%0 Conference Proceedings
%T Fragmentation Metrics in Spectrally-Spatially Flexible Optical Networks
%+ Wroclaw University of Science and Technology
%+ Politecnico di Milano [Milan] (POLIMI)
%+ Department of Systems and Computer Networks [Wroclaw]
%A Lechowicz, Piotr
%A Tornatore, Massimo
%A Włodarczyk, Adam
%A Walkowiak, Krzysztof
%Z Part 1: Regular Papers
%< avec comité de lecture
%( Lecture Notes in Computer Science
%B 23th International IFIP Conference on Optical Network Design and Modeling (ONDM)
%C Athens, Greece
%Y Anna Tzanakaki
%Y Manos Varvarigos
%Y Raul Muñoz
%Y Reza Nejabati
%Y Noboru Yoshikane
%Y Markos Anastasopoulos
%Y Johann Marquez-Barja
%I Springer International Publishing
%3 Optical Network Design and Modeling
%V LNCS-11616
%P 235-247
%8 2019-05-13
%D 2019
%R 10.1007/978-3-030-38085-4_21
%K Spectrally-spatially flexible optical networks
%K Network fragmentation
%K Network optimization
%K Routing
%K Space
%K Spectrum allocation
%Z Computer Science [cs]
%Z Computer Science [cs]/Networking and Internet Architecture [cs.NI]Conference papers
%X Spectrally-spatially flexible optical networks (SS-FONs) are proposed as a solution for future traffic requirements in optical backbone networks. As SS-FONs operate within flex-grid, the provisioning of lightpaths spanning multiple frequency slots results in spectrum fragmentation, especially in presence of dynamic traffic. Fragmentation, in turn, may lead to blocking of dynamic requests due to the lack of sufficiently-large free spectral windows. In this paper, to reach a better understanding of fragmentation in SS-FON, we extend several metrics used in (single-core) elastic optical networks to measure the fragmentation in SS-FONs. Next, we apply these metrics to a dynamic-routing algorithm with the goal of minimizing bandwidth blocking. Finally, we analyze the impact of spatial continuity constraint (SCC) on the network fragmentation. Simulations run on two representative network topologies show that the root mean square factor metric yields the best performance in terms of blocking when compared to other analyzed metrics.
%G English
%Z TC 6
%Z WG 6.10
%2 https://inria.hal.science/hal-03200685/document
%2 https://inria.hal.science/hal-03200685/file/484327_1_En_21_Chapter.pdf
%L hal-03200685
%U https://inria.hal.science/hal-03200685
%~ IFIP-LNCS
%~ IFIP
%~ IFIP-TC
%~ IFIP-WG
%~ IFIP-TC6
%~ IFIP-LNCS-11616
%~ IFIP-ONDM
%~ IFIP-WG6-10