Application Generation Framework for Real-Time Complex Event Processing

Abstract

We propose to develop a framework which provides the ability to apply complex event processing in realtime domains, thus allowing an easier process of developing and maintaining specific solutions for real-time event-based systems, while upholding the real time requirements of the system. Specifically, we propose to develop a framework that includes an integrated development environment for defining rules, and, given a set of rules, generates code for a complex event processing application for which it is able to determine time bounds on the response of this application to a set of supported events. In particular, the tool helps determine a time bound for the execution time of the code corresponding to each rule. Many Service Oriented Architecture (SOA) applications, in domains such as financial services, manufacturing, gaming and military/aerospace, have real-time performance requirements. We present real-life industry use cases from these domains as motivation for the potential benefit in developing real-time complex event processing applications. In support of a feasibility argument for the proposed approach we present some preliminary experimental results obtained on a partially implemented tool.

Complex Event Processing Methods for Greenhouse Control

“…In 2008, D. Gyllstrom et al proposed the SASE+ improvement system and applied the green closure operator for repeated events [52]. In the same year, Magid Y. et al also strictly defined a series of operators, applying scenario description methods to complex event models [53]. With the vigorous development of computer technology and the exponential growth of data, event detection methods emerged one after another [18].…”

Network Computing Middleware

“…(2) 物联网智能应用的一大特点是对海量传感器数据或事件的实时处理 [53] .面对来自大量不同传感器数 据源且不断增长的不确定海量时序关联数据和相关的海量传感器事件,面向服务的中间件技术已难以发挥作 用,复杂事件处理中间件及其相应的事件驱动架构成为物联网大规模应用的核心研究内容.事件驱动架构 [54] 的 优点在于能使物联网应用系统针对海量传感器事件,在很短的时间内做出反应.复杂事件处理中间件通过其边 缘服务器从系统中获取大量统称为事件的信息,将其过滤组合,并进行基于规则引擎的智能处理 [55] 和基于数据 流 [56] 的分析计算.如何有效支持不确定海量时序关联数据流的数据级、特征级和决策级等多层次的数据融 合 [57−59] ,支持物联网服务的动态发现和动态定位,以及应对越来越多的感知层、传输层和应用层等多层次的安 全挑战 [60−62] ,是当前物联网中间件的重要研究热点.…”

Semantic Information Modeling for Emerging Applications in Smart Grid

“…CEP deals with detecting event patterns in realtime from among a cloud of information represented as events. CEP has been successfully applied in many application domains ranging from supply chain management [25], [26] to financial services [15], [19]. The requirement of timely response to power use activities in dynamic DR makes CEP an attractive approach.…”