DOI: https://doi.org/10.15587/1729-4061.2019.164686

Traffic engineering in a software-defined network based on the decision-making method

Yurii Kulakov, Alla Kohan, Yevheniia Pavlenkova, Nikol Pastrello, Nikita Machekhin

Abstract


One of the main control tasks in a computer network is to organize an effective system of information delivery; this task is of particular relevance in the software defined network. Conventional routing tools do not meet the requirements to service quality and the requirements for equitable distribution of congestion along communication channels. Routing in conventional networks is performed by the shortest path search based on a specified parameter, but these tools do not provide sufficient agility when changing routes in the network. Another drawback is the need to transmit regular updates of routing information by passing the service traffic, thereby dramatically increasing the congestion and reducing the throughput.

At present, the most effective way to ensure the assigned quality of service parameters, as well as a promising solution to organize efficient routing under conditions of uncertainty, is a software defined network. This new networking paradigm makes it possible to simplify the process of managing the network, to significantly enhance the use of network resources, and to reduce operating costs. One of the main advantages of such a network is control at the upper levels of the reference model, which makes it possible to simplify both the process of network management and the process to manage traffic in corporate networks and data center networks.

A new approach to traffic design in a software defined network has been proposed that employs the making-decision theory oriented towards routing exactly in such networks. If there is a «problematic area» and there is the need to overcome it, the decision-making theory under conditions of uncertainty is used, since the probability of selecting the best way to circumvent it accounts for the patterns in transmitted traffic. Such a method makes it possible to reduce the loss of inelastic traffic that is an important component of the overall amount of transmitted information. From a practical point of view, the algorithm constructed in this work, when compared to known algorithms for traffic engineering, improves the quality of service in software defined networks

Keywords


traffic engineering; software defined network; fuzzy logic; throughput capacity; channels congestion; network reconfiguration

References


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He, J., Song, W. (2015). Achieving near-optimal traffic engineering in hybrid Software Defined Networks. 2015 IFIP Networking Conference (IFIP Networking). doi: https://doi.org/10.1109/ifipnetworking.2015.7145321

Shu, Z., Wan, J., Lin, J., Wang, S., Li, D., Rho, S., Yang, C. (2016). Traffic engineering in software-defined networking: Measurement and management. IEEE Access, 4, 3246–3256. doi: https://doi.org/10.1109/access.2016.2582748

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Lin, S.-C., Wang, P., Luo, M. (2016). Control traffic balancing in software defined networks. Computer Networks, 106, 260–271. doi: https://doi.org/10.1016/j.comnet.2015.08.004

Lin, S.-C., Akyildiz, I. F., Wang, P., Luo, M. (2016). QoS-Aware Adaptive Routing in Multi-layer Hierarchical Software Defined Networks: A Reinforcement Learning Approach. 2016 IEEE International Conference on Services Computing (SCC). doi: https://doi.org/10.1109/scc.2016.12

Kulakov, Yu. A., Kogan, A. V., Hrapov, V. M. (2017). The method of constructing traffic in the multipath routing. Visnyk NTUU «KPI» Informatyka, upravlinnia ta obchysliuvalna tekhnika, 65, 28–33.

Kulakov, Y., Kopychko, S., Gromova, V. (2019). Organization of Network Data Centers Based on Software-Defined Networking. Advances in Intelligent Systems and Computing, 447–455. doi: https://doi.org/10.1007/978-3-319-91008-6_45

Al-Fares, M., Radhakrishnan, S., Huang, N., Vahdat, A., Raghavan, B. (2010). Hedera: Dynamic Flow Scheduling for Data Center Networks. NSDI'10 Proceedings of the 7th USENIX conference on Networked systems design and implementation. San Jose, 19–34.

Zhang, H., Guo, X., Yan, J., Liu, B., Shuai, Q. (2014). SDN-based ECMP algorithm for data center networks. 2014 IEEE Computers, Communications and IT Applications Conference. doi: https://doi.org/10.1109/comcomap.2014.7017162

Chiang, S.-H., Kuo, J.-J., Shen, S.-H., Yang, D.-N., Chen, W.-T. (2018). Online Multicast Traffic Engineering for Software-Defined Networks. IEEE INFOCOM 2018 – IEEE Conference on Computer Communications. doi: https://doi.org/10.1109/infocom.2018.8486290

Jutila, M. (2017). Adaptive traffic management in heterogeneous communication networks. University of Oulu, 96.

Trestian, R., Muntean, G.-M., Katrinis, K. (2013). MiceTrap: Scalable traffic engineering of datacenter mice flows using OpenFlow. IFIP/IEEE Int. Symp. on Integr. Netw. Managem. IM 2013. Ghent, 904–907.

Qazi, Z. A., Lee, J., Jin, T., Bellala, G., Arndt, M., Noubir, G. (2013). Application-awareness in SDN. ACM SIGCOMM Computer Communication Review, 43 (4), 487–488. doi: https://doi.org/10.1145/2534169.2491700

Dinh, K. T., Kukliński, S., Kujawa, W., Ulaski, M. (2016). MSDN-TE: Multipath Based Traffic Engineering for SDN. Intelligent Information and Database Systems, 630–639. doi: https://doi.org/10.1007/978-3-662-49390-8_61

Braun, W., Menth, M. (2015). Load-dependent flow splitting for traffic engineering in resilient OpenFlow networks. 2015 International Conference and Workshops on Networked Systems (NetSys). doi: https://doi.org/10.1109/netsys.2015.7089060

Kul'gin, M. (2000). Tekhnologii korporativnyh setey. Sankt-Peterburg, 704.

Kulakov, Y., Kohan, A., Kopychko, S. (2020). Traffic Orchestration in Data Center Network Based on Software-Defined Networking Technology. Advances in Computer Science for Engineering and Education II, 228–237. doi: https://doi.org/10.1007/978-3-030-16621-2_21


GOST Style Citations


A Survey on Software-Defined Networking / Xia W., Wen Y., Foh C. H., Niyato D., Xie H. // IEEE Communications Surveys & Tutorials. 2015. Vol. 17, Issue 1. P. 27–51. doi: https://doi.org/10.1109/comst.2014.2330903 

Ahmed A. M., Paulus R. Congestion detection technique for multipath routing and load balancing in WSN // Wireless Networks. 2017. Vol. 23, Issue 3. P. 881–888. doi: https://doi.org/10.1007/s11276-015-1151-5 

He J., Song W. Achieving near-optimal traffic engineering in hybrid Software Defined Networks // 2015 IFIP Networking Conference (IFIP Networking). 2015. doi: https://doi.org/10.1109/ifipnetworking.2015.7145321 

Traffic engineering in software-defined networking: Measurement and management / Shu Z., Wan J., Lin J., Wang S., Li D., Rho S., Yang C. // IEEE Access. 2016. Vol. 4. P. 3246–3256. doi: https://doi.org/10.1109/access.2016.2582748 

Energy-aware traffic engineering in hybrid SDN/IP backbone networks / Wei Y., Zhang X., Xie L., Leng S. // Journal of Communications and Networks. 2016. Vol. 18, Issue 4. P. 559–566. doi: https://doi.org/10.1109/jcn.2016.000079 

Lin S.-C., Wang P., Luo M. Control traffic balancing in software defined networks // Computer Networks. 2016. Vol. 106. P. 260–271. doi: https://doi.org/10.1016/j.comnet.2015.08.004 

QoS-Aware Adaptive Routing in Multi-layer Hierarchical Software Defined Networks: A Reinforcement Learning Approach / Lin S.-C., Akyildiz I. F., Wang P., Luo M. // 2016 IEEE International Conference on Services Computing (SCC). 2016. doi: https://doi.org/10.1109/scc.2016.12 

Kulakov Yu. A., Kogan A. V., Hrapov V. M. The method of constructing traffic in the multipath routing // Visnyk NTUU «KPI» Informatyka, upravlinnia ta obchysliuvalna tekhnika. 2017. Issue 65. P. 28–33.

Kulakov Y., Kopychko S., Gromova V. Organization of Network Data Centers Based on Software-Defined Networking // Advances in Intelligent Systems and Computing. 2019. P. 447–455. doi: https://doi.org/10.1007/978-3-319-91008-6_45 

Hedera: Dynamic Flow Scheduling for Data Center Networks / Al-Fares M., Radhakrishnan S., Huang N., Vahdat A., Raghavan B. // NSDI'10 Proceedings of the 7th USENIX conference on Networked systems design and implementation. San Jose, 2010. P. 19–34.

SDN-based ECMP algorithm for data center networks / Zhang H., Guo X., Yan J., Liu B., Shuai Q. // 2014 IEEE Computers, Communications and IT Applications Conference. 2014. doi: https://doi.org/10.1109/comcomap.2014.7017162 

Online Multicast Traffic Engineering for Software-Defined Networks / Chiang S.-H., Kuo J.-J., Shen S.-H., Yang D.-N., Chen W.-T. // IEEE INFOCOM 2018 – IEEE Conference on Computer Communications. 2018. doi: https://doi.org/10.1109/infocom.2018.8486290 

Jutila M. Adaptive traffic management in heterogeneous communication networks. University of Oulu, 2017. 96 p.

Trestian R., Muntean G.-M., Katrinis K. MiceTrap: Scalable traffic engineering of datacenter mice flows using OpenFlow // IFIP/IEEE Int. Symp. on Integr. Netw. Managem. IM 2013. Ghent, 2013. P. 904–907.

Application-awareness in SDN / Qazi Z. A., Lee J., Jin T., Bellala G., Arndt M., Noubir G. // ACM SIGCOMM Computer Communication Review. 2013. Vol. 43, Issue 4. P. 487–488. doi: https://doi.org/10.1145/2534169.2491700 

MSDN-TE: Multipath Based Traffic Engineering for SDN / Dinh K. T., Kukliński S., Kujawa W., Ulaski M. // Intelligent Information and Database Systems. 2016. P. 630–639. doi: https://doi.org/10.1007/978-3-662-49390-8_61 

Braun W., Menth M. Load-dependent flow splitting for traffic engineering in resilient OpenFlow networks // 2015 International Conference and Workshops on Networked Systems (NetSys). 2015. doi: https://doi.org/10.1109/netsys.2015.7089060 

Kul'gin M. Tekhnologii korporativnyh setey. Sankt-Peterburg, 2000. 704 p.

Kulakov Y., Kohan A., Kopychko S. Traffic Orchestration in Data Center Network Based on Software-Defined Networking Technology // Advances in Computer Science for Engineering and Education II. 2020. P. 228–237. doi: https://doi.org/10.1007/978-3-030-16621-2_21 







Copyright (c) 2019 Yurii Kulakov, Alla Kohan, Yevheniia Pavlenkova, Nikol Pastrello, Nikita Machekhin

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ISSN (print) 1729-3774, ISSN (on-line) 1729-4061