The world’s second largest blockchain, Ethereum, is being scaled and the much-anticipated solution has encountered pitfalls.
Ethereum (ETH) Price Today – ETH / USD
Plasma has been at the forefront of this transition. The concept was accepted as the best bet for short-term scaling for the digital currency. Researchers have already developed five different versions of this protocol. However, within the distinct iterations, there is evidence that the work has slowed down.
As the concept slows, developers and others facing zk-snarks, a type of cryptography pioneered by Zcash as the way forward. Startups are starting to embrace the technology as it allows developers to separate the transactions into batches.
For instance, Gnosis, the prediction market platform is currently exploring the use of zk-snarks to reinforce a decentralized exchange in what is called snapp” (snark dapp). Also, pseudonymous developer, barrywhitehat, has used the technology in creating a roll-up that can be applied to Ethereum scaling on a broader sense.
Ethereum’s creator, Vitalik Buterin has written about the advantages of this approach. He also stated that it could be applied to more than five hundred transactions in the short term.
Issues at Devcon 4
During Ethereum’s annual developer conference, participants were excited about zk-snarks and its applications. There were seven tracks dedicated to the related systems and this technology. kelvin Fitcher, a plasma researcher at OmiseGo, termed the growing hype “snark-nado.”
CTO of Gnosis, Stefan George also spoke to Coindesk and explained that the approach is compelling because it has the potential to be more decentralized than plasma and is ready for deployment anytime soon.
“More and more people understand what the possibilities are. Even beyond zero-knowledge, it’s also a great scalability tool that Ethereum is missing, and we can use it without waiting.”
Pitfalls of plasma
Ethereum founder, Buterin and Joseph Poon, conceived the system last year in April. Ever since it was released, different iterations of this method have emerged. So many researches are also devoted to it as well. Each new iteration reveals a problem to be fixed, leading to a host of variants that run the tradeoffs in different manners.