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Synergy: Sharing-Aware Component Composition for Distributed Stream Processing Systems

机译:协同作用:分布式流处理系统的共享感知组件组成

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摘要

Many emerging on-line data analysis applications require applying continuous query operations such as correlation, aggregation, and filtering to data streams in real-time. Distributed stream processing systems allow in-network stream processing to achieve better scalability and quality-of-service (QoS) provision. In this paper we present Synergy, a distributed stream processing middleware that provides sharing-aware component composition. Synergy enables efficient reuse of both data streams and processing components, while composing distributed stream processing applications with QoS demands. Synergy provides a set of fully distributed algorithms to discover and evaluate the reusability of available data streams and processing components when instantiating new stream applications. For QoS provision, Synergy performs QoS impact projection to examine whether the shared processing can cause QoS violations on currently running applications. We have implemented a prototype of the Synergy middleware and evaluated its performance on both PlanetLab and simulation testbeds. The experimental results show that Synergy can achieve much better resource utilization and QoS provision than previously proposed schemes, by judiciously sharing streams and processing components during application composition.
机译:许多新兴的在线数据分析应用程序需要对数据流实时应用连续查询操作,例如相关性,聚合和过滤。分布式流处理系统允许网络内流处理实现更好的可伸缩性和服务质量(QoS)提供。在本文中,我们介绍了Synergy,这是一种分布式流处理中间件,提供共享感知的组件组成。协同功能可有效重用数据流和处理组件,同时组成具有QoS要求的分布式流处理应用程序。 Synergy提供了一组完全分布式的算法,用于在实例化新的流应用程序时发现和评估可用数据流和处理组件的可重用性。对于QoS提供,Synergy执行QoS影响预测,以检查共享处理是否会导致当前正在运行的应用程序违反QoS。我们已经实现了Synergy中间件的原型,并在PlanetLab和模拟测试平台上评估了其性能。实验结果表明,通过在应用程序编写过程中明智地共享流和处理组件,Synergy可以比以前提出的方案实现更好的资源利用率和QoS提供。

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