Considering Transmission Impairments in Wavelength Routed Networks

Abstract — We consider dynamically reconfigurable wavelength routed networks in which lightpaths carrying IP traffic are on demand established. We face the Routing and Wavelength Assignment problem considering as constraints the physical impairments that arise in all-optical wavelength routed networks. In particular, we study the impact of the physical layer when establishing a lightpath in transparent optical network. Because no signal transformation and regeneration at intermediate nodes occurs, noise and signal distortions due to non-ideal transmission devices are accumulated along the physical path, and they degrade the quality of the received signal. We propose a simple yet accurate model for the physical layer which consider both static and dynamic impairments, i.e., nonlinear effects depending on the actual wavelength/lightpath allocation. We then propose a novel algorithm to solve the RWA problem that explicitly considers the physical impairments. Simulation results show the effectiveness of our approach. Indeed, when the transmission impairments come into play, an accurate selection of paths and wavelengths which is driven by physical consideration is mandatory. I

Challenges and Requirements for Introducing Impairment-awareness into the Management and Control Planes of ASON/GMPLS WDM Networks

The absence of electrical regenerators in transparent WDM networks significantly contributes to reduce the overall network cost. In transparent WDM networks, a proper resource allocation requires that the presence of physical impairments in Routing and Wavelength Assignment (RWA) and lightpath provisioning be taken into account. In this article a centralized, a hybrid centralized-distributed and two distributed approaches that integrate information about most relevant physical impairments in RWA and lightpath provisioning are presented and assessed. Both centralized and hybrid approaches perform a centralized path computation at the management-plane level, utilizing physical impairment information, while the lightpath provisioning is done by the management plane or the control plane, respectively. The distributed approaches fall entirely within the scope of the ASON/GMPLS control plane. For these two approaches, we provide functional requirements, architectural functional blocks, and protocol extensions for implementing either an impairment-aware real-time RWA, or a lighpath provisioning based on impairment-aware signaling

An integrated view on monitoring and compensation for dynamic optical networks: from management to physical layer

A vertical perspective, ranging from management and routing to physical layer options, concerning dynamic network monitoring and compensation of impairments (M&C), is given. Feasibility, reliability, and performance improvements on reconfigurable transparent networks are expected to arise from the consolidated assessment of network management and control specifications, as a more accurate evaluation of available M&C techniques. In the network layer, physical parameters aware algorithms are foreseen to pursue reliable network performance. In the physical layer, some new M&C methods were developed and rating of the state-of-the-art reported in literature is given. Optical monitoring implementation and viability is discussed.Publicad

An analysis of Regenerator Placement strategies for a Translucent OBS network architecture

Most research works in optical burst switching (OBS) networks do not take into account the impact of physical layer impairments (PLIs) either by considering fully transparent (i.e., using optical 3R regeneration) or opaque (i.e., electrical 3R regeneration) networks. However, both solutions are not feasible for different reasons. In this paper, we propose a novel translucent OBS (T-OBS) network architecture which aims at bridging the gap between the transparent and opaque solutions. In order to evaluate its performance, a formulation of the routing and regenerator placement and dimensioning problem (RRPD) is presented. Since such formulation results in a complex problem, we also propose several alternative heuristic strategies. In particular, we evaluate the trade-off between optimality and execution times provided by these methods. Finally, we conduct a series of simulation experiments that prove that the T-OBS network model proposed effectively deals with burst losses caused by the impact of PLIs and ensures that the overall network performance remains unaffected.Preprin

Performance of translucent optical networks under dynamic traffic and uncertain physical-layer information

This paper investigates the performance of translucent Optical Transport Networks (OTNs) under different traffic and knowledge conditions, varying from perfect knowledge to drifts and uncertainties in the physical-layer parameters. Our focus is on the regular operation of a translucent OTN, i.e., after the dimensioning and regenerator placement phase. Our contributions can be summarized as follows. Based on the computation of the Personick’s Q factor, we introduce a new methodology for the assessment of the optical signal quality along a path, and show its application on a realistic example. We analyze the performance of both deterministic and predictive RWA techniques integrating this signal quality factor Q in the lightpath computation process. Our results confirm the effectiveness of predictive techniques to deal with the typical drifts and uncertainties in the physical-layer parameters, in contrast to the superior efficacy of deterministic approaches in case of perfect knowledge. Conversely to most previous works, where all wavelengths are assumed to have the same characteristics, we examine the case when the network is not perfectly compensated, so the Maximum Transmission Distance (MTD) of the different wavelength channels may vary. We show that blocking might increase dramatically when the MTD of the different wavelength channels is overlooked.Postprint (published version

An Overview on Application of Machine Learning Techniques in Optical Networks

Today's telecommunication networks have become sources of enormous amounts of widely heterogeneous data. This information can be retrieved from network traffic traces, network alarms, signal quality indicators, users' behavioral data, etc. Advanced mathematical tools are required to extract meaningful information from these data and take decisions pertaining to the proper functioning of the networks from the network-generated data. Among these mathematical tools, Machine Learning (ML) is regarded as one of the most promising methodological approaches to perform network-data analysis and enable automated network self-configuration and fault management. The adoption of ML techniques in the field of optical communication networks is motivated by the unprecedented growth of network complexity faced by optical networks in the last few years. Such complexity increase is due to the introduction of a huge number of adjustable and interdependent system parameters (e.g., routing configurations, modulation format, symbol rate, coding schemes, etc.) that are enabled by the usage of coherent transmission/reception technologies, advanced digital signal processing and compensation of nonlinear effects in optical fiber propagation. In this paper we provide an overview of the application of ML to optical communications and networking. We classify and survey relevant literature dealing with the topic, and we also provide an introductory tutorial on ML for researchers and practitioners interested in this field. Although a good number of research papers have recently appeared, the application of ML to optical networks is still in its infancy: to stimulate further work in this area, we conclude the paper proposing new possible research directions

CDC ROADM design tradeoffs due to physical layer impairments in optical networks

In this work, we assess the impact of several physical layer impairments (PLIs) on the performance of optical networks based on colorless, directionless and contentionless reconfigurable optical add/drop multiplexers (ROADMs), through Monte-Carlo simulation, and considering polarization division multiplexing 4 and 16 quadrature amplitude modulation (QAM) signals, at 28 GBaud, for 37.5 GHz optical channels. The PLIs taken into account are the amplified spontaneous emission noise, optical filtering, in-band crosstalk and nonlinear interference noise caused by Kerr effect. A detailed model of the ROADM node is built considering two typical ROADM architectures, broadcast and select (B&S) and route and select (R&S), and two different add/drop structures, multicast switches (MCSs) and wavelength selective switches (WSSs), resulting in four different ROADM node scenarios. Our results have shown that for 16QAM signals, the B&S ROADMs with WSSs-based add/drop structures is the scenario that has the best relation cost/performance, foreseeing its use in metro networks, while for 4QAM signals, the R&S ROADM with WSSs-based add/drop structure scenario allows a larger ROADM cascade at an expectable lower cost anticipating its implementation in long-haul networks

Cross-layer modeling and optimization of next-generation internet networks

Scaling traditional telecommunication networks so that they are able to cope with the volume of future traffic demands and the stringent European Commission (EC) regulations on emissions would entail unaffordable investments. For this very reason, the design of an innovative ultra-high bandwidth power-efficient network architecture is nowadays a bold topic within the research community. So far, the independent evolution of network layers has resulted in isolated, and hence, far-from-optimal contributions, which have eventually led to the issues today's networks are facing such as inefficient energy strategy, limited network scalability and flexibility, reduced network manageability and increased overall network and customer services costs. Consequently, there is currently large consensus among network operators and the research community that cross-layer interaction and coordination is fundamental for the proper architectural design of next-generation Internet networks. This thesis actively contributes to the this goal by addressing the modeling, optimization and performance analysis of a set of potential technologies to be deployed in future cross-layer network architectures. By applying a transversal design approach (i.e., joint consideration of several network layers), we aim for achieving the maximization of the integration of the different network layers involved in each specific problem. To this end, Part I provides a comprehensive evaluation of optical transport networks (OTNs) based on layer 2 (L2) sub-wavelength switching (SWS) technologies, also taking into consideration the impact of physical layer impairments (PLIs) (L0 phenomena). Indeed, the recent and relevant advances in optical technologies have dramatically increased the impact that PLIs have on the optical signal quality, particularly in the context of SWS networks. Then, in Part II of the thesis, we present a set of case studies where it is shown that the application of operations research (OR) methodologies in the desing/planning stage of future cross-layer Internet network architectures leads to the successful joint optimization of key network performance indicators (KPIs) such as cost (i.e., CAPEX/OPEX), resources usage and energy consumption. OR can definitely play an important role by allowing network designers/architects to obtain good near-optimal solutions to real-sized problems within practical running times