Detection method for complex events in mass disordered data streams of Internet of Things Manufacturing

Abstract

The invention discloses a detection method for complex events in mass disordered data streams of Internet of Things Manufacturing, and aims at solving the problem of low efficiency on detecting the events in mass disordered data streams in the Internet of Things Manufacturing. The method is characterized in that ENFA (Extended Nondeterministic Finite Automaton) is utilized for selecting events in mass disordered data streams, and the storage relationship of a hash table structure is utilized to handle events in the mass disordered data streams, so as to realize the detection of the complex events in mass disordered data streams. The method has the advantages that the existing automaton-based complex event mode detection method is improved, the existing complex event detection technology is expanded to be able to efficiently detect the complex events in the mass disordered data streams, and therefore, the detection efficiency is raised.

Description

technical field [0001] The present invention relates to the field of manufacturing Internet of Things, and more specifically, to a method for detecting complex events of massive out-of-sequence data streams in the manufacturing Internet of Things. Background technique [0002] Manufacturing Internet of Things technology is based on middleware, massive information fusion processing and system integration technology, based on Internet of Things network development service platform and application system to solve the comprehensive information perception, reliable transmission, Massive data processing, precise control and credible service issues, technology to increase the added value of product technology, and enhance the management and control capabilities of the manufacturing and service process. Complex event detection technology is a technology that can use the association between event attributes to continuously filter the massive data streams that arrive continuously thro...

AI Technical Summary

Problems solved by technology

[0004] The present invention mainly aims at the problem of low efficiency of detecting complex events in massive out-of-order data streams of the manufacturing Internet of Things, and proposes a complex event detection method for massive out-of-order data streams in the manufacturing Internet of Things. The method mainly uses ENFA (Extended Nondeterministic Finite Automaton) to detect The events in the massive out-of-order data stream are selected, and the storage relationship of the hash table structure is used to process the events in the massive out-of-order data stream, so as to realize the complex event detection in the massive out-of-order data stream and improve the current massive out-of-order data stream The complex event detection method in the data stream expands the existing complex event detection technology and improves the efficiency of complex event detection in massive out-of-order data streams in the manufacturing industry

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