Timing evolution and prediction of Internet transmission behavior
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 tr...
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| Format: | Article |
| Language: | zho |
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Editorial Department of Journal on Communications
2018-06-01
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| Series: | Tongxin xuebao |
| Subjects: | |
| Online Access: | http://www.joconline.com.cn/zh/article/doi/10.11959/j.issn.1000-436x.2018096/ |
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| _version_ | 1841539407756132352 |
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| author | He TIAN Hai ZHAO Jinfa WANG Chuan LIN |
| author_facet | He TIAN Hai ZHAO Jinfa WANG Chuan LIN |
| author_sort | He TIAN |
| collection | DOAJ |
| description | 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. |
| format | Article |
| id | doaj-art-1a698990f2a44f75b1a08138c0f8a5d5 |
| institution | Kabale University |
| issn | 1000-436X |
| language | zho |
| publishDate | 2018-06-01 |
| publisher | Editorial Department of Journal on Communications |
| record_format | Article |
| series | Tongxin xuebao |
| spelling | doaj-art-1a698990f2a44f75b1a08138c0f8a5d52025-01-14T07:14:58ZzhoEditorial Department of Journal on CommunicationsTongxin xuebao1000-436X2018-06-013911612659718910Timing evolution and prediction of Internet transmission behaviorHe TIANHai ZHAOJinfa WANGChuan LINThe 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.http://www.joconline.com.cn/zh/article/doi/10.11959/j.issn.1000-436x.2018096/Internet transmissionnetwork traveling timeLogistic modelChaos characteristicsbehavior prediction |
| spellingShingle | He TIAN Hai ZHAO Jinfa WANG Chuan LIN Timing evolution and prediction of Internet transmission behavior Tongxin xuebao Internet transmission network traveling time Logistic model Chaos characteristics behavior prediction |
| title | Timing evolution and prediction of Internet transmission behavior |
| title_full | Timing evolution and prediction of Internet transmission behavior |
| title_fullStr | Timing evolution and prediction of Internet transmission behavior |
| title_full_unstemmed | Timing evolution and prediction of Internet transmission behavior |
| title_short | Timing evolution and prediction of Internet transmission behavior |
| title_sort | timing evolution and prediction of internet transmission behavior |
| topic | Internet transmission network traveling time Logistic model Chaos characteristics behavior prediction |
| url | http://www.joconline.com.cn/zh/article/doi/10.11959/j.issn.1000-436x.2018096/ |
| work_keys_str_mv | AT hetian timingevolutionandpredictionofinternettransmissionbehavior AT haizhao timingevolutionandpredictionofinternettransmissionbehavior AT jinfawang timingevolutionandpredictionofinternettransmissionbehavior AT chuanlin timingevolutionandpredictionofinternettransmissionbehavior |