Method for using hash B + tree structure to detect complex events in manufacturing Internet of Things massive data streams

Abstract

The invention discloses a method using a hash B + tree structure to detect complex events in manufacturing Internet of Things massive data streams and aims to the solve the problems that current methods for detecting the complex events in the manufacturing Internet of Things massive data streams are long in detecting time, slow in response, low in detecting efficiency, and the like. The method has the advantages that an nondeterministic finite automata (NFA) is used in combination with the hash table B + tree technology to detect the complex events, the detecting capability of the complex events in the manufacturing Internet of Things massive data streams is increased greatly, current complex event mode detecting methods based on the NFA are improved, existing complex event detecting technologies are expanded, and detecting of the complex events in the manufacturing Internet of Things massive data streams can be completed efficiently.

Description

technical field [0001] The present invention relates to the field of manufacturing IoT data processing, and more specifically, to a method for detecting complex events in a Hash B+ tree structure oriented to manufacturing IoT mass data streams. Background technique [0002] Manufacturing Internet of Things technology is a technology based on the Internet, embedded systems, RFID, and sensor networks. Through the organic integration and deep collaboration of computing, communication, and control technologies, it realizes real-time perception, dynamic control, and monitoring of large and complex processes in the manufacturing industry. Information service, so as to coordinate the complex physical process of the manufacturing industry, and achieve the purpose of process optimization and system energy saving. In the modern manufacturing Internet of Things, due to the increasing scale of manufacturing production, the increasingly complex manufacturing process, the harsh production...

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Problems solved by technology

[0006] The present invention mainly aims at the problems of long detection time, slow response speed, and low detection efficiency when the above-mentioned current complex event detection method detects complex events on the massive event stream of the manufacturing IoT, and proposes a method for manufacturing IoT massive data streams. The Greek B+ tree structure complex event detection method is to use the automaton (NFA) joint hash table B and tree structure technology to realize the complex event detection method in the mass event flow of the manufacturing Internet of Things. This method improves the current automaton-based sequence scanning and sequence The complex event pattern detection method of the process expands the existing complex event detection technology, so that it can more efficiently complete the complex event detection on the massive data of the manufacturing Internet of Things, and greatly improves the complex event detection ability in the massive data stream

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