1,408 research outputs found

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

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    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

    Center for Aeronautics and Space Information Sciences

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    This report summarizes the research done during 1991/92 under the Center for Aeronautics and Space Information Science (CASIS) program. The topics covered are computer architecture, networking, and neural nets

    Advances in Optical Amplifiers

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    Optical amplifiers play a central role in all categories of fibre communications systems and networks. By compensating for the losses exerted by the transmission medium and the components through which the signals pass, they reduce the need for expensive and slow optical-electrical-optical conversion. The photonic gain media, which are normally based on glass- or semiconductor-based waveguides, can amplify many high speed wavelength division multiplexed channels simultaneously. Recent research has also concentrated on wavelength conversion, switching, demultiplexing in the time domain and other enhanced functions. Advances in Optical Amplifiers presents up to date results on amplifier performance, along with explanations of their relevance, from leading researchers in the field. Its chapters cover amplifiers based on rare earth doped fibres and waveguides, stimulated Raman scattering, nonlinear parametric processes and semiconductor media. Wavelength conversion and other enhanced signal processing functions are also considered in depth. This book is targeted at research, development and design engineers from teams in manufacturing industry, academia and telecommunications service operators

    Optics and virtualization as data center network infrastructure

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    The emerging cloud services have motivated a fresh look at the design of data center network infrastructure in multiple layers. To transfer the huge amount of data generated by many data intensive applications, data center network has to be fast, scalable and power efficient. To support flexible and efficient sharing in cloud services, service providers deploy a virtualization layer as part of the data center infrastructure. This thesis explores the design and performance analysis of data center network infrastructure in both physical network and virtualization layer. On the physical network design front, we present a hybrid packet/circuit switched network architecture which uses circuit switched optics to augment traditional packet-switched Ethernet in modern data centers. We show that this technique has substantial potential to improve bisection bandwidth and application performance in a cost-effective manner. To push the adoption of optical circuits in real cloud data centers, we further explore and address the circuit control issues in shared data center environments. On the virtualization layer, we present an analytical study on the network performance of virtualized data centers. Using Amazon EC2 as an experiment platform, we quantify the impact of virtualization on network performance in commercial cloud. Our findings provide valuable insights to both cloud users in moving legacy application into cloud and service providers in improving the virtualization infrastructure to support better cloud services
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