Once the problem of gas price volatility is identified and modeled successfully, the next step is to solve it. This can be achieved in a variety of ways. Hackers will propose and test their solutions to prove its effectiveness.
The second part of the challenge is to implement a “reservation mechanism” for the agents. This mechanism will work like a futures contract—it will allow users to set the gas price for their transactions in advance, or in other words, reserve space in future blocks. However, we won’t call it a futures contract, because they require the enforceability of law (which doesn’t exist in the context of blockchains). However, the hacker will assume that the contract is binding and enforceable for simplicity’s sake, and simulate the gas market in the presence of such contracts.
Modeling and simulation will be done using cadCAD, a tool for complex systems design recently open-sourced by BlockScience.
See the problem statement for a detailed explanation of the gas market and the problem of volatility.
Built With
- cadcad
- python
