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首页> 外文期刊>IEEE Transactions on Knowledge and Data Engineering >BestPeer++: A Peer-to-Peer BasedLarge-Scale Data Processing Platform
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BestPeer++: A Peer-to-Peer BasedLarge-Scale Data Processing Platform

机译:BestPeer ++:基于对等的大型数据处理平台

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摘要

The corporate network is often used for sharing information among the participating companies and facilitating collaboration in a certain industry sector where companies share a common interest. It can effectively help the companies to reduce their operational costs and increase the revenues. However, the inter-company data sharing and processing poses unique challenges to such a data management system including scalability, performance, throughput, and security. In this paper, we present BestPeer++, a system which delivers elastic data sharing services for corporate network applications in the cloud based on BestPeer—a peer-to-peer (P2P) based data management platform. By integrating cloud computing, database, and P2P technologies into one system, BestPeer++ provides an economical, flexible and scalable platform for corporate network applications and delivers data sharing services to participants based on the widely accepted pay-as-you-go business model. We evaluate BestPeer++ on Amazon EC2 Cloud platform. The benchmarking results show that BestPeer++ outperforms HadoopDB, a recently proposed large-scale data processing system, in performance when both systems are employed to handle typical corporate network workloads. The benchmarking results also demonstrate that BestPeer++ achieves near linear scalability for throughput with respect to the number of peer nodes.
机译:公司网络通常用于在参与公司之间共享信息,并在公司拥有共同利益的某些行业中促进协作。它可以有效地帮助公司降低运营成本并增加收入。但是,公司间的数据共享和处理给这种数据管理系统带来了独特的挑战,包括可伸缩性,性能,吞吐量和安全性。在本文中,我们介绍了BestPeer ++,该系统基于BestPeer(一种基于对等(P2P)的数据管理平台)为云中的企业网络应用程序提供弹性数据共享服务。通过将云计算,数据库和P2P技术集成到一个系统中,BestPeer ++为企业网络应用程序提供了经济,灵活和可扩展的平台,并根据广泛接受的按需付费业务模型向参与者提供数据共享服务。我们在Amazon EC2 Cloud平台上评估BestPeer ++。基准测试结果表明,当两个系统都用于处理典型的公司网络工作负载时,BestPeer ++的性能优于最近提出的大型数据处理系统HadoopDB。基准测试结果还表明,BestPeer ++相对于对等节点数,实现了接近线性的吞吐量扩展。

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