A Solution for Blockchain Scalability
The lack of scalability, meaning the blockchain is only capable of processing a few transactions per second, is a major bottleneck for blockchain technology to garner mass adoption. However, with only 5 transactions per second (tps) for Bitcoin and 12 transactions per second for , existing blockchain solutions are not competitive to centralized solutions like Visa as a payments system and AWS as cloud computing service. For example, with the growing popularity of CryptoKitties in 2017, it slowed down the Ethereum network significantly with just a few thousand users. This is certainly a concern for companies using Ethereum to power their services.
Currently, every computer maintaining Bitcoin and Ethereum network are working on the same public ledger. Every node has to process every single transaction. Adding more computers into the network improves only security but not efficiency. A blockchain trilemma is none of the mentioned blockchains can achieve scalability, security, and decentralization at the same time.
Bitcoin and Ethereum are networks security is provided by Proof-of-Work. Hundreds of thousands of computers and machines that specialize in mining around the world help to process transactions. As a P2P cash system / a world computer, Bitcoin and Ethereum are both secure and decentralized. However, they are not immediately scalable. So to improve scalability, a lot of solutions have been suggested. For example, BitcoinCash (fork of Bitcoin) increases block size to allowing the processing of more transactions in each block, while Lightning Network (second layer) utilized off-chain payment channels to reduce the burden on the main chain. Sharding is one of the most popular approaches in development by different blockchain projects including Ethereum, Zilliqa, Quarkchain, etc.
Sharding is a horizontal partitioning, a database design principle, that separates database servers to spread the load. It’s introduction is for blockchain to solve scalability issues and latency issues.
Implementing sharding in the blockchain, means the network separates into different teams (shards). So the shards can process transactions in parallel. Similarly, each node will have only part of the data on the blockchain, not the entire information. As a result, more transactions can be processed at the same time. For example, imagine a network of 1,000 nodes; one may divide the network into 10 shards each composed of 100 nodes. The speed should increase by 10-fold.
The way to assign nodes into different shards is the key. A random sampling of validators on each shard is suggested for Ethereum’s sharding solution. Sufficient randomness can ensure that validators will not know which shard they will get in advance. Also, it requires ⅔ of all validators on a shard to confirm the legitimacy of a block.
Apart from this, the minimum size of a shard should be under limits to reduce the possibility that malicious nodes that could assign to the same shard. With the above strategies, there will not be a sacrifice in the security of the network for the tremendous improvement on efficiency.
Sharding is commonly used in a privately owned system. It can horizontally spread the load for a database or search engine. However, implementing it into a public blockchain is still a challenge. So, the nature of decentralization and transparency makes it difficult to maintain security. Apart from single shard attacks, developers face further issues such as cross-shard communication.
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