Research On Application System Based On Real - Time Data Flow

With the development of computer hardware and sensor networks, data stream is widely used in various fields as a new data form.As the characteristics of data stream are different from the traditional static data,traditional data mining methods are no longer suitable for data stream mining, which becomes a new research topic in the field of data mining,and has brought great challenges to research and industrial control fields.By analyzing the characteristics of real-time data streams and related technologies,this paper introduces some typical clustering algorithms that currently exist in the literature,analyzes their advantages and disadvantages as well as the applicable environment.Finally,this paper shows the application of the real-time data stream through two specific examples.One analyzes the Internet usage in campus by the Netflow flow,the other proposes a method to do product quality supervision based on real-time data analysis, aiming at the common quality analysis and supervision problem in the process of steel production. Combining with real-time database and relational database, the method performs a real-time detection of steel production in both real-time supervision and off-line tracing. The main work is the implementation of on the collection of real-time data for real-time databases, and the analysis schema given both real-time and relational data. The method proposed has been applied in several production lines of a steel factory and performed well quality management.