H. Sukhwani, J. M. Martínez, Xiaolin Chang, Kishor S. Trivedi, A. Rindos
{"title":"许可区块链网络(Hyperledger Fabric) PBFT共识过程的性能建模","authors":"H. Sukhwani, J. M. Martínez, Xiaolin Chang, Kishor S. Trivedi, A. Rindos","doi":"10.1109/SRDS.2017.36","DOIUrl":null,"url":null,"abstract":"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","PeriodicalId":6475,"journal":{"name":"2017 IEEE 36th Symposium on Reliable Distributed Systems (SRDS)","volume":null,"pages":null},"PeriodicalIF":0.0000,"publicationDate":"2017-09-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"279","resultStr":"{\"title\":\"Performance Modeling of PBFT Consensus Process for Permissioned Blockchain Network (Hyperledger Fabric)\",\"authors\":\"H. Sukhwani, J. M. Martínez, Xiaolin Chang, Kishor S. Trivedi, A. Rindos\",\"doi\":\"10.1109/SRDS.2017.36\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"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\",\"PeriodicalId\":6475,\"journal\":{\"name\":\"2017 IEEE 36th Symposium on Reliable Distributed Systems (SRDS)\",\"volume\":null,\"pages\":null},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2017-09-01\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"279\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"2017 IEEE 36th Symposium on Reliable Distributed Systems (SRDS)\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/SRDS.2017.36\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"2017 IEEE 36th Symposium on Reliable Distributed Systems (SRDS)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/SRDS.2017.36","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
Performance Modeling of PBFT Consensus Process for Permissioned Blockchain Network (Hyperledger Fabric)
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