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

A new proposal of an efficient algorithm for routing and wavelength assignment in optical networks.

The routing and wavelength assignment (RWA) algorithms used in optical networks are critical to achieve good network performance. However, despite several previous studies to optimize the RWA, which is classified as an NP-Hard, it seems that there is not, a priori, any solution that would lead to standardization of this process. This article presents the proposed RWA algorithm based on a Generic Objective Function (GOF) which aims to establish a base from which it is possible to develop a standard or multiple standards for optical networks. The GOF algorithm introduces the concept of implicit constraint, which guarantees a simple solution to a problem not as trivial as the RWA

Artificial intelligence (AI) methods in optical networks: A comprehensive survey

Producción CientíficaArtificial intelligence (AI) is an extensive scientific discipline which enables computer systems to solve problems by emulating complex biological processes such as learning, reasoning and self-correction. This paper presents a comprehensive review of the application of AI techniques for improving performance of optical communication systems and networks. The use of AI-based techniques is first studied in applications related to optical transmission, ranging from the characterization and operation of network components to performance monitoring, mitigation of nonlinearities, and quality of transmission estimation. Then, applications related to optical network control and management are also reviewed, including topics like optical network planning and operation in both transport and access networks. Finally, the paper also presents a summary of opportunities and challenges in optical networking where AI is expected to play a key role in the near future.Ministerio de Economía, Industria y Competitividad (Project EC2014-53071-C3-2-P, TEC2015-71932-REDT

Resource Management in Survivable Multi-Granular Optical Networks

The last decade witnessed a wild growth of the Internet traffic, promoted by bandwidth-hungry applications such as Youtube, P2P, and VoIP. This explosive increase is expected to proceed with an annual rate of 34% in the near future, which leads to a huge challenge to the Internet infrastructure. One foremost solution to this problem is advancing the optical networking and switching, by which abundant bandwidth can be provided in an energy-efficient manner. For instance, with Wavelength Division Multiplexing (WDM) technology, each fiber can carry a mass of wavelengths with bandwidth up to 100 Gbits/s or higher. To keep up with the traffic explosion, however, simply scaling the number of fibers and/or wavelengths per fiber results in the scalability issue in WDM networks. One major motivation of this dissertation is to address this issue in WDM networks with the idea of waveband switching (WBS). This work includes the author\u27s study on multiple aspects of waveband switching: how to address dynamic user demand, how to accommodate static user demand, and how to achieve a survivable WBS network. When combined together, the proposed approaches form a framework that enables an efficient WBS-based Internet in the near future or the middle term. As a long-term solution for the Internet backbone, the Spectrum Sliced Elastic Optical Path (SLICE) Networks recently attract significant interests. SLICE aims to provide abundant bandwidth by managing the spectrum resources as orthogonal sub-carriers, a finer granular than wavelengths of WDM networks. Another important component of this dissertation is the author\u27s timely study on this new frontier: particulary, how to efficiency accommodate the user demand in SLICE networks. We refer to the overall study as the resource management in multi-granular optical networks. In WBS networks, the multi-granularity includes the fiber, waveband, and wavelength. While in SLICE networks, the traffic granularity refers to the fiber, and the variety of the demand size (in terms of number of sub-carriers)

Dynamic wavelength allocation in IP/WDM metro access networks

Ankara : The Department of Electrical and Electronics Engineering and the Institute of Engineering and Science of Bilkent University, 2008.Thesis (Ph.D.) -- Bilkent University, 2008.Includes bibliographical references leaves 132-139.Increasing demand for bandwidth and proliferation of packet based traffic have been causing architectural changes in the communications infrastructure. In this evolution, metro networks face both the capacity and dynamic adaptability constraints. The increase in the access and backbone speeds result in high bandwidth requirements, whereas the popularity of wireless access and limited number of customers in metro area necessitates traffic adaptability. Traditional architecture which has been optimized for carrying circuit-switched connections, is far from meeting these requirements. Recently, several architectures have been proposed for future metro access networks. Nearly all of these solutions support dynamic allocation of bandwidth to follow fluctuations in the traffic demand. However, reconfiguration policies that can be used in this process have not been fully explored yet. In this thesis, dynamic wavelength allocation (DWA) policies for IP/WDM metro access networks with reconfiguration delays are considered. Reconfiguration actions incur a cost since a portion of the capacity becomes idle in the reconfiguration period due to the signalling latencies and tuning times of optical transceivers. Exact formulation of the DWA problem is developed as a Markov Decision Process (MDP) and a new cost function is proposed to attain both throughput efficiency and fairness. For larger problems, a heuristic approach based on first passage probabilities is developed. The performance of the method is evaluated under both stationary and non-stationary traffic conditions. The effects of relevant network and traffic parameters, such as delay and flow size are also discussed. Finally, performance bounds for the DWA methods are derived.Yetginer, EmrePh.D

On greening optical access networks

With the remarkable growth of fiber-based services, the number of FTTx subscribers has been dramatically increasing in recent years. Owing to the environmental concern, reducing energy consumption of optical access networks has become an important issue for network designers. In Ethernet passive optical network (EPON), the optical line terminal (OLT) located at the central office broadcasts the downstream traffic to all optical network units (ONUs), each of which checks all arrival downstream packets to obtain those destined to itself. Since traffic of ONUs changes dynamically, properly defining the sleep mode for idle ONUs can potentially save a significant amount of energy. However, it is challenging to shut down an ONU receiver as the ONU needs to receive some downstream control packets to perform upstream transmission. In this framework, a novel sleep control scheme is proposed to address the downstream issue which can efficiently put ONU receivers to sleep. This dissertation further defines multiple levels of power saving in which the ONU disables certain functions based on the upstream and downstream traffic load. The proposed schemes are completely compatible with the multi-point control protocol (MPCP) and EPON standards. Elimination of the handshake process makes the sleep control schemes more efficient. Currently, OLTs also consume a significant amount of energy in EPON. Therefore, reducing energy consumption of OLT is as important as reducing energy consumption of ONUs; such requirement becomes even more urgent as OLT keeps increasing its provisioning data rate, and higher data rate provisioning usually implies higher energy consumption. Thus, a novel energy-efficient OLT structure, which guarantees services of end users with a smallest number of power-on OLT line cards, is proposed. More specifically, the number of power-on OLT line cards is adapted to the real-time incoming traffic. Also, to avoid service disruption resulted by powering off OLT line cards, a proper optical switch is equipped in OLT to dynamically configure the communications between OLT line cards and ONUs. By deploying a semi-Markov based technique, the performance characteristics of the sleep control scheme such as delay and energy-saving are theoretically analyzed. It is shown that, with proper settings of sleep control parameters, the proposed scheme can save a significant amount of energy in EPON

An Erlang multirate loss model supporting elastic traffic under the threshold policy

In this paper, we propose a multirate teletraffic loss model of a single link with certain bandwidth capacity that accommodates Poisson arriving calls, which can tolerate bandwidth compression (elastic traffic), under the threshold policy. When compression occurs, the service time of new and in-service calls increases. The threshold policy provides different QoS among service-classes by limiting the number of calls of a service-class up to a pre-defined threshold, which can be different for each service-class. Due to the bandwidth compression mechanism, the steady state probabilities in the proposed model do not have a product form solution. However, we approximate the model by a reversible Markov chain, and prove recursive formulas for the calculation of call blocking probabilities and link utilization. The accuracy of the proposed formulas is verified through simulation and found to be very satisfactory