建模和分析实时数据流

Krasimira Kapitanova, S. Son, Woochul Kang, Wontae Kim
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引用次数: 5

摘要

实现态势感知对于实时数据流应用程序来说尤其具有挑战性,因为它们i)在连续的无界数据流上操作,ii)具有固有的实时要求。在本文中,我们展示了如何使用正式的数据流建模和分析来更好地理解流行为、评估查询成本和提高应用程序性能。我们使用基于Petri网的形式化规范语言MEDAL对数据流查询和数据流系统中的服务质量(QoS)管理机制进行建模。MEDAL在一个模型中结合查询逻辑和数据接收控制的能力使我们能够设计一个单一的系统综合模型。此模型可用于执行大量分析,以帮助改进应用程序的性能和QoS。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Modeling and Analyzing Real-Time Data Streams
Achieving situation awareness is especially challenging for real-time data stream applications because they i) operate on continuous unbounded streams of data, and ii) have inherent real-time requirements. In this paper we show how formal data stream modeling and analysis can be used to better understand stream behavior, evaluate query costs, and improve application performance. We use MEDAL, a formal specification language based on Petri nets, to model the data stream queries and the Quality-of-Service (QoS) management mechanisms in a data stream system. MEDAL's ability to combine query logic and data admission control in one model allows us to design a single comprehensive model of the system. This model can be used to perform a large set of analyses to help improve the application's performance and QoS.
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