Timing evolution and prediction of Internet transmission behavior - He TIAN; Hai ZHAO; Jinfa WANG; Chuan LIN (Tongxin xuebao)
The transmission behavior of Internet plays an importance role in the research on the relationship between network topology structure and dynamic behavior.Selecting effective path samples in four monitoring points which from different regions authorized by CAIDA_Ark project and statistics network traveling time and traveling diameter,their correlation is very weak,network traveling time is presented on multi-peak and heavy tail distribution.Using nonlinear time sequences analysis method to identify the Chaos characteristics of network traveling time evolution sequences.The results show that their timing evolution has Chaos characteristics.Based on this,the Logistic equation was lead to establish network transmission behavior prediction model,and particle swarm optimization (PSO) was used to optimize model parameters.The model by the network traveling time sequences of four monitoring points was experimented,evaluated it from accuracy and availability,the results show that the model can predict network transmission behavior accurately in the short term.It can be used as a tool for predicting the network behaviors’ evolution in a period of time.