Complex event detection method on basis of IMF (instance matching frequency) internal and external memory replacement policy

Abstract

The invention relates to a complex event detection method on the basis of an IMF (Instance Matching Frequency) internal and external memory replacement policy. In the method, when a user does not terminate a detection process, an event flow is continuously scanned; a current event is read; an object statistical table is constructed and modified; and different treatments are carried out according to the type of the current event; if the current event is a terminal event, a complex event detection process is triggered and a detected sequence which meets a user defined mode is output; if the current event is a nonterminal event and an internal memory quota of the current event is not full, the internal memory storage of an event instance is carried out on the basis of an object tree and an index thereof; and if the current event is the nonterminal event and the internal memory quota of the current event is full, the internal and external memory replacement of the event instance is carried out on the basis of the IMF policy and the current event is associated with an event instance bit map to carry out external memory storage of each event instance of an replaced object. The complex event detection method can effectively support the large time scale complex event detection and has high efficiency of utilizing the space and processing time.

Description

technical field [0001] The invention belongs to event stream processing technology, and in particular relates to a complex event detection method based on an IMF (Instance Matching Frequency, instance matching frequency) internal and external memory replacement strategy. Background technique [0002] As sensors and Electronic Data Gathering Equipment (EDGE) such as Radio Frequency Identification (RFID) are widely used in many fields such as supply chain management, environmental monitoring, and the Internet of Things, a large number of incidents are generated. type of data. However, users are not interested in all raw event data. For example, in a wind monitoring system, the application is not interested in the wind speed data read by each sensor, but only in the wind speed increased by 5 miles within 2 seconds. Interesting information from which the arrival of a hurricane or tornado can be inferred. The wind speed data here is called the original event or basic event, and...

AI Technical Summary

Problems solved by technology

A complex event with a large time scale takes a long time from occurrence to completion. Therefore, the detection process needs to set a large time window, resulting in a very large amount of data involved in the detection of complex events. Based on existing processing methods and technologies, it is impossible to Event storage and detection are done in

At present, there are no research results on large time scale complex event detection

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