Cloud PARTE: elastic complex event processing based on mobile actors

Janwillem Swalens, Thierry Renaux, L. Hoste, Stefan Marr, W. Meuter
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引用次数: 4

Abstract

Traffic monitoring or crowd management systems produce large amounts of data in the form of events that need to be processed to detect relevant incidents. Rule-based pattern recognition is a promising approach for these applications, however, increasing amounts of data as well as large and complex rule sets demand for more and more processing power and memory. In order to scale such applications, a rule-based pattern detection system needs to be distributable over multiple machines. Today's approaches are however focused on static distribution of rules or do not support reasoning over the full set of events. We propose Cloud PARTE, a complex event detection system that implements the Rete algorithm on top of mobile actors. These actors can migrate between machines to respond to changes in the work load distribution. Cloud PARTE is an extension of PARTE and offers the first rule engine specifically tailored for continuous complex event detection that is able to benefit from elastic systems as provided by cloud computing platforms. It supports fully automatic load balancing and supports online rules with access to the entire event pool.
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Cloud part:基于移动参与者的弹性复杂事件处理
交通监控或人群管理系统以事件的形式产生大量数据,需要对这些数据进行处理以检测相关事件。对于这些应用程序来说,基于规则的模式识别是一种很有前途的方法,但是,不断增加的数据量以及大型和复杂的规则集需要越来越多的处理能力和内存。为了扩展这样的应用程序,基于规则的模式检测系统需要分布在多台机器上。然而,今天的方法侧重于规则的静态分布,或者不支持对整个事件集进行推理。我们提出了一个复杂的事件检测系统Cloud PARTE,它在移动参与者之上实现了Rete算法。这些参与者可以在机器之间迁移,以响应工作负载分布的变化。Cloud PARTE是PARTE的扩展,提供了第一个专门为连续复杂事件检测量身定制的规则引擎,能够从云计算平台提供的弹性系统中受益。它支持全自动负载均衡,支持访问整个事件池的在线规则。
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Tanks: multiple reader, single writer actors Cloud PARTE: elastic complex event processing based on mobile actors Semantics-preserving sharing actors Structured reasoning about actor systems Load balancing non-uniform parallel computations
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