Abstract
Quickly detecting related primitive events for multiple complex events from massive event stream usually faces with a great challenge due to their single pattern characteristic of the existing complex event detection methods. Aiming to solve the problem, a multiple pattern complex event detection scheme based on decomposition and merge sharing is proposed in this article. The achievement of this article lies that we successfully use decomposition and merge sharing technology to realize the high-efficient detection for multiple complex events from massive event streams. Specially, in our scheme, we first use decomposition sharing technology to decompose pattern expressions into multiple subexpressions, which can provide many sharing opportunities for subexpressions. We then use merge sharing technology to construct a multiple pattern complex events by merging sharing all the same prefix, suffix, or subpattern into one based on the above decomposition results. As a result, our proposed detection method in this article can effectively solve the above problem. The experimental results show that the proposed detection method in this article outperforms some general detection methods in detection model and detection algorithm in multiple pattern complex event detection as a whole.
Highlights
Internet of Manufacturing Things (IOMT)[1] is an important technology to enhance perception, control and management ability of manufacturing and service process, promote enterprise’s production and management innovation, and drive manufacturing transformation and upgrading
The working principle for our proposed detection scheme in this article is that, first, we study and analyze the relationship between single pattern detection expressions; second, we set up two important decomposition rules for the pattern expressions; third, we decompose the pattern expression using the above decomposition rules; fourth, we merge sharing all the same prefix, suffix, or subpattern into one based on the above decomposition results; fifth, we construct a multiple pattern detection model using merging sharing technology; we use the detection model to quickly detect multiple pattern complex events
Where Costord(DS + TS) refers to the optimal multiple pattern CED models based on decomposition and merge sharing; Cost(DS) refers to all the multiple
Summary
Internet of Manufacturing Things (IOMT)[1] is an important technology to enhance perception, control and management ability of manufacturing and service process, promote enterprise’s production and management innovation, and drive manufacturing transformation and upgrading. In real environment of IOMT, a large number of pattern expressions of complex event are registered in detection system to detect various production activities of manufacturing, and we need to rapidly detect multiple different complex events from massive even streams at the same time because its high responsiveness of detection result in IOMT. Under these circumstances, if we still use the above existing CED methods to detect multiple complex events from massive manufacturing event streams, there will be a long detection time, high memory consumption, and low detection efficiency due to its single pattern detection characteristic. Our proposed CED method is presented in section ‘‘Proposed scheme.’’ The experimental results and analysis with our proposed scheme are shown in section ‘‘Experimental results and analysis.’’ In section ‘‘Conclusion,’’ we give our conclusions
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