Ethereum: Why aren’t block hashes used directly as complexity estimates?

The Case Against Direct Block Hash Scores: Understanding Ethereum’s Difficulty Function

As one of the pioneers of blockchain technology, Ethereum has always been innovative in its approach to managing the complex mathematical problems required for a secure and decentralized network. One such aspect is the use of difficulty functions to optimize block creation rates. However, there are several reasons why direct block hash scores aren’t used as initial scores for difficulty purposes on Ethereum. In this article, we’ll delve into these reasons and explore alternative approaches.

The Current Implementation: Difficulty Functions and Block Hashes

On Ethereum, a difficulty function is applied to the hash of each new block before it’s added to the blockchain. This process is known as “difficulty adjustment.” The difficulty function takes the current target difficulty level (e.g., 4,000) and adjusts it in increments based on the number of successful blocks that have already been mined. The adjusted target difficulty level is then used to calculate the block reward and validate transactions.

The hash of each new block serves as an initial score for the difficulty function. This can be misleading, as it does not account for factors like block size, transaction complexity, or network congestion. For instance, a block with a low hash value but high transaction volume might still have a relatively low difficulty adjustment. Conversely, a block with a high hash value but lower transaction volume might receive an adjusted difficulty score that’s more challenging.

Why Block Hashes Aren’t Instant Scores

One primary reason Ethereum does not use direct block hash scores is to prevent over-optimization and ensure the network remains resilient. By adjusting the target difficulty based on existing blocks, the network can:

• Prevent a “block glut”: When an adjustment is too high, it might cause an explosion of new blocks with identical hashes, leading to congestion and reduced network performance.

• Encourage diversity in block rewards: A fixed hash score does not incentivize miners to vary their block sizes or transaction complexity, which can result in a more diverse set of block rewards.

• Avoid “hash collision” issues

  : By using the previous block’s hash as an initial score, Ethereum avoids potential collisions where two blocks with identical hashes are added simultaneously.

Alternative Approaches: Why Not Just Add Block Hashes?

While adding all block hashes together might seem appealing at first glance, it has several drawbacks:

• Computational overhead: Calculating and storing the sum of all block hashes would require significant computational resources.

• Difficulty adjustment complexity: The difficulty function is already complex; simply adding a hash to each new block does not account for other factors that influence difficulty adjustments (e.g., transaction volume, network congestion).

• Scalability limitations

  : A simple addition approach would strain the network’s capacity and potentially lead to scalability issues.

Conclusion

In conclusion, Ethereum’s implementation of difficulty functions with adjusted target difficulties is a deliberate design choice aimed at optimizing block creation rates while preventing over-optimization and ensuring network resilience. While direct block hash scores might seem appealing, they have several drawbacks that make them less desirable than the current approach. The use of block hashes as initial scores encourages diversity in block rewards, prevents “block glut,” and avoids potential collision issues. As the Ethereum network continues to evolve and mature, it’s likely we’ll see further innovations in difficulty function design, exploring alternative approaches like hash-based scoring or incorporating additional factors into the process.