The growing number of implementations of blockchain systems stands in stark contrast with still limited research on a systematic comparison of performance characteristics of these solutions. Such research is crucial for evaluating fundamental trade-offs introduced by novel consensus protocols and their implementations. These performance limitations are commonly analyzed with ad-hoc benchmarking frameworks focused on the consensus algorithm of blockchain systems. However, comparative evaluations of design choices require macro-benchmarks for uniform and comprehensive performance evaluations of blockchains at the system level rather than performance metrics of isolated components. To address this research gap, we implement Gromit, a generic framework for analyzing blockchain systems. Gromit treats each system under test as a transaction fabric where clients issue transactions to validators. We use Gromit to conduct the largest blockchain study to date, involving seven representative systems with varying consensus models. We determine the peak performance of these systems with a synthetic workload in terms of transaction throughput and scalability and show that transaction throughput does not scale with the number of validators. We explore how robust the subjected systems are against network delays and reveal that the performance of permissoned blockchain is highly sensitive to network conditions.
翻译:229. 然而,对设计选择的比较性评价要求系统一级对链条进行统一和全面的绩效评价,而不是对孤立部件进行绩效衡量,因此,对设计选择进行宏观基准评估,要求系统一级对链条进行统一和全面的绩效评价,而不是对孤立部件进行绩效衡量;为解决这一研究差距,我们实施Gromit,这是一个分析链条系统的一般框架。Gromit将每个正在试验中的系统作为客户向验证人进行交易的交易结构对待。我们利用Gromit进行迄今为止最大的链条研究,涉及七个具有不同共识模式的代表性系统。我们确定这些系统在交易量和可扩展性方面综合工作量的高峰性业绩,并表明通过量与验证人的数量相比并不相称。我们探索受管制的系统在网络上是否可靠,并揭示渗透的链条的性能对网络条件非常敏感。