Vitalik’s Study: Inequality-based Penalization Mechanism May Potentially Mitigate Validator Decentralization Issues

Vitalik recently increased the discussion on the issue of centralization among validators and published research results on the mechanism of collective punishment for validators. Historical data has proven that an unequal punishment mechanism can be used to incentivize validators to lean towards decentralized staking through economic means.

Table of Contents
Background: Ethereum Validator Centralization Issue
Unequal Punishment Mechanism
Introducing Common Punishments into the Unequal Punishment Mechanism
Vitalik’s Experiment Demonstrates Feasibility

Since the completion of the Ethereum merger, the role of validators has become increasingly important. They are responsible for tasks such as transaction sorting, block production, block verification, and consensus. To fulfill these tasks, validators need to stake 32 ETH and provide sufficient hardware resources, which has raised the participation threshold for users. As a result, most users stake their ETH with nodes such as Lido or Coinbase, leading to a serious centralization problem in the current Ethereum network.

After the London hard fork, Ethereum’s next important goal seems to be addressing the growing centralization issue among network validators. Vitalik and his partners at the Ethereum Foundation discussed this topic during their presentation at ETHTaipei, where they outlined several solutions that are currently being developed, including Verkle Trees, PBS, DVT, and rainbow staking.

Recommended Reading:
ETHTaipei | Next Steps for Ethereum’s London Hard Fork: PBS, Verkle Trees to Reduce Validator Centralization Issue
Reason for Recommendation: This article summarizes the four main improvement solutions that the Ethereum Foundation is currently working on to address the issue of validator centralization, providing insights into the Ethereum roadmap.

However, in addition to the existing methods, Vitalik recently published a study on the use of unequal punishment as an economic means to potentially reduce the issue of validator centralization.

Vitalik proposes a punishment scheme where if a validator behaves improperly (including accidentally) and operates abnormally, the more validators (measured by the total amount of ETH staked) exhibiting improper behavior simultaneously with that validator, the greater the punishment they will receive.

This theory is based on the assumption that centralized validator clusters (such as Lido) are more likely to make the same mistakes simultaneously. If there is a single large participant, any mistakes they make are more likely to be replicated across all validator accounts under their control, even if the ETH is distributed among many nominally independent accounts.

Through the design of an unequal punishment mechanism, the market can be incentivized to reduce excessively large validator clusters, thereby reducing the issue of validator centralization.

This design has already been implemented in the Ethereum network, but it is only applied in extreme error scenarios and rarely occurs in general situations. Therefore, Vitalik believes that if this mechanism is applied to more common punishments, such as missing an attestation due to disconnection or network delays, it may be more effective in achieving its purpose.

However, introducing this punishment mechanism for general errors would have a significant impact on the network and would require the preliminary proof of a hypothesis: whether different validators within the same validator cluster may have related causes for errors. In other words, it needs to be proven that validators within the same cluster are more likely to make errors simultaneously compared to randomly selected validators in the network.

If the answer to this question is negative, then the unequal punishment mechanism would not be feasible.

Vitalik conducted statistical analysis of past historical data by scripting and further divided the errors of missing attestations by validators into two categories to calculate more accurately and reach preliminary conclusions: concentrated validator clusters are indeed more likely to make errors simultaneously.

He also stated that in specific unequal punishment models, it is indeed possible to effectively reduce the advantage of concentrated validator clusters, imposing greater punishments on them when they make errors, without affecting small to medium-sized clusters of 10-300 validators and independent validators.

It is expected that this technical approach can improve the decentralization level of validators.

(Ethereum Releases 2024 Roadmap, Continues Advancing Towards a World Settlement Layer)