123 research outputs found

    Quality of Transmission Aware Optical Networking Using Enhanced Gaussian Noise Model

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    We present a new joint routing, wavelength, and power allocation method for optical network planning. The introduced gradient-based convex optimization approach has a lower computational complexity, compared to common linear programming techniques, suitable for both static as well as time-critical dynamic network planning with fast convergence requirement. The proposed scheme takes physical-layer impairments into account, using the enhanced Gaussian noise nonlinear model. In contrast to methods exploiting the theoretical full link spectrum utilization assumption (fully occupied fiber-optic C-hand spectrum), we focus on maximizing the network achievable rate and minimum signal-to-noise ratio (SNR) margin of networks with partial spectrum utilization in their links, relevant to the majority of empirical metro network scenarios. According to numerical results, the network achievable rate can be improved around 17% by performing power optimization over the individual launch power of network lightpaths compared to optimizing a single flat (equal) launch power for all the lightpaths. Moreover, the minimum SNR margin of the simulated network is improved by about 23 dB. Finally, it is observed that maximizing the network minimum SNR margin needs the launch power of each lightpath to be proportional to the total nonlinear interference noise efficiency influencing the lightpath

    On the offline physical layer impairment aware RWA algorithms in transparent optical networks: state-of-the-art and beyond

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    In transparent optical networks with no regeneration, the problem of capacity allocation to traffic demands is called "Roting and Wavelength Assignment". Much work on this topic recently has focused on the dynamic case, whereby demands arrive and must be served in real-time. In addition, due to lack of regeneration, physical impairments accumulate as light propagates and QoT may become inappropiate (e.g., too high Bit Error Rate). Considering the physical layer impairments in the network planning phase gives rise to a class of RWA algorithms: offline Physical Layer Impairment Aware- (PLIA-)RWA. This paper makes a survey of such algorithms, proposes a taxonomy, and a comparison between these algorithms for common metrics. We also propose a novel offline PLIA-RWA algorithm, called POLIO-RWA, and show through simulations that it decreases blocking rate compared with other PLIA-RWA algorithms.Postprint (published version

    Experimental demonstration of cognitive provisioning and alien wavelength monitoring in multi-domain EON

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    This paper proposes a cognitive multi-domain EON architecture with machine-learning aided RMSA and alien wavelength monitoring. Testbed experiments show modulation format recognition, QoT monitoring and cognitive routing for a 160 GBd alien multi-wavelength lightpath.Peer ReviewedPostprint (published version

    Enabling Technologies for Cognitive Optical Networks

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    Experimental demonstration of machine-learning-aided QoT estimation in multi-domain elastic optical networks with alien wavelengths

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    In multi-domain elastic optical networks with alien wavelengths, each domain needs to consider intradomain and interdomain alien traffic to estimate and guarantee the required quality of transmission (QoT) for each lightpath and perform provisioning operations. This paper experimentally demonstrates an alien wavelength performance monitoring technique and machine-learning-aided QoT estimation for lightpath provisioning of intradomain/interdomain traffic. Testbed experiments demonstrate modulation format recognition, QoT monitoring, and cognitive routing for a 160 Gbaud alien multi-wavelength lightpath. By using experimental training datasets from the testbed and an artificial neural network, we demonstrated an accurate optical-signal-to-noise ratio prediction with an accuracy of ∼95% when using 1200 data points

    Traffic engineering in dynamic optical networks

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    Traffic Engineering (TE) refers to all the techniques a Service Provider employs to improve the efficiency and reliability of network operations. In IP over Optical (IPO) networks, traffic coming from upper layers is carried over the logical topology defined by the set of established lightpaths. Within this framework then, TE techniques allow to optimize the configuration of optical resources with respect to an highly dynamic traffic demand. TE can be performed with two main methods: if the demand is known only in terms of an aggregated traffic matrix, the problem of automatically updating the configuration of an optical network to accommodate traffic changes is called Virtual Topology Reconfiguration (VTR). If instead the traffic demand is known in terms of data-level connection requests with sub-wavelength granularity, arriving dynamically from some source node to any destination node, the problem is called Dynamic Traffic Grooming (DTG). In this dissertation new VTR algorithms for load balancing in optical networks based on Local Search (LS) techniques are presented. The main advantage of using LS is the minimization of network disruption, since the reconfiguration involves only a small part of the network. A comparison between the proposed schemes and the optimal solutions found via an ILP solver shows calculation time savings for comparable results of network congestion. A similar load balancing technique has been applied to alleviate congestion in an MPLS network, based on the efficient rerouting of Label-Switched Paths (LSP) from the most congested links to allow a better usage of network resources. Many algorithms have been developed to deal with DTG in IPO networks, where most of the attention is focused on optimizing the physical resources utilization by considering specific constraints on the optical node architecture, while very few attention has been put so far on the Quality of Service (QoS) guarantees for the carried traffic. In this thesis a novel Traffic Engineering scheme is proposed to guarantee QoS from both the viewpoint of service differentiation and transmission quality. Another contribution in this thesis is a formal framework for the definition of dynamic grooming policies in IPO networks. The framework is then specialized for an overlay architecture, where the control plane of the IP and optical level are separated, and no information is shared between the two. A family of grooming policies based on constraints on the number of hops and on the bandwidth sharing degree at the IP level is defined, and its performance analyzed in both regular and irregular topologies. While most of the literature on DTG problem implicitly considers the grooming of low-speed connections onto optical channels using a TDM approach, the proposed grooming policies are evaluated here by considering a realistic traffic model which consider a Dynamic Statistical Multiplexing (DSM) approach, i.e. a single wavelength channel is shared between multiple IP elastic traffic flows
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