%0 Journal Article %1 bolodurina2018development %A Bolodurina, Irina %A Parfenov, Denis %D 2018 %E Meghanathan, Natarajan %J International Journal of Computer Networks & Communications (IJCNC) %K Cloud applications; center; data flows; learning machine mining; network; software-defined traffic virtual %N 2 %P 15-22 %R 10.5121/ijcnc.2018.10202 %T The Development and Study of the Methods and Algorithms for the Classification of Data Flows of Cloud Applications in the Network of the Virtual Data Center %U http://airccse.org/journal/ijc2018.html %V 10 %X This paper represents the results of the research, which have allowed us to develop a hybrid approach to the processing, classification, and control of traffic routes. The approach enables to identify traffic flows in the virtual data center in real-time systems. Our solution is based on the methods of data mining and machine learning, which enable to classify traffic more accurately according to more criteria and parameters. As a practical result, the paper represents the algorithmic solution of the classification of the traffic flows of cloud applications and services embodied in a module for the controller of the software-defined network. This solution enables to increase the efficiency of handling user requests to cloud applications and reduce the response time, which has a positive effect on the quality of service in the network of the virtual data center

@article{bolodurina2018development, abstract = {This paper represents the results of the research, which have allowed us to develop a hybrid approach to the processing, classification, and control of traffic routes. The approach enables to identify traffic flows in the virtual data center in real-time systems. Our solution is based on the methods of data mining and machine learning, which enable to classify traffic more accurately according to more criteria and parameters. As a practical result, the paper represents the algorithmic solution of the classification of the traffic flows of cloud applications and services embodied in a module for the controller of the software-defined network. This solution enables to increase the efficiency of handling user requests to cloud applications and reduce the response time, which has a positive effect on the quality of service in the network of the virtual data center }, added-at = {2018-04-10T04:34:47.000+0200}, author = {Bolodurina, Irina and Parfenov, Denis}, biburl = {https://www.bibsonomy.org/bibtex/283a46e84f41d9f02843c605b0094bac4/laimbee}, doi = {10.5121/ijcnc.2018.10202}, editor = {Meghanathan, Natarajan}, interhash = {d1f5312745935e3263f82747a96b01bf}, intrahash = {83a46e84f41d9f02843c605b0094bac4}, issn = {09749322}, journal = {International Journal of Computer Networks & Communications (IJCNC) }, keywords = {Cloud applications; center; data flows; learning machine mining; network; software-defined traffic virtual}, language = {English}, month = {March}, number = 2, pages = {15-22}, timestamp = {2018-04-10T04:34:47.000+0200}, title = {The Development and Study of the Methods and Algorithms for the Classification of Data Flows of Cloud Applications in the Network of the Virtual Data Center}, url = {http://airccse.org/journal/ijc2018.html}, volume = 10, year = 2018 }