An Automated Customization and Performance Profiling Framework for Permissioned Blockchains in a Virtualized Environment The permissioned blockchains have demonstrated their potential to provide trustworthy and security services in various industrial scenarios, especially in the Cloudbased virtualized environments. To customize the configuration of a blockchain application, an operator needs the performance characteristics of a blockchain network in different Cloud environments. However, manually profiling the performance characteristics of a blockchain network is very timeconsuming. Therefore, in this paper, we propose a BlockchaIninfRAstructure CustomIzation and AutoprofiLing (BIRACIAL) framework to automate the whole process of blockchain deployment and performance profiling. Based on the profile and performance requirements of a blockchain application, the framework aims to plan the virtual infrastructure for permissioned blockchain, to automate the provision of the required infrastructure, to deploy the customized permissioned blockchain, and to enable continuous monitoring of blockchain performance. Our evaluation results show that the proposed framework can achieve automated deployment of different permissioned blockchain networks under certain overheads. The performance profiling results can be used to compare and select the appropriate blockchain platforms and consensus algorithms.

Performance modeling and analysis of a Hyperledgerbased system using GSPN Abstract   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 Generalized Stochastic Petri Nets (GSPN). This model decomposes a transaction flow into multiple phases and provides a simulationbased 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 realtime system to validate the proposed model and approaches.