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Processing Flows of Information: From Data Stream to Complex Event Processing

机译:信息处理流程:从数据流到复杂事件处理

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An increasing number of distributed applications requires processing continuously flowing data from geographically distributed sources at unpredictable rate to obtain timely responses to complex queries. Examples of such applications come from the most disparate fields: from wireless sensor networks to financial tickers, from traffic management to click-stream inspection. These requirements led to the development of a number of systems specifically designed to process information as a flow according to a set of pre-deployed processing rules. We collectively call them Information Flow Processing (IFP) Systems. Despite having a common goal, IFP systems differ in a wide range of aspects, including architectures, data models, rule languages, and processing mechanisms. In this tutorial we draw a general framework to analyze and compare the results achieved so far in the area of IFP systems. This allows us to offer a systematic overview of the topic, favoring the communication between different communities, and highlighting a number of open issue that still need to be addressed in research.
机译:越来越多的分布式应用程序要求以不可预测的速率处理来自地理分布源的连续数据流,以获得对复杂查询的及时响应。此类应用的示例来自最不同的领域:从无线传感器网络到金融行情自动收录机,从流量管理到点击流检查。这些要求导致开发了许多系统,这些系统专门设计用于根据一组预先部署的处理规则将信息作为流进行处理。我们将它们统称为信息流处理(IFP)系统。尽管有一个共同的目标,但IFP系统在很多方面都存在差异,包括体系结构,数据模型,规则语言和处理机制。在本教程中,我们绘制了一个通用框架来分析和比较迄今为止在IFP系统领域中取得的结果。这使我们能够对该主题进行系统的概述,有利于不同社区之间的交流,并突出了一些尚待研究解决的开放性问题。

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