KEYWORDS: Data modeling, Autoregressive models, Distributed computing, Computer programming, Switches, Mathematical modeling, Internet, Local area networks, Data storage, Computing systems
The thesis develops a network traffic predication application. The application, built on the R language oriented distributed stream processing systems described above, uses JDSU micro probe systems and nProbe to collect network traffic data, make predication on ARIMA model, and provide the basic data visualization function. Compared to similar systems, our network predication platform, has higher scalability and serviceability thanks to the distributed stream processing system, and better development efficiency with the help of R and CRAN.
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