Efficient transaction processing is the key to improving blockchain network throughput and solving blockchain scalability issues. This article explains the basics, principles, common types, and potential benefits of parallelization.
Parallelization (parallel transaction execution) is a method of handling multiple tasks simultaneously. Parallelization is closely related to the concept of parallel computing in computer science. Parallel computing refers to executing multiple processes simultaneously.
Network data is organized through parallelization, allowing multiple transactions to be verified simultaneously rather than processed one by one in sequence. The task of executing transactions is distributed across multiple nodes. Each node handles various parts of the transaction volume separately, which helps speed up processing times and alleviate network congestion.
In parallel transaction processing, the network can check various potential states simultaneously, each state representing the result of validating a specific set of transactions. This allows the network to assess the potential impact of transactions before they are officially recorded on the ledger. After the evaluation, the nodes agree on a common state, displaying the unified results of parallel verification.
Blockchain parallelization is divided into two major types, namely optimistic parallelization and state access parallelization.
1.Optimistic parallelization. In the optimistic parallel execution model, the network skips the initial sorting stage and directly processes transactions simultaneously. This approach assumes that most transactions in the queue are independent and uses the same approach to recheck and correct any transactions that are related after the transaction is executed. That is, if transactions are initially determined to be unrelated, but are later found to affect each other, the system will adjust those transactions to ensure the data remains accurate.
2.State access parallelization. In the state access parallel execution model, the network initially classifies transactions based on their impact on the network state. Various impacts include interactions with specific smart contracts or accounts, which help determine which transactions can be processed in parallel without conflict. Transactions that do not interact can be executed simultaneously. In contrast, transactions that affect similar state factors need to be processed in a specific order, with the ordering priority determined by gas fees.
Transaction-level parallelization means that multiple transactions can be processed simultaneously. This increases network throughput and increases transactions per second (TPS). Furthermore, transaction-level parallelization reduces the time required for transaction confirmation and improves the overall responsiveness of the network. This type of parallelization is ideal for high-demand blockchains where fast processing times must be maintained.
However, there are also difficulties with transaction-level parallelization. For example, processing transactions simultaneously is highly dependent on data. The output of one transaction may affect another transaction, which requires complex data management strategies to ensure data consistency and reliability.
Block-level parallelization means that block creation and verification are performed simultaneously, aiming to improve network scalability. By processing multiple blocks simultaneously, this approach helps the blockchain accommodate more transactions and prevents potential network congestion.
However, block-level parallelism needs to be implemented carefully to avoid affecting the security of the blockchain. In addition, block-level parallelization requires more computing resources, thereby increasing the hardware requirements for network nodes. This may limit some users’ participation in the network, negatively impacting its decentralization and accessibility.
Smart contract parallelization refers to the parallel execution of multiple smart contracts. This can improve the performance of decentralized applications (DApps), enhancing their scalability and responsiveness.
There are multiple mechanisms to facilitate parallel execution of smart contracts. For example, optimistic aggregation executes transactions off-chain and only interacts with the blockchain when transactions are confirmed, reducing the load on the main chain. Validium scaling solutions for Ethereum combine zero-knowledge proofs with off-chain computation to provide scalability and privacy for smart contract applications.
Distributing tasks to multiple nodes can shorten transaction execution time and increase transaction processing speed. Networks that implement parallelization tend to be more efficient than networks that operate on a sequential processing model.
Parallelization distributes transaction verification to multiple nodes to solve the scalability issue of the blockchain. This speeds up the process and also supports horizontal scaling. Horizontal expansion means that the network adds or removes nodes as demand changes.
Parallelization distributes transactions to subgroups of nodes, thereby reducing handling fees. This is less expensive than processing transactions sequentially, where each transaction is verified by each node. In addition, increasing transaction speed can reduce competition between nodes and further reduce transaction fees.
Parallelization is a way to process multiple transactions at the same time. Its many advantages include increasing transaction processing speed, improving scalability and reducing handling fees. In the future, parallelization can be combined with other scaling solutions such as sharding to further expand the scalability of blockchain networks.
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