Numerical Simulation and Experiments on Advanced Traffic Engineering

In this paper, we present artificial intelligence (AI)-assisted advanced traffic engineering (TE) methods and some techniques for numerical simulation and experiments to validate those methods. TE is to optimize network performance and resource usage by changing routes or logical topologies in response to environmental changes such as a sudden traffic demand increase. In performing TE, we modify the logical configuration of a network, but this often causes unexpected congestion or performance degradation. We cannot fully predict the behavior of an operational network composed of numerous heterogeneous network systems. To minimize the negative impact of TE, we develop numerical simulation and experiment techniques that emulate large-scale multilayer transport networks.

[1]  Masayuki Murata,et al.  Dynamic resource allocation mechanism for managed self-organization , 2011, 2011 13th Asia-Pacific Network Operations and Management Symposium.

[2]  Junichi Kani,et al.  Decomposition-based VNF placement algorithm in TDM-WDM-based optical aggregation network , 2018, NOMS 2018 - 2018 IEEE/IFIP Network Operations and Management Symposium.

[3]  Eiji Oki,et al.  Adaptive Virtual Network Topology Control Based on Attractor Selection , 2010, Journal of Lightwave Technology.

[4]  Mikkel Thorup,et al.  Internet traffic engineering by optimizing OSPF weights , 2000, Proceedings IEEE INFOCOM 2000. Conference on Computer Communications. Nineteenth Annual Joint Conference of the IEEE Computer and Communications Societies (Cat. No.00CH37064).

[5]  Biswanath Mukherjee,et al.  Some principles for designing a wide-area WDM optical network , 1996, TNET.

[6]  D. Zibar,et al.  Machine Learning Techniques in Optical Communication , 2016 .

[7]  Eiji Oki,et al.  Gradually Reconfiguring Virtual Network Topologies Based on Estimated Traffic Matrices , 2007, IEEE/ACM Transactions on Networking.

[8]  Masayuki Murata,et al.  Experimental demonstration of adaptive virtual network topology control mechanism based on SDTN architecture , 2013 .