maisМоделирование и анализ информационных системModeling and Analysis of Information Systems1818-10152313-5417Yaroslavl State University10.18255/1818-1015-2015-4-521-532mais-270Research ArticleОригинальные статьиArticlesРазработка механизма адаптивной маршрутизации трафика в программно-конфигурируемых сетяхDevelopment of an Adaptive Routing Mechanism in Software-Defined NetworksНосковА. Н.NoskovA. N.

старший преподаватель

ул. Советская, 14, г. Ярославль, 150000 Россия

Lecturer

Sovetskaya str., 14, Yaroslavl, 150000, Russia

lantoni@uniyar.ac.ruМановИ. А.ManovI. A.

магистрант

ул. Советская, 14, г. Ярославль, 150000 Россия

 magister

Sovetskaya str., 14, Yaroslavl, 150000, Russia

ivanmanov@live.comЯрославский государственный университет им. П.Г. ДемидоваРоссияP.G. Demidov Yaroslavl State UniversityRussian Federation201520082015224521532Copyright © Носков А.Н., Манов И.А., 20152015Носков А.Н., Манов И.А.Noskov A.N., Manov I.A.Данная работа распространяется под лицензией Creative Commons Attribution 4.0.This work is licensed under a Creative Commons Attribution 4.0 License.https://www.mais-journal.ru/jour/article/view/270

Цель данной работы – разработать единый механизм адаптивной маршрутизации трафика различного рода, опираясь на текущие требования к качеству предоставления сервисов.Программное конфигурирование сети – это технологии будущего. Современная тенденция развития систем связи постоянно подтверждает этот факт. Однако на сегодняшний день применение этой технологии в ее текущем виде оправдано лишь в больших сетях технологических гигантов и операторов связи. К настоящему времени создано большое количество динамических протоколов маршрутизации трафика в сетях связи. Наша задача создать такое решение, которое сможет использовать возможности каждого узла принимать решение о передаче информации всеми возможными способами для каждого типа трафика. Достижение поставленной цели возможно путем решения задачи разработки обобщенной метрики, подробно характеризующей каналы связи между устройствами в сети, и задачи разработки механизма адаптивного перестроения логической топологии сети (управления маршрутами) для обеспечения качественной работы всей сети в целях удовлетворения текущим требованиям к качеству предоставления того или иного вида сервиса.

The purpose of this work is to develop a unitary mechanism of adaptive routing of different kinds, basing on the current requirements on the quality of service. The software configuration of a network is the technology of the future. The trend in communication systems constantly confirms this fact. However, the application of this technology in its current form is justified only in large networks of technology giants and telecom operators. Today we have a large number of dynamic routing protocols to route big volume traffic in communication networks. Our task is to create the solution that can use the opportunities of each node to make a decision on the transmission of information by all possible means for each type of traffic. Achieving this goal is possible by solving the problem of the development of generalized metrics, which details the links between devices in the network, and the problem of establishing a framework of adaptive logical network topology (route management) to ensure the quality of the whole network in order to meet the current requirements on the quality of a particular type service.

программно-конфигурируемые сетиинформационный потокsoftware defined networkinformation flowReferencesITU-T. Recommendation Y.1540 Internet protocol aspects – Quality of service and network performance, 2011.ITU-T. Recommendation Y.1540 Internet protocol aspects – Quality of service and network performance, 2011.ITU-T. Recommendation Y.1541 Network Performance Objectives for IP-Based Services, 2011.ITU-T. Recommendation Y.1541 Network Performance Objectives for IP-Based Services, 2011.ITU-T. Y.1541: Network performance objectives for IP-based services.ITU-T. Y.1541: Network performance objectives for IP-based services.John F. Buford, Heather Yu, Eng Lua, P2P Networking and Applications, The Morgan Kaufmann Series in Networking, 2009.John F. Buford, Heather Yu, Eng Lua, P2P Networking and Applications, The Morgan Kaufmann Series in Networking, 2009.Luc De Ghein, MPLS Fundamentals, Cisco Press, 2006.Luc De Ghein, MPLS Fundamentals, Cisco Press, 2006.Thomas D. Nadeau, Ken Gray, SDN: Software Defined Networks, O’Reilly Media, 2013.Thomas D. Nadeau, Ken Gray, SDN: Software Defined Networks, O’Reilly Media, 2013.Вешегна Ш., Качество облуживания в IP-сетях, Cisco Press, 2003, 356 с.; [Veshegna Sh., Kachestvo obslujivaniya v IP-setyah, Cisco Press, 2003, 356 pp., (in Russian).]Вешегна Ш., Качество облуживания в IP-сетях, Cisco Press, 2003, 356 с.; [Veshegna Sh., Kachestvo obslujivaniya v IP-setyah, Cisco Press, 2003, 356 pp., (in Russian).]Blei D. M., Ng A. Y., Jordan M. I., “Latent Dirichlet Allocation”, Journal of Machine Learning Research, 3 (2002), 993–1022.Blei D. M., Ng A. Y., Jordan M. I., “Latent Dirichlet Allocation”, Journal of Machine Learning Research, 3 (2002), 993–1022.Daud A, Li J. ,Zhou L., Muhammad F., “Knowledge discovery through directed probabilistic topic models”, Frontiers of Computer Science in China, 4:2 (2010), 280–301.Daud A, Li J. ,Zhou L., Muhammad F., “Knowledge discovery through directed probabilistic topic models”, Frontiers of Computer Science in China, 4:2 (2010), 280–301.Gelman A., Carlin J. B., Stern H. S., Rubin D. B., Bayesian Data Analysis, Chapman and Hall/CRC, 2013.Gelman A., Carlin J. B., Stern H. S., Rubin D. B., Bayesian Data Analysis, Chapman and Hall/CRC, 2013.Vapnik V., Statistical Learning Theory, Wiley, 1998.Vapnik V., Statistical Learning Theory, Wiley, 1998.Ferguson T. S., “A bayesian analysis of some nonparametric problems”, The Annals of Statistics, 1:2 (1973), 209–230.Ferguson T. S., “A bayesian analysis of some nonparametric problems”, The Annals of Statistics, 1:2 (1973), 209–230.Kintsch W., Handbook of Latent Semantic Analysis, Erlbaum, Hillsdale, NJ, 2007.Kintsch W., Handbook of Latent Semantic Analysis, Erlbaum, Hillsdale, NJ, 2007.Knorr E. M., Ng R. T., “Algorithms for Mining Distance-Based Outliers in LargeKnorr E. M., Ng R. T., “Algorithms for Mining Distance-Based Outliers in LargeDatasets”, Proceedings of the 24th International Conference on Very Large Data Bases, 1 (1998), 392–403.Datasets”, Proceedings of the 24th International Conference on Very Large Data Bases, 1 (1998), 392–403.Knorr E. M., Ng R. T., “Finding Intensional Knowledge of Distance-based Outliers”, Proceedings of the 25th International Conference on Very Large Data Bases, 1 (1999), 211–222.Knorr E. M., Ng R. T., “Finding Intensional Knowledge of Distance-based Outliers”, Proceedings of the 25th International Conference on Very Large Data Bases, 1 (1999), 211–222.Minka T., Lafferty J., “Expectation-propagation for the generative aspect model”, Proceedings of the 18th Conference on Uncertainty in Artificial Intelligence, 2002.Minka T., Lafferty J., “Expectation-propagation for the generative aspect model”, Proceedings of the 18th Conference on Uncertainty in Artificial Intelligence, 2002.Saurabh Ganeriwal, Laura K. Balzano, Mani B., “Reputation-based Framework for High Integrity Sensor Networks”, ACM Transactions on Sensor Networks, 5 (2007).Saurabh Ganeriwal, Laura K. Balzano, Mani B., “Reputation-based Framework for High Integrity Sensor Networks”, ACM Transactions on Sensor Networks, 5 (2007).Paramasivan B. A, Prakash M. J, Kaliappan M., “Development of a secure routing protocol using game theory model in mobile ad hoc networks”, Journal of Communications and Networks, 1:15 (2015), 75–83.Paramasivan B. A, Prakash M. J, Kaliappan M., “Development of a secure routing protocol using game theory model in mobile ad hoc networks”, Journal of Communications and Networks, 1:15 (2015), 75–83.Samsudin N. A. a, Bradley A. P. b, “Extended na?ve bayes for group based classification Advances in Intelligent Systems and Computing”, 1st International Conference on Soft Computing and Data Mining, 287 (2014), 497–506.Samsudin N. A. a, Bradley A. P. b, “Extended na?ve bayes for group based classification Advances in Intelligent Systems and Computing”, 1st International Conference on Soft Computing and Data Mining, 287 (2014), 497–506.Jolliffe I. T., Principal components analysis, Springer-Verlag, New York, 1986.Jolliffe I. T., Principal components analysis, Springer-Verlag, New York, 1986.Shipman C. M., Hopkinson K. M., Lopez J., “Con-resistant trust for improved reliability in a smart-grid special protection system”, IEEE Transactions on Power Delivery, 13:1 (2015), 455–462Shipman C. M., Hopkinson K. M., Lopez J., “Con-resistant trust for improved reliability in a smart-grid special protection system”, IEEE Transactions on Power Delivery, 13:1 (2015), 455–462

The authors declare that there are no conflicts of interest present.