| Autor: |
Haiqing YU, Wei DING, Jie XU |
| Jazyk: |
čínština |
| Rok vydání: |
2020 |
| Předmět: |
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| Zdroj: |
Dianxin kexue, Vol 36, Pp 74-82 (2020) |
| Druh dokumentu: |
article |
| ISSN: |
1000-0801 |
| DOI: |
10.11959/j.issn.1000-0801.2020117 |
| Popis: |
Real-time access hyper-point helps managers better control the network.Under high-speed network conditions,the difficulty in accessing hyper-point detection lies in the pressure exerted by large traffic on computing.Based on the 40 Gbit/s bandwidth network environment,from the perspective of accuracy analysis,the flow record statistics algorithm and the estimation-based superpoint detection algorithm were compared.The flow record statistical algorithm was improved by the threshold model based on heavy-tailed distribution.The estimation-based superpoint detection algorithm was implemented in the GPU environment by SRLA.The research results show that the estimation-based hyper-point detection algorithm which has obviously higher accuracy and more room for improvement is more suitable for real-time detection of hyper-point in high-speed network than the flow record statistical algorithm. |
| Databáze: |
Directory of Open Access Journals |
| Externí odkaz: |
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