论文标题
执行订单验证区块链的交易视角
A Transactional Perspective on Execute-order-validate Blockchains
论文作者
论文摘要
智能合约使区块链系统能够从简单的加密货币平台（例如比特币）演变为一般的交易系统，例如以太坊。满足新兴业务需求的餐饮，在HyperLeDger Fabric中提出了一种名为“执行订单越野”的新体系结构，以支持并行交易并改善区块链的吞吐量。但是，这种新架构可能在序列化时会导致许多无效的交易。由于数据处理以外的其他因素（例如加密和共识），因此块形成率固有地限制了，因此该问题进一步夸大了。 在这项工作中，我们提出了一种通过减少无效的交易来改善区块链的吞吐量来增强执行订单质量体系结构的新颖方法。我们的方法灵感来自现代数据库系统中最新的乐观并发控制技术。与采用数据库的预防方法的现有区块链相反，该方法可能会流产可序列化的交易，我们的方法在理论上是更细粒度的。具体而言，在订购之前，不可审理的交易被中止，其余交易保证是可序列化的。为了进行评估，我们分别在两个区块链中实施我们的方法，在HyperLeDger织物之上的Fabricsharp和FastFabricsharp在FastFabric上。我们将Fabricsharp与香草织物和三个相关系统的性能进行了比较，其中两个分别用数据库中的一种标准和一种最先进的并发控制技术实现。结果表明，与几乎所有实验场景中的其他系统相比，面料的吞吐量高25％。此外，FastFabricsharp对FastFabric的改进高达66％。
Smart contracts have enabled blockchain systems to evolve from simple cryptocurrency platforms, such as Bitcoin, to general transactional systems, such as Ethereum. Catering for emerging business requirements, a new architecture called execute-order-validate has been proposed in Hyperledger Fabric to support parallel transactions and improve the blockchain's throughput. However, this new architecture might render many invalid transactions when serializing them. This problem is further exaggerated as the block formation rate is inherently limited due to other factors beside data processing, such as cryptography and consensus. In this work, we propose a novel method to enhance the execute-order-validate architecture, by reducing invalid transactions to improve the throughput of blockchains. Our method is inspired by state-of-the-art optimistic concurrency control techniques in modern database systems. In contrast to existing blockchains that adopt database's preventive approaches which might abort serializable transactions, our method is theoretically more fine-grained. Specifically, unserializable transactions are aborted before ordering and the remaining transactions are guaranteed to be serializable. For evaluation, we implement our method in two blockchains respectively, FabricSharp on top of Hyperledger Fabric, and FastFabricSharp on top of FastFabric. We compare the performance of FabricSharp with vanilla Fabric and three related systems, two of which are respectively implemented with one standard and one state-of-the-art concurrency control techniques from databases. The results demonstrate that FabricSharp achieves 25% higher throughput compared to the other systems in nearly all experimental scenarios. Moreover, the FastFabricSharp's improvement over FastFabric is up to 66%.
