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Network Traffic Prediction Based On Grey Neural Network Model

Posted on:2009-11-21Degree:MasterType:Thesis
Country:ChinaCandidate:J H CaoFull Text:PDF
GTID:2178360272956441Subject:Computer application technology
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As the rapid development and application of Internet, the scale of internet is becoming larger and larger, the application of the internet is becoming more and more complicated. Due to network is a very complicated non-line system, in order to realize reliable data transfer and reasonable internet resource distribution, it is very important to comprehend the control mechanism and complicated behavioral character of network. Excellent analysis and modeling could help to evaluate the network character more effectively. A predictable model which totally accord with the complicated network statistic character, could help to analyze and emulate the network accurately, and conduce to the network design and control.Predicting and modeling network traffic is always an important subject in network capability studying .The Prediction results can bring out essential reference for bandwidth allocation ,network traffic control, routing control ,entry control and error control in network management. Network traffic is dynamical,real time,correlative ,stochastic and noisy. The forecasting precision and expressive power of the model is very important for analysis,simulation and network behavior study.The aim of this article is to explore a new network model in order to describe and predict the network character accurately. In the beginning, the article analyze some main character about network, in the actual network environment, it present quite obvious multi-scale character, such as self-similarity, long-range dependence, fraction and multi-fraction; in following, the article analyze and compare the advantage and disadvantage of some traditional network analytic model, such as semi-Markov model, Poisson model, ARMA model and ON/OFF model.This Paper advanced a kind of grey predicting method based on error and give out a new combined prediction model with grey theory and neural network .Such methods were used to predict and making analysis for the data we selected. Precision and effect of the model has also been analysed. Foresaid work laid the foundation for developing short term(and long rang )network traffic prediction software system·Aiming at the shortages of common dynamic integrate linking status method and network throughput based routing algorithm ,a new optimized routing method was brought out. It can well complement some existent algorithm .Theoretical analytic result shows, routing effect is better.
Keywords/Search Tags:network traffic, grey model, prediction, neural network, combination prediction model, routing
PDF Full Text Request
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