Abstract
In order to cope with the increase of the final user traffic, operators and vendors are pushing towards physical layer aware networking as a way to maximize the network capacity. To this aim, optical networks are becoming more and more open by exposing physical parameters enabling fast and reliable estimation of the lightpath quality of transmission. This comes in handy not only from the point of view of the planning and managing of the optical paths but also on a more general picture of the whole optical network performance. In this work, the Statistical Network Assessment Process (SNAP) is presented. SNAP is an algorithm allowing for estimating different network metrics such as blocking probability or link saturation, by generating traffic requests on a graph abstraction of the physical layer. Being aware of the physical layer parameters and transceiver technologies enables assessing their impact on high level network figures of merit. Together with a detailed description of the algorithm, we present a comprehensive review of several results on the networking impact of multirate transceivers, flex-grid spectral allocation as a means to finely exploit lightpath capacity and of different Space Division Multiplexing (SDM) solutions.
Highlights
The IP traffic forecasts [1] show that the final user will rule the traffic increase
The multi-rate transceiver based on pure modulation formats, i.e., polarization multiplexed-quadrature amplitude modulation of cardinality M (PM M-QAM) constellations, delivers a finite and discrete set of rates, determined by the maximum cardinality of the constellation M supported by the available quality of transmission (QoT) of the selected LP
As a static metric targeting blocking probability (BP) = 10−2, we have reported as vertical bars in Figure 8c; the total traffic gain of uncoupled fiber ribbons (UFR) and strongly coupled multi-core fibers (SCMCF) with respect to the SCMCF w/o nonlinear distortion mitigation (NLM) taken as reference
Summary
The IP traffic forecasts [1] show that the final user will rule the traffic increase. Given a description of the network topology and transmission technologies, SNAP is capable of evaluating several metrics such as statistics of the average bit-rate per LP < Rb,λ > for all possible LP demands arrangement, blocking probability (BP) vs allocated traffic and average load of each link. Such statistical characterization can be used to derive general and statistically effective assessment of the network performance.
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