| Autor: |
Bolodurina, I P, Parfenov, D I |
| Zdroj: |
IOP Conference Series: Materials Science and Engineering; January 2018, Vol. 302 Issue: 1 p012059-012059, 1p |
| Abstrakt: |
We have elaborated a neural network model of virtual network flow identification based on the statistical properties of flows circulating in the network of the data center and characteristics that describe the content of packets transmitted through network objects. This enabled us to establish the optimal set of attributes to identify virtual network functions. We have established an algorithm for optimizing the placement of virtual data functions using the data obtained in our research. Our approach uses a hybrid method of visualization using virtual machines and containers, which enables to reduce the infrastructure load and the response time in the network of the virtual data center. The algorithmic solution is based on neural networks, which enables to scale it at any number of the network function copies. |
| Databáze: |
Supplemental Index |
| Externí odkaz: |
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