Journal on Communications ›› 2018, Vol. 39 ›› Issue (6): 116-126.doi: 10.11959/j.issn.1000-436x.2018096

• Papers • Previous Articles     Next Articles

Timing evolution and prediction of Internet transmission behavior

He TIAN1,Hai ZHAO2,Jinfa WANG2,Chuan LIN2   

  1. 1 Engineering Practice Center,Liaoning Institute of Science and Technology,Benxi 117004,China
    2 School of Computer Science and Engineering,Northeastern University,Shenyang 110004,China
  • Revised:2018-04-02 Online:2018-06-01 Published:2018-07-09
  • Supported by:
    The National Natural Science Foundation of China(60973022)

Abstract:

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.

Key words: Internet transmission, network traveling time, Logistic model, Chaos characteristics, behavior prediction

CLC Number: 

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