Performance Modeling of PBFT Consensus Process for Permissioned Blockchain Network (Hyperledger Fabric)

被引：268

作者：

Sukhwani, Harish ^{[1
]}

Martinez, Jose M. ^{[1
]}

Chang, Xiaolin ^{[2
]}

Trivedi, Kishor S. ^{[1
]}

Rindos, Andy ^{[3
]}

机构：

[1] Duke Univ, Dept Elect & Comp Engn, Durham, NC 27708 USA

[2] Beijing Jiaotong Univ, Sch Comp & Informat Technol, Beijing, Peoples R China

[3] IBM Corp, Armonk, NY 10504 USA

来源：

2017 IEEE 36TH INTERNATIONAL SYMPOSIUM ON RELIABLE DISTRIBUTED SYSTEMS (SRDS) | 2017年

关键词：

blockchain; hyperledger fabric; PBFT; performance modeling; Stochastic reward nets;

D O I：

10.1109/SRDS.2017.36

中图分类号：

TP18 [人工智能理论];

学科分类号：

081104 ; 0812 ; 0835 ; 1405 ;

摘要：

While Blockchain network brings tremendous benefits, there are concerns whether their performance would match up with the mainstream IT systems. This paper aims to investigate whether the consensus process using Practical Byzantine Fault Tolerance (PBFT) could be a performance bottleneck for networks with a large number of peers. We model the PBFT consensus process using Stochastic Reward Nets (SRN) to compute the mean time to complete consensus for networks up to 100 peers. We create a blockchain network using IBM Bluemix service, running a production-grade IoT application and use the data to parameterize and validate our models. We also conduct sensitivity analysis over a variety of system parameters and examine the performance of larger networks.

引用

页码：253 / 255

页数：3

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