Research On Complex Event Processing Over Interval Event Stream Supporting Regular Expression Pattern Matching

With the advent of the era of big data,the data generated in various fields is getting larger and larger.Some of the data generated in some areas are characterized by large amounts of data,real-time arrival,and difficulty in storage,and are called streaming data.In order to effectively and timely process these data,the streaming processing has been fully developed.As one of the core technologies of streaming computing,complex event processing technology has also received more and more attention.Complex event processing technology uses external data generated by the system or received by the system as an event.After these events are captured,pattern matching is performed on the generated event stream to identify meaningful events.When an index is reached,Make timely feedback.At present,the complex event processing system has been used in many fields such as medical care,monitoring,and economics,and has achieved good results.Currently,the events targeted by the complex event processing system are mostly point-based events.However,in real life,the beginning and ending of an event may not occur at the same time,and it must have a duration.It is possible to meet the more practical requirements by timing constraints on two events with duration.Therefore,it is necessary to discuss the timing relationship between interval-based events.To solve the above problems,this paper proposes a method to support interval temporal logic and regular expression,which can detect the complex event streams.It uses regular expressios to describe event patterns in event processing languages.At the same time,combining regular expression and interval temporal logic to expand complex event processing techniques for temporal logic constraints between pointbased events can not only make up for the lack of description of temporal logic relations between interval-based events,but also can be used conveniently for regular expression describes the interval-based event pattern constraints and enhances the detection capabilities of complex event processing.In this method,different timed automata are designed for different interval temporal logics,TA and TA-Net are used to pattern match events.Finally,this paper designs and implements a new complex event processing system called CIEP.And apply the above technology to this system.Functionally,the system supports multi-source transient event detection and multi-source interval-based event detection.In terms of performance,the system can efficiently process large amounts of data by comparing and testing multiple sets of tests.