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Service provisioning can be enhanced with spectrally spatially flexible optical networks (SS-FONs) with multicore fibers; however, intercore crosstalk (XT) is a dominant impairment that complicates the problem of maintaining the quality of transmission (QoT) and resource allocation. The selection of modulation formats (MFs), due to their unique XT sensitivities, further increases the complexity. The routing, modulation, core, and spectrum assignment (RMCSA) problem must select the resources carefully to exploit the available capacity while meeting the desired QoT. In this paper, we propose an RMCSA algorithm called the tridental resource assignment (TRA) algorithm for transparent SS-FONs, and its variant, translucency-aware TRA (TaTRA), for translucent SS-FONs. TRA balances three different factors that affect network performance under dynamic resource allocation. We consider translucent networks with flexible regeneration and with and without modulation and spectrum conversion. Our resource assignment approach includes both an offline network planning component to calculate path priorities and an online/dynamic provisioning component to allocate resources. Extensive simulation experiments performed in realistic network scenarios indicate that TRA and TaTRA significantly reduce the bandwidth blocking probability by several orders of magnitude in some cases. 

Emerging inter-datacenter applications involving data transferred, processed, and analyzed at multiple data centers, such as virtual machine migrations, real-time data backup, remote desktop, and virtual data centers, can be modeled as virtual network requests that share computing and spectrum resources of a common substrate physical interdatacenter network. Recent advances make flexible optical networks an ideal candidate for meeting the dynamic and heterogeneous connection demands between datacenters. In this paper, we address the static (offline) version of the virtual network embedding problem in flexible optical networks equipped with sliceable bandwidth variable transponders (SBVTs). The objective is to minimize the total number of required SBVTs in the network. An Integer Linear Programming (ILP) formulation is presented, lower bounds are derived, and four heuristics are proposed and compared. Simulation results are presented to show the effectiveness of the proposed approaches.