ranslucent optical networks exploit the advantages of both transparent optical networks (where connections are switched in the optical domain) and opaque networks (where connections are optically terminated in each intermediate node and switched in the electrical domain)[1]. On the one hand, optical transparency offers considerable bandwidth at low cost. On the other hand, by performing opto-electronic signal regeneration at some of the intermediate nodes, it is possible to recover the signal degradation due to physical impairments. Both linear physical impairments (e.g., amplified spontaneous emission noise, chromatic dispersion, and polarization mode dispersion) and non-linear physical impairments due to intra-and inter-channel effects (e.g., self-phase modulation, four-wave mixing, cross-phase modulation, and cross-talk) contribute to the degradation of the optical signal quality. Such effects are especially critical for high data rates and limited wavelength spacing [2]. Opto-electronic regenerators are used to reamplify, reshape, and retime the optical signal (i.e., 3R regeneration) with the aim of guaranteeing the quality of transmission (QoT) required by the endto-end connections.In translucent optical networks, a requested connection can be supported either by a transparent lightpath, that is, a single all-optical segment, or by a translucent lightpath, that is, a sequence of all-optical segments connected by nodes that opto-electronically regenerate the signal. Thus, a careful regenerator placement and an intelligent regenerator utilization are fundamental for designing and managing cost-effective translucent optical networks with QoT guarantees. Several studies focused on centralized schemes for regenerator placement and routing and wavelength assignment in translucent optical networks [1, 3, 4] when connection requests are known in advance (i.e., static traffic scenario).Translucent optical networks with dynamic connection requests present additional cross-layer challenges. In [5], a framework is proposed to address these challenges assuming that updated information is available at each node. A first challenge is the regenerator placement, which should be tailored to the dynamic scenario. Indeed, specific algorithms are required to account not only for the present and estimated future network traffic, but also to account for the dynamic provisioning and rerouting of network resources [6]. Other challenges are the QoT evaluation and the dissemination of QoT-related information. The work in [7] proposes routing solutions when QoT information is inaccurate or outdated, for example, due to coarse measurements of QoT parameters and reduced availability of monitoring equipment. Moreover, another main challenge is the study of strategies for regenerator discovery and selection. Such strategies must be designed while keeping in mind that network state information may be available only locally and may change frequently due to the dynamic nature of the connection requests. All these issues T T
AbstractThe evolut...
