论文标题
使用GSPN对基于超重机的系统的性能建模和分析
Performance Modeling and Analysis of a Hyperledger-based System Using GSPN
论文作者
论文摘要
作为一个高度可扩展的允许区块链平台，Hyperledger Fabric支持从治理到金融的广泛行业用例。在本文中，我们提出了一个模型，通过使用广义随机培养皿（GSPN）来分析基于高毛的系统的性能。该模型将事务流分解为多个阶段，并提供了基于模拟的方法，以获得系统延迟和吞吐量，并具有特定的到达率。基于此模型，我们分析了订购服务对系统性能的不同配置以找出瓶颈的影响。此外，提出了一种数学配置选择方法，以确定最大化系统吞吐量的最佳配置。最后，在运行系统上进行了广泛的实验，以验证提出的模型和方法。
As a highly scalable permissioned blockchain platform, Hyperledger Fabric supports a wide range of industry use cases ranging from governance to finance. In this paper, we propose a model to analyze the performance of a Hyperledgerbased system by using Generalised Stochastic Petri Nets (GSPN). This model decomposes a transaction flow into multiple phases and provides a simulation-based approach to obtain the system latency and throughput with a specific arrival rate. Based on this model, we analyze the impact of different configurations of ordering service on system performance to find out the bottleneck. Moreover, a mathematical configuration selection approach is proposed to determine the best configuration which can maximize the system throughput. Finally, extensive experiments are performed on a running system to validate the proposed model and approaches.
