A multiple pattern complex event detection scheme based on decomposition and merge sharing for massive event streams

Jianhua Wang, Bang Ji, Feng Lin, Shilei Lu, Yubin Lan and Lianglun Cheng

International Journal of Distributed Sensor Networks, 2020, vol. 16, issue 10, 1550147720961336

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.

Keywords: Complex event detection; multiple pattern; decomposition sharing; merge sharing; massive event streams (search for similar items in EconPapers)
Date: 2020
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Persistent link: https://EconPapers.repec.org/RePEc:sae:intdis:v:16:y:2020:i:10:p:1550147720961336

DOI: 10.1177/1550147720961336

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