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In our previous series, we covered the following 12 articles:
This article series provides the concluding articles where we will briefly touch on a few fascinating areas, including cross-blockchain interoperability, technology fusion, and the convergence between blockchain, Artificial Intelligence/Machine Learning, and Internet of Things.
Facing the challenges of Ethereum and blockchain
There are quite a few challenges that Ethereum and blockchain are facing. We will go through them in the following sections.
Consensus protocol and scalability
As we discussed in our earlier series, Deep Research on Ethereum, there are several active work and research streams in the Ethereum community racing to solve Ethereum's scalability issues. Obviously, the Ethereum ecosystem has evolved considerably since it was invented 4-5 years ago. However, for the mainstream adoption of Ethereum and blockchain technology in general, scalability is the most pressing issue. The solution to the scalability issue holds the key to making Ethereum sink or swim.
Let's recap on the current state of scalability challenges and analyze various approaches and activities in improving scalability in Ethereum:
- Scalability issues in Ethereum: In Ethereum and blockchain, scalability occurred because every transaction needs to be processed and verified by all the nodes in the decentralized network. For the network to agree on the true state of the blockchain network, there are consensus protocols involved which allow the network of untrusted nodes to reach consensus. In general, blockchain compromises scalability and throughput in favor of decentralization and the security of the network. In this article, we'll take a step back and discuss the common challenges that are faced in scaling Ethereum.
In the abstract sense, when a transaction happens, it is sent to the network and relayed to all the network nodes. It will be packaged into a block, which will be added to the blockchain by the mining node, and then verified by all the nodes. The whole process involves totally uncoordinated, but largely interdependent, activities to make a transaction recorded and secured in the network. It involves the communication of transactions and blocks, proof of the transaction's validity and verification of it, and an agreement on the finality of the transactions. Think of Ethereum as a heart valve. At its current capacity, transactions are pumped in and out at a slow and steady pace. The network is operating as expected. But as transaction volume picks up, or any part of the network becomes clogged, the system becomes inadequate for running critical business and finance operations.
Simply adding network nodes won't help at all. Solutions such as increasing block size or packaging more in a block have their limits. In our previous articles ( Horizontal Scaling versus Vertical Scaling in Distributed Systems & How to Scale up Ethereum Blockchain Applications & Review of scaling solutions for Ethereum), we discussed the block size increase solution. There are some proposals to reexamine the block structure and Merkle tree, with an intention to be able to effectively package more transactions in a block. It may be worth reading. Such solutions may help in the short term, but they alone won't fundamentally address these issues. There were solutions for increasing the block creation's frequency that didn't fly, simply due to the fact they may cause long finality and instability of the blockchain. That leaves most of the focus on proof, verification, and finality.
- Shardingand Layer 1 solutions: As we discussed in our other article, the Ethereum community has settled into a multi-pronged strategy in addressing scalability through the Ethereum 2.0 roadmap. Shifting to a Proof-of-Stake(PoS) consensus with Casper CBC is the ultimate goal. In the short term and as a tactical step, Ethereum is moving to a hybrid PoS and Proof-of-Work(PoW) model which seems to be a practical and prudent approach.
Ethereum sharding is the audacious attempt to address the fundamental issues with blockchain scalability. It intends to find a scalable solution without compromising network security and decentralization, two tenets of blockchain technology. Sharding is not a new concept and has been proven effective in managing large distributed database systems. The success with sharding in the traditional world comes from two factors: one is that the solution itself typically involves a central mediator or intermediary to make sharding and aggregation coordination, while the other is that software vendors have a central authority or governance structure in making sharding solution decisions, and deciding where to compromise and what subset of the issues to address and where to market.
The complexity and risks in implementing Ethereum sharding increase immensely. Not only will the blockchain and world state be sharded, but the entire decentralized peer-to-peer network will be grouped into different shards as well. The complexity lies in enforcing data and network security while being able to coordinate those transaction activities and aggregate data and transactions across blockchain data and network segments. For that purpose, Ethereum Casper introduces the beacon chain layer as the decentralized alternative to the central mediator in the traditional sharding implementation. A mix of PoW and PoS consensus protocol, as well as the finality solution of Casper FFG, will certainly add to the complexity of sharding implementation. How it works is still largely a work in progress.
- Off-chain computation with Zero-Knowledge Succinct Non-Interactive Argument of Knowledge and multiparty computation: Ethereum is envisioned as the world computer, but people quickly realized that, in the Ethereum architecture's current form, there are huge expenses associated with that vision and the consequence in scalability and throughput this has caused. One of those is computations. Another one is on-chain storage. We talked a little about zk- SNARKs in our earlier articles. This is another promising strategy that offloads expensive encryption computation out of the Ethereum Virtual Machine(EVM) to third-party verifiers, without compromising privacy and security, to improve scalability and throughput in Ethereum. Vitalik thinks that, by using zk-SNARKs to mass-validate transactions, we can actually scale asset transfer transactions on Ethereum to about 500 transactions per second. We have seen such success in Zcash. It is one of the areas the Ethereum community is closely watching. More research and prototypes have yet to be seen before we can see a clear roadmap or a future implementation.
- Multiparty computation (MPC) is another area that may have the potential for addressing privacy and scalability issues. In an MPC model, a set of participants, P1, P2, ..., Pn, are assigned a subset of private data, D1, D2, ..., Dn, respectively. The participants want to compute the value of a public function on that private data while keeping their own inputs secret. While pairing with blockchain, the subset of blockchain data (mainly the reference to the public blockchain), will be stored privately in some kind of distributed hash table(DTH) within each MPC node.
The following steps explain the process flow for some MPC blockchains such as Platon:
- Deploy the smart contract to the blockchain.
- Invoke the smart contract function by providing computation algorithm parameters.
- The computation task will distribute the contract to an off-chain MPC network.
- The MPC nodes will verify the computation and generate the required proof.
- The on-chain nodes will broadcast the result and proof.
- The block producers verify the proof.
- The verified result will be returned to the user through a smart contract.
- The miner will get coin as an economic reward.
The computation is offloaded and done securely through the coordination of all the MPC nodes, without anyone knowing anything from other MPC nodes. The idea behind this is that, by offloading computations out of the main chain, it will stay leaner and more scalable.
- Layer 2 solutions: There are discussions in the Ethereum community and Ethereum 2.0 roadmap about reexamining Ethereum's blockchain data structure, as well as the storage model. Hopefully, a solution will be created to make the Ethereum client stateless and leverage it more for enforcing security and integrity. A good compromise would be to offload those to Layer 2 or off-chain solutions.
We will continue to see Layer 2 scaling solutions take shape in Ethereum. We talked about state channel solutions with Raiden and side-chain solutions with Plasma in our earlier articles and discussed how the Layer 2 solution would work. As the Ethereum ecosystem evolves, and more and more transactions need to be processed, it definitely makes much more sense to explore the Layer 2 solutions. Their purpose is to offload expensive computations and transaction processing out of Mainnet and leverage Ethereum as the root chain for security guarantees and enforcement. State channels, as the perfect solution for micropayments, will continue to flourish in the payment space. Plasma, as the side-chains for many different verticals, will probably be the main avenue for Ethereum to expand beyond the finance, banking, and payment industry.
In our next article ( UI/UX and Design Thinking for Ethereum Blockchain Development), we discuss how to use UI/UX and design thinking best practices while building Ethereum blockchain applications.
This article is written in collaboration with Brian Wu who is a leading author of “Learn Ethereum: Build your own decentralized applications with Ethereum and smart contracts” book. He has written 7 books on blockchain development.
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