A survey on OFDM-based elastic core optical networking

Orthogonal frequency-division multiplexing (OFDM) is a modulation technology that has been widely adopted in many new and emerging broadband wireless and wireline communication systems. Due to its capability to transmit a high-speed data stream using multiple spectral-overlapped lower-speed subcarriers, OFDM technology offers superior advantages of high spectrum efficiency, robustness against inter-carrier and inter-symbol interference, adaptability to server channel conditions, etc. In recent years, there have been intensive studies on optical OFDM (O-OFDM) transmission technologies, and it is considered a promising technology for future ultra-high-speed optical transmission. Based on O-OFDM technology, a novel elastic optical network architecture with immense flexibility and scalability in spectrum allocation and data rate accommodation could be built to support diverse services and the rapid growth of Internet traffic in the future. In this paper, we present a comprehensive survey on OFDM-based elastic optical network technologies, including basic principles of OFDM, O-OFDM technologies, the architectures of OFDM-based elastic core optical networks, and related key enabling technologies. The main advantages and issues of OFDM-based elastic core optical networks that are under research are also discussed

On QoS-assured degraded provisioning in service-differentiated multi-layer elastic optical networks

The emergence of new network applications is driving network operators to not only fulfill dynamic bandwidth requirements, but offer various grades of service. Degraded provisioning provides an effective solution to flexibly allocate resources in various dimensions to reduce blocking for differentiated demands when network congestion occurs. In this work, we investigate the novel problem of online degraded provisioning in service-differentiated multi-layer networks with optical elasticity. Quality of Service (QoS) is assured by service-holding-time prolongation and immediate access as soon as the service arrives without set-up delay. We decompose the problem into degraded routing and degraded resource allocation stages, and design polynomial-time algorithms with the enhanced multi-layer architecture to increase the network flexibility in temporal and spectral dimensions. Illustrative results verify that we can achieve significant reduction of network service failures, especially for requests with higher priorities. The results also indicate that degradation in optical layer can increase the network capacity, while the degradation in electric layer provides flexible time-bandwidth exchange.Comment: accepted by IEEE GLOBECOM 201

Modulation-Adaptive Link-Disjoint Path Selection Model for 1 + 1 Protected Elastic Optical Networks

In elastic optical networks (EONs), an appropriate modulation technique is adapted according to the distance of an optical path. A robust modulation technique with a large number of spectrum slots is considered for longer distance optical paths, and a less robust modulation technique with a small number of spectrum slots is used for shorter distance optical paths. When an optical path is configured, the number of required spectrum slots is determined based on the nonlinear relationship between the optical path length and the number of utilized spectrum slots. Minimizing the total path lengths does not always minimize the total number of required spectrum slots for configuring an optical path, which decreases the spectrum utilization. This paper introduces a modulation-adaptive link-disjoint path selection model by considering a step function based on realistic modulation formats in order to minimize the total number of utilized spectrum slots in 1 + 1 protected EONs. We formulate the modulation-adaptive link-disjoint path selection problem as an integer linear programming (ILP). We prove that the modulation-adaptive link-disjoint path selection problem is NP-complete. By using an optimization solver, we solve the ILP problem for different backbone networks, namely, Japan Photonic Network (JPN48), German 17 Network, and COST 239 Network, within a practical time. Numerical results obtained from performance evaluation indicate that the introduced model reduces the number of utilized spectrum slots compared to the conventional schemes

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

Traffic-grooming- and multipath-routing-enabled impairment-aware elastic optical networks

Traffic grooming and multipath routing are two techniques that are widely adopted to increase the performance of traditional wavelength division multiplexed networks. They have been recently applied in elastic optical networks to increase spectral efficiency. In this study, we investigate the potential gains by jointly employing the two techniques in combination with a realistic physical impairment model. To allocate resources and quantify spectral efficiency gains over existing impairment-aware schemes, we present an analytical optimization formulation for small networks and a heuristic for large networks. Through numerical simulations, we demonstrate that traffic grooming and multipath routing, together, increase spectral efficiency and reduce resource consumption over existing schemes. We show that the proposed scheme offers significant performance improvements in networks with low degrees of connectivity, high traffic loads, and long links