A decade after the first block was generated on July 30, 2015, Ethereum’s roadmap has a renewed sense of direction and purpose.
Sure, the recent price increase helps a lot, but after years of mucking around with scaling via L2s, the Ethereum L1 finally has a credible path to maximal scaling while preserving maximal decentralization.
The TL;DR is that the gas limit and transactions per second (TPS) will increase multiple times a year from here on out. Validators will switch from reexecuting transactions to simply verifying zero-knowledge (ZK) proofs, enabling the base layer to hit 10,000 transactions per second.
The L2s will scale up in concert to process hundreds of thousands, if not millions of TPS, and a new type of L2 called “native rollups” will act like programmable shards of a unified blockchain offering the same security as the base layer.
While these proposals are yet to be signed off on by the governance processes, they build on ideas Ethereum creator Vitalik Buterin began exploring in 2017 and are being championed by high-profile Ethereum Foundation researcher Justin Drake. At EthCC earlier this month, Drake said:
“We’re at this inflection point for Ethereum scaling. And in particular, I have conviction that we will enter a gigagas era for the L1…. that’s roughly 10,000 TPS. And the key unlock for the gigagas era is zkEVMs and real time proving.”
Drake wants the ecosystem to hit 10 million TPS within 10 years, and no single blockchain can achieve that level of throughput. That means that horizontal scaling, using a “network of networks” — each L2 with different use cases, tradeoffs and benefits — is the only way to scale the ecosystem to the needs of the entire world.
(Jump straight to the zkEVM roadmap to 10K TPS explainer if you are already familiar with the background and rationale.)
Why has Ethereum L1 been unable to scale?
While other blockchains use greater hardware and computing power to scale up throughput, Ethereum has always had an ideological, some would say utopian, fixation on decentralization.
From the point of view of ETH maxis, “data center chains” like Solana have multimillion-dollar centralized points of failure that a government could target to censor transactions. Even chains with lower hardware specs, like Sui, have prohibitive costs and bandwidth requirements that impact decentralization.
Ethereum can run on a bunch of Raspberry Pis. These low specs enable “home stakers” to participate in a network of 15,000-16,000 public nodes and 1 million validators. As a result, it’s almost impossible to censor transactions and the network is resilient against attacks. Even after 50%-70% of the network complied with US government sanctions on Tornado Cash, the little guys kept confirming those transactions.
The trade-off is the network is very slow and currently processes around 18-20 transactions per second compared to Solana’s 1,500 TPS.
Blockchains are horribly inefficient by design — a bit like a Google spreadsheet that makes every computer with a copy recalculate the figures before updating a cell.
“They basically want anyone to be able to keep up with the chain and reexecute the transactions,” explains Uma Roy, co-founder of ZK-proofs specialist Succinct Labs. “That means that you can’t just have an arbitrarily high amount of transactions because there’s overhead from this reexecution.”
The inability to scale the L1 enough while preserving decentralization forced Ethereum to adopt the much criticized L2 roadmap in 2020.
Zero-knowledge proofs solve blockchain trilemma
Buterin coined the phrase the “blockchain trilemma” to describe how difficult it is to achieve security, scalability and decentralization all at once in a blockchain network. Every scaling proposal worked on any two of the three properties, but came at the cost of the third.
Until now.
Zero-knowledge proofs, which Drake aptly describes as “moon math,” are able to prove mathematically that a bunch of complicated transactions have been performed correctly without revealing what those transactions are.
While generating a proof is difficult, verifying it’s correct is fast and easy.
So, instead of getting a bunch of underpowered Raspberry Pis to laboriously reexecute every single transaction, the plan is to get those validators to just check the math in a tiny ZK-proof.
“Instead of having people reexecute stuff, you just give them a proof that something happened,” explains Roy. “And now anyone can verify the proof, and they don’t have to redo the computation.”
Forget Raspberry Pis…
cointelegraph.com