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Hyperledger Fabric: A Distributed Operating System for Permissioned Blockchains.

计算机科学 数字加密货币 模块化设计 分布式计算 灵活性(工程) 可扩展性 计算机安全 操作系统 统计 数学
作者
Elli Androulaki,Artem Barger,Vita Bortnikov,Christian Cachin,Konstantinos Christidis,Angelo De,David Enyeart,Christopher Ferris,Gennady Laventman,Yacov Manevich,S. Muralidharan,Chet Murthy,Binh T. Nguyen,Manish Sethi,Gari Singh,Keith Smith,Alessandro Sorniotti,Chrysoula Stathakopoulou,Marko Vukolić,Sharon Weed Cocco,Jason Yellick
出处
期刊:Cornell University - arXiv 被引量:229
标识
DOI:10.1145/3190508.3190538
摘要

Fabric is a modular and extensible open-source system for deploying and operating permissioned blockchains and one of the Hyperledger projects hosted by the Linux Foundation (this http URL). Fabric is the first truly extensible blockchain system for running distributed applications. It supports modular consensus protocols, which allows the system to be tailored to particular use cases and trust models. Fabric is also the first blockchain system that runs distributed applications written in standard, general-purpose programming languages, without systemic dependency on a native cryptocurrency. This stands in sharp contrast to existing blockchain platforms that require smart-contracts to be written in domain-specific languages or rely on a cryptocurrency. Fabric realizes the permissioned model using a portable notion of membership, which may be integrated with industry-standard identity management. To support such flexibility, Fabric introduces an entirely novel blockchain design and revamps the way blockchains cope with non-determinism, resource exhaustion, and performance attacks. This paper describes Fabric, its architecture, the rationale behind various design decisions, its most prominent implementation aspects, as well as its distributed application programming model. We further evaluate Fabric by implementing and benchmarking a Bitcoin-inspired digital currency. We show that Fabric achieves end-to-end throughput of more than 3500 transactions per second in certain popular deployment configurations, with sub-second latency, scaling well to over 100 peers.

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