GATES: a grid-based middleware for processing distributed data streams

Liang Chen, Kolagatla Reddy, G. Agrawal
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引用次数: 70

Abstract

Increasingly, a number of applications rely on, or can potentially benefit from, analysis and monitoring of data streams. Moreover, many of these applications involve high volume data streams and require distributed processing of data arising from a distributed set of sources. Thus, we believe that a grid environment is well suited for flexible and adaptive analysis of these streams. This paper reports the design and initial evaluation of a middleware for processing distributed data streams. Our system is referred to as GATES (grid-based adaptive execution on streams). This system is designed to use the existing grid standards and tools to the extent possible. It flexibly achieves the best accuracy that is possible while maintaining the real-time constraint on the analysis. We have developed a self-adaptation algorithm for this purpose. Results from a detailed evaluation of this system demonstrate the benefits of distributed processing, and the effectiveness of our self-adaptation algorithm.
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GATES:用于处理分布式数据流的基于网格的中间件
越来越多的应用程序依赖于或可能受益于数据流的分析和监控。此外,许多此类应用程序涉及大容量数据流,需要对来自分布式源集的数据进行分布式处理。因此,我们认为网格环境非常适合对这些流进行灵活和自适应的分析。本文报道了一个用于处理分布式数据流的中间件的设计和初步评估。我们的系统被称为GATES(基于网格的自适应流执行)。本系统旨在尽可能使用现有的网格标准和工具。它灵活地在保持分析的实时约束的同时实现可能的最佳精度。我们为此开发了一种自适应算法。对该系统的详细评估结果表明了分布式处理的优点,以及我们的自适应算法的有效性。
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