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

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

Combination of Advanced Reservation and Resource Periodic Arrangement for RMSA in EON with Deep Reinforcement Learning

The Elastic Optical Networks (EON) provide a solution to the massive demand for connections and extremely high data traffic with the Routing Modulation and Spectrum Assignment (RMSA) as a challenge. In previous RMSA research, there was a high blocking probability because the route to be passed by the K-SP method with a deep neural network approach used the First Fit policy, and the modulation problem was solved with Modulation Format Identification (MFI) or BPSK using Deep Reinforcement Learning. The issue might be apparent in spectrum assignment because of the influence of Advanced Reservation (AR) and Resource Periodic Arrangement (RPA), which is a decision block on a connection request path with both idle and active data traffic. The study’s limitation begins with determining the modulation of m = 1 and m = 4, followed by the placement of frequencies, namely 13 with a combination of standard block frequencies 41224–24412, so that the simulation results are less than 0.0199, due to the combination of block frequency slices with spectrum allocation rule techniques.

BER-Adaptive RMLSA Algorithm for Wide-Area Flexible Optical Networks

Wide-area optical networks face significant transmission challenges due to the relentless growth of bandwidth demands experienced nowadays. Network operators must consider the relationship between modulation format and maximum reach for each connection request due to the accumulation of physical layer impairments in optical fiber links, to guarantee a minimum quality of service (QoS) and quality of transmission (QoT) to all connection requests. In this work, we present a BER-adaptive solution to solve the routing, modulation format, and spectrum assignment (RMLSA) problem for wide-area elastic optical networks. Our main goal is to maximize successful connection requests in wide-area networks while choosing modulation formats with the highest efficiency possible. Consequently, our technique uses an adaptive bit-error-rate (BER) threshold to achieve communication with the best QoT in the most efficient manner, using the strictest BER value and the modulation format with the smallest bandwidth possible. Additionally, the proposed algorithm relies on 3R regeneration devices to enable long-distances communications if transparent communication cannot be achieved. We assessed our method through simulations for various network conditions, such as the number of regenerators per node, traffic load per user, and BER threshold values. In a scenario without regenerators, the BER-Adaptive algorithm performs similarly to the most relaxed fixed BER threshold studied in blocking probability. However, it ensures a higher QoT to most of the connection requests. The proposed algorithm thrives with the use of regenerators, showing the best performance among the studied solutions, enabling long-distance communications with a high QoT and low blocking probability

Optimized traffic profile for FlexGrid optical networks

This work is focused on studying the connections’ bandwidth distribution effects on the FlexGrid network performance. An accurate study of spectrum occupancy in heavy loaded FlexGrid optical networks is carried out. This analysis is useful to figure out which traffic profiles are more suitable for this kind of networks. Two different cases are considered with respect to the offered connections. In the elastic case, connections sizes can take any value from 1 to a maximum number of spectrum slots. In the multi-rate case, only three connections sizes are allowed. It is demonstrated that by generating the connections with some specific statistical properties, the network performance is improved. These properties are derived from the theoretical study of spectrum occupation in ideal conditions. The main contribution of this work is therefore the proposal of an Optimum traffic profile which allows to efficiently use the spectrum in FlexGrid optical networks. The gain obtained by generating the proposed traffic profile is evaluated by means of simulations at the link as well as at the whole network level.Peer ReviewedPostprint (author's final draft

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