Network Traffic Prediction Based on a Periodic Traffic Model
He Jun
Abstract
He Jun
Abstract
This paper introduces some communication links for long with our network monitor system. The practical traffic measured from operating network including WAN and LAN can all be divide into two fractions: time dependent fraction and time independent fraction. Based on above experiment conclusion,a selftraining traffic modeling arithmetic based on online measurement and a traffic forecasting arithmetic are designed which can forecast the traffic at any time. The comparison between forecasting traffic at different precision and practical traffic is also given.
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This paper introduces some communication links for long with our network monitor system. The practical traffic measured from operating network including WAN and LAN can all be divide into two fractions: time dependent fraction and time independent fraction. Based on above experiment conclusion,a selftraining traffic modeling arithmetic based on online measurement and a traffic forecasting arithmetic are designed which can forecast the traffic at any time. The comparison between forecasting traffic at different precision and practical traffic is also given.
Key concepts: Computer science, Traffic generation model, Network traffic simulation, Fraction (chemistry), Traffic model, Floating car data, Real-time computing, Traffic congestion reconstruction with Kerner's three-phase theory