Potentialities and Criticalities of Flexible-Rate Transponders in DWDM Networks: A Statistical Approach

Abstract

We propose a novel method to assess physical layer potentialities of core optical networks aimed at finding solutions that better exploit the installed equipment. We focus on the use of flexible-rate transponders for the implementation of the elastic paradigm on the state-ofthe-art dense wavelength-division-multiplexed fixed-grid network scenarios. We make use of the waveplane-based routing and wavelength assignment algorithm presented in Dai et al. [J. Lightwave Technol., vol. 33, p. 3815, 2015] to implement a progressive statistical loading of the analyzed network topology, and perform a Monte Carlo analysis delivering a statistical characterization of the average bit rate per lightpath together with the assessment of network blocking. The proposed method allows for the identification of criticalities in terms of link congestion and lightpath quality of transmission, addressing solutions by identifying network bottlenecks. We apply the proposed method to a large pan-European network topology comparing two different transmission techniques for the implementations of flexible-rate transponders: pure PM-m-QAM versus hybrid modulation formats. Over this realistic network example, besides displaying the overall statistics for the average bit rate per lightpath, we show statistics for critical lightpaths and congested fiber links.Index Terms-Optical fiber communications; Optical fiber networks; Waveplane-based network performance analysis.A76 J. OPT. COMMUN. NETW./VOL. 8, NO. 7/JULY 2016 Cantono et al.1943-0620/16/070A76-10 Journal

Statistical Assessment of Open Optical Networks

“…As a first SNAP analysis, we review the results presented in [7]. Here, we have derived the average bit-rate per LP < R b,λ > by means of given-traffic investigation as static metric for the network physical layer.…”

“…In this section, we describe in detail the SNAP algorithm. SNAP has been introduced in [24] and used in [7,[26][27][28][29][30][31][32][33]]. An extensive discussion on the application of SNAP can be also found in [34].…”

“…To perform the aforementioned studies, we propose what we call a Statistical Network Assessment Process (SNAP). This methodology is based on the waveplane-based routing and wavelength assignment (RWA) [5,6] and performs a loading of the network through a Monte Carlo algorithm (MCA) [7] in which at each iteration corresponds to a different realization of the set of lightpath (LP) allocation requests. The set of traffic requests between two nodes of the network can be finite and given a priori or the network can be progressively loaded generating data connection requests according to a certain probability distribution until a stop criterion.…”

Throughput Gains From Adaptive Transceivers in Nonlinear Elastic Optical Networks

“…For optical communications networks techniques include minimum cut to estimate throughput upper bounds, Monte-Carlo simulations to route sequential [26], [27] or dynamic demands to find the blocking load and integer linear program (ILP) based multicommodity flow solutions [36].…”

“…Such techniques have been used to compare RWA algorithms [22], [23] and the advantages of adaptive networking [24], [25] for dynamic networks. Monte-Carlo techniques with sequential loading techniques have also been used [26] and more recently the SNAP, statistical network assessment process, algorithm [27] has been developed. The stochastic nature of the demands means the traffic matrix is less well defined and the RWA solution may skew towards more easily accommodated demands.…”