1,418 research outputs found

    A survey on OFDM-based elastic core optical networking

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    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

    Optimal RWA for SDM Optical Network under Dynamic Traffic

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    With the rapid increase in demand for data transmission in our generation where Internet and cloud concepts play an essential role, it has become mandatory that we handle data most efficiently. A promising solution to overcome the capacity crunch problem which is so evident in future is applications of Space Division Multiplexing, where we explore the remaining unused domain that is the spectral and spatial domain. Space Division Multiplexing using multi-core fibers (MCF), and few-mode fibers (FMF) has been studied in our work to enhance the data-carrying capacity of optical fibers while minimizing the transmission cost per bit. The objective is to develop a path protection scheme to handle communication requests in the data center (DC) networks using elastic optical networking and space division multiplexing (SDM). Our approach to this problem is to 1) determining the initial allocation of light path on the topology, 2) possible spectrum allocation using the flex-grid flexible-SDM model, 3) choose the best possible route to minimize the number of subcarriers needed for data transfer. We propose to evaluate the developed Integer Linear Programming (ILP) formulation based on this scheme

    A Novel Solution to the Dynamic Routing and Wavelength Assignment Problem in Transparent Optical Networks

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    We present an evolutionary programming algorithm for solving the dynamic routing and wavelength assignment (DRWA) problem in optical wavelength-division multiplexing (WDM) networks under wavelength continuity constraint. We assume an ideal physical channel and therefore neglect the blocking of connection requests due to the physical impairments. The problem formulation includes suitable constraints that enable the algorithm to balance the load among the individuals and thus results in a lower blocking probability and lower mean execution time than the existing bio-inspired algorithms available in the literature for the DRWA problems. Three types of wavelength assignment techniques, such as First fit, Random, and Round Robin wavelength assignment techniques have been investigated here. The ability to guarantee both low blocking probability without any wavelength converters and small delay makes the improved algorithm very attractive for current optical switching networks.Comment: 12 Pages, IJCNC Journal 201

    An Overview on Application of Machine Learning Techniques in Optical Networks

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    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

    Protection and restoration algorithms for WDM optical networks

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    Currently, Wavelength Division Multiplexing (WDM) optical networks play a major role in supporting the outbreak in demand for high bandwidth networks driven by the Internet. It can be a catastrophe to millions of users if a single optical fiber is somehow cut off from the network, and there is no protection in the design of the logical topology for a restorative mechanism. Many protection and restoration algorithms are needed to prevent, reroute, and/or reconfigure the network from damages in such a situation. In the past few years, many works dealing with these issues have been reported. Those algorithms can be implemented in many ways with several different objective functions such as a minimization of protection path lengths, a minimization of restoration times, a maximization of restored bandwidths, etc. This thesis investigates, analyzes and compares the algorithms that are mainly aimed to guarantee or maximize the amount of remaining bandwidth still working over a damaged network. The parameters considered in this thesis are the routing computation and implementation mechanism, routing characteristics, recovering computation timing, network capacity assignment, and implementing layer. Performance analysis in terms of the restoration efficiency, the hop length, the percentage of bandwidth guaranteed, the network capacity utilization, and the blocking probability is conducted and evaluated

    Spatial-spectral flexible optical networking:enabling switching solutions for a simplified and efficient SDM network platform

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    The traffic carried by core optical networks grows at a steady but remarkable pace of 30-40% year-over-year. Optical transmissions and networking advancements continue to satisfy the traffic requirements by delivering the content over the network infrastructure in a cost and energy efficient manner. Such core optical networks serve the information traffic demands in a dynamic way, in response to requirements for shifting of traffics demands, both temporally (day/night) and spatially (business district/residential). However as we are approaching fundamental spectral efficiency limits of singlemode fibers, the scientific community is pursuing recently the development of an innovative, all-optical network architecture introducing the spatial degree of freedom when designing/operating future transport networks. Spacedivision- multiplexing through the use of bundled single mode fibers, and/or multi-core fibers and/or few-mode fibers can offer up to 100-fold capacity increase in future optical networks. The EU INSPACE project is working on the development of a complete spatial-spectral flexible optical networking solution, offering the network ultra-high capacity, flexibility and energy efficiency required to meet the challenges of delivering exponentially growing traffic demands in the internet over the next twenty years. In this paper we will present the motivation and main research activities of the INSPACE consortium towards the realization of the overall project solution

    Computation of Dispersion Penalty for the Analysis of WDM Link Quality

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    The provisioning of light path over WDM/DWDM network is a challenging factor, which depends on various physical layer impairments such as dispersion in fiber. We proposed a light path provisioning mechanism by considering the effect of dispersion in fiber termed as dispersion penalty, which is the prominent effect at high speed WDM network. In the case of non-ideal filter, light path provisioning without considering the physical layer impairments does not satisfy the signal quality guaranteed transmission. In this algorithm, Quality of Service is described in terms of dispersion penalty values with an assumption that the entire client has a requirement of penalty less than 2 Db. Here we have analyzed the degradation in bit rate due to the effect of dispersion. The maximum possible length of fiber is also reduced due to high dispersion in fiber. Dispersion penalty is the increment in the received power to eliminate the effect of some undesirable distortion in optical fiber. Dispersion penalty is calculated in terms of bit rate and band width for each data path. The proposal of dispersion penalty budgeting is to ensure that the optical power reaching the receiver is adequate under all circumstances. The proposed algorithm defines a mechanism for effective light path provisioning by comparing the requirement of client and the available resources of the network
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