Wavelengths switching and allocation algorithms in multicast technology using m-arity tree networks topology

This thesis was submitted for the degree of Doctor of Philosophy and awarded by Brunel University London.In this thesis, the m-arity tree networks have been investigated to derive equations for their nodes, links and required wavelengths. The relationship among all parameters such as leaves nodes, destinations, paths and wavelengths has been found. Three situations have been explored, firstly when just one server and the leaves nodes are destinations, secondly when just one server and all other nodes are destinations, thirdly when all nodes are sources and destinations in the same time. The investigation has included binary, ternary, quaternary and finalized by general equations for all m-arity tree networks. Moreover, a multicast technology is analysed in this thesis to transmit data carried by specific wavelengths to several clients. Wavelengths multicast switching is well examined to propose split-convert-split-convert (S-C-S-C) multicast switch which consists of light splitters and wavelengths converters. It has reduced group delay by 13% and 29% compared with split-convert (S-C) and split-convert-split (S-C-S) multicast switches respectively. The proposed switch has also increased the received signal power by a significant value which reaches 28% and 26.92% compared with S-C-S and S-C respectively. In addition, wavelengths allocation algorithms in multicast technology are proposed in this thesis using tree networks topology. Distributed scheme is adopted by placing wavelength assignment controller in all parents’ nodes. Two distributed algorithms proposed shortest wavelength assignment (SWA) and highest number of destinations with shortest wavelength assignment (HND-SWA) algorithms to increase the received signal power, decrease group delay and reduce dispersion. The performance of the SWA algorithm was almost better or same as HND-SWA related to the power, dispersion and group delay but they are always better than other two algorithms. The required numbers of wavelengths and their utilised converters have been examined and calculated for the researched algorithms. The HND-SWA has recorded the superior performance compared with other algorithms. It has reduced number of utilised wavelengths up to about 19% and minimized number of the used wavelengths converters up to about 29%. Finally, the centralised scheme is discussed and researched and proposed a centralised highest number of destinations (CHND) algorithm with static and dynamic scenarios to reduce network capacity decreasing (Cd) after each wavelengths allocation. The CDHND has reduced (Cd) by about 16.7% compared with the other algorithms

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

Design and provisioning of WDM networks for traffic grooming

Wavelength Division Multiplexing (WDM) is the most viable technique for utilizing the enormous amounts of bandwidth inherently available in optical fibers. However, the bandwidth offered by a single wavelength in WDM networks is on the order of tens of Gigabits per second, while most of the applications\u27 bandwidth requirements are still subwavelength. Therefore, cost-effective design and provisioning of WDM networks require that traffic from different sessions share bandwidth of a single wavelength by employing electronic multiplexing at higher layers. This is known as traffic grooming. Optical networks supporting traffic grooming are usually designed in a way such that the cost of the higher layer equipment used to support a given traffic matrix is reduced. In this thesis, we propose a number of optimal and heuristic solutions for the design and provisioning of optical networks for traffic grooming with an objective of network cost reduction. In doing so, we address several practical issues. Specifically, we address the design and provisioning of WDM networks on unidirectional and bidirectional rings for arbitrary unicast traffic grooming, and on mesh topologies for arbitrary multipoint traffic grooming. In multipoint traffic grooming, we address both multicast and many-to-one traffic grooming problems. We provide a unified frame work for optimal and approximate network dimensioning and channel provisioning for the generic multicast traffic grooming problem, as well as some variants of the problem. For many-to-one traffic grooming we propose optimal as well as heuristic solutions. Optimal formulations which are inherently non-linear are mapped to an optimal linear formulation. In the heuristic solutions, we employ different problem specific search strategies to explore the solution space. We provide a number of experimental results to show the efficacy of our proposed techniques for the traffic grooming problem in WDM networks

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