Sui testnet wave-2: A look from the inside

On January 25th, 2023, P2P joined the Sui network testnet wave-2. We had also participated in the first wave of the testnet with the goal of understanding the node operation nuances of the Sui blockchain. The second testnet was a game played by validators and delegators to understand the network economics and staking specifics.

High-level overview of Sui economics specifics

Sui is a layer one blockchain focused on scalability, user and developer experience, and utilizes its own variant of the Move programming language. It allows for consensus to be forgotten in simple use cases, and transaction processing is parallelized.

In this article, we will briefly cover two elements of the Sui economy:

• Storage Fund
• Reference Gas Price Mechanism

Let’s start with the storage fund. It plays the role of a compensation buffer to reward validators for on-chain data storage. It is evenly staked to validators and a portion of staking rewards get reinvested back into the fund. This parameter influences the overall reward calculation. It starts relatively low in the beginning but its share steadily increases slowly along with the storage growth.

Another element influencing the validator rewards is a Reference Gas Price [RGP]. It represents the minimum price at which validators are willing to process transactions. For users, it plays the role of a guide when propagating transactions ensuring that gas prices close to the reference price will be executed appropriately. Every epoch, validators submit their quotes for RGP and the protocol chooses the 2/3's percentile by stake as the epoch reference price.

Staking rewards consist of stake subsidies and gas revenue. Subsidies are known for each epoch. For testnet-2 epoch, subsidies were equal to 0,01% * total stake (mainnet subsidies will differ from wave-2) making them relatively low compared to gas revenue. Validators could calculate expected gas revenue based on the selected RGP and on-chain activity. Each participant received random costs and had to select RGP to remain profitable but at a reasonable level to improve UX and maintain lower transaction costs for users.

Testnet overview

The Sui team has prepared a dashboard to track the progress of the validators during the testnet If validators selected an RGP that was equal to or lower than the final epoch RGP, they received a bonus point. Points were also assigned for maintaining positive profitability during the epoch. The score rules were changed after the 6th epoch to switch the behavior of participants during the game, so some data will be split in two groups: The first group from epoch 2 to epoch 6, and the second group from epoch 7 to epoch 31. The first two epochs were experimental and were not counted and we excluded them from the analysis.

Validator shares and costs varied during the testnet, resulting in different capabilities to remain profitable and get into the ⅔ percentile in RGP voting leading to a semi-random points distribution. The analytics below can bring some clarity to the actual activity of participants during the testnet.

Important note, validators could have different goals and strategies for the game, and the data below should not be taken as a representation of participation quality. We set the following goals for the testnet:

• To align with Sui economics specifics
• To understand the RGP selection process and build a reliable model to calculate it

We decided to prioritize the calculation precision and set our RGP quotes for each epoch with a targeted profitability margin of 5-15%. Our goal was to strike a balance between maintaining profitability without overpricing the user experience. It’s important to note that the logic for the mainnet may differ from that of the testnet.

Wave-2 Analytics

The economic conditions during the testnet changed every epoch, requiring validators to adjust their strategies in order to remain profitable. Out of the 41 validators, only 17 changed their RGP for 80% of the epochs during the testnet.

Profitability was an important part of the assessment, and the following breakdown shows the number of epochs in which each validator had positive profits. However, it is important to note that validators may have had different goals for the testnet. Nonetheless, over 50% of participants were able to make a profit in 80% of the epochs.

This chart shows the total margin of validators during the testnet. We can observe changes in behavior after the rule change that stopped punishing validators for not being in the ⅔ percentile with their RGP quotes.

Epoch 7-31 resulted in a more selective approach that takes profit into consideration.

In the following plots, we will display the standard deviation of each validator, which indicates how stable and precise their margin was. A lower standard deviation indicates more precise and consistent RGP quotes. For instance, if a validator quoted around 10% margin most of the time, their deviation would be low.

Another way to represent margin statistics is through the mean, total and median margin parameters, which also provide insights into validator behavior. This chart excludes extreme values that deviate from the average by more than 2.5 standard deviations. If all three parameters are similar, it indicates that a participant successfully targeted and maintained the margin. For instance, the mean, total and median parameters for P2P vary from 8 to 11 percent, falling within the selected 5-15 percent range that we aimed for internally beforehand.

Feel free to explore the spreadsheet with the data and graphs provided in the article.

For a more detailed picture we have compiled a heatmap showing the deviation from each validator’s optimal RGP for each epoch. We assumed that the validator's optimal RGP is calculated based on a random margin value within the  5-15% interval. We can infer that In the second part of the game, validators moved towards profitability and calculated their RGP more precisely.

Summary

The Sui testnet-2 was an intriguing experiment that contributed to a better understanding of staking economics and network specifics.

• Validators were able to experiment with different calculations to develop their own strategies during the game
• The main purpose of RGP is to maintain a balance between validator profitability and end-user experience
• Using an optimal margin level for calculating RGP may be an effective way to achieve both goals
• Calculating RGP involves multiple parameters that can fluctuate and may be difficult to predict in advance leaving room for modeling improvements over time
• Participating in a testnet is an excellent opportunity to familiarise with network specifics and prepare for mainnet launch.

If you’re interested in staking or in launching a white-label validator with us, feel free to express interest on p2p.org. We’ll keep you informed about key milestones and help you get onboarded to the mainnet from the very beginning.

Special thanks to Alexey Toporov for aggregating the data and creating the charts for the article.

About P2P Validator

P2P Validator is a world-leading staking provider with the best industry security practices AAA SR-rating and proven expertise. We provide comprehensive due diligence on digital assets and offer only top-notch staking opportunities. At the time of the latest update, more than 1 billion USD value is staked with P2P Validator by over 40,000 delegators across 40+ networks. We have successfully participated in Sui testnet-1 & testnet-2 to become the most comprehensive partner for staking and branded node maintenance.