Deployment Approaches in Distributed Complex Event Processing

Arsenij Andreevich Zorin, Irina Evgenyevna Chernetskaya
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Abstract

Big Data technologies have traditionally focused on processing human-generated data, while neglecting the vast amounts of data generated by Machine-to-Machine (M2M) interactions and Internet-of-Things (IoT) platforms. These interactions generate real-time data streams that are highly structured, often in the form of a series of event occurrences. In this paper, we aim to provide a comprehensive overview of the main research issues in Complex Event Processing (CEP) techniques, with a special focus on optimizing the distribution of event handlers between working nodes. We introduce and compare different deployment strategies for CEP event handlers. These strategies define how the event handlers are distributed over different working nodes. In this paper we consider the distributed approach, because it ensures, that the event handlers are scalable, fault-tolerant, and can handle large volumes of data.
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分布式复杂事件处理中的部署方法
传统上,大数据技术专注于处理人类产生的数据,而忽略了机器对机器(M2M)交互和物联网(IoT)平台产生的大量数据。这些交互产生高度结构化的实时数据流,通常以一系列事件发生的形式出现。在本文中,我们旨在全面概述复杂事件处理(CEP)技术的主要研究问题,并特别关注优化工作节点之间事件处理程序的分布。我们介绍并比较了CEP事件处理程序的不同部署策略。这些策略定义了如何在不同的工作节点上分布事件处理程序。在本文中,我们考虑分布式方法,因为它确保了事件处理程序是可伸缩的、容错的,并且可以处理大量数据。
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18
审稿时长
4 weeks
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