551 research outputs found

    Multicast routing from a set of data centers in elastic optical networks

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    This paper introduces the Multi-Server Multicast (MSM) approach for Content Delivery Networks (CDNs) delivering services offered by a set of Data Centers (DCs). All DCs offer the same services. The network is an Elastic Optical Network (EON) and for a good performance, routing is performed directly at the optical layer. Optical switches have heterogeneous capacities, that is, light splitting is not available in all switches. Moreover, frequency slot conversion is not possible in any of them. We account for the degradation that optical signals suffer both in the splitting nodes, as well as across fiber links to compute their transmission reach. The optimal solution of the MSM is a set of light-hierarchies. This multicast route contains a light trail from one of the DCs to each of the destinations with respect to the optical constraints while optimizing an objective (e.g., minimizing a function). Finding such a structure is often an NP-hard problem. The light-hierarchies initiated from different DCs permit delivering the multicast session to all end-users with a better utilization of the optical resources, while also reducing multicast session latencies, as contents can be delivered from such DCs closer to end-users. We propose an Integer Linear Programming (ILP) formulation to optimally decide on which light-hierarchies should be setup. Simulation results illustrate the benefits of MSM in two reference backbone networks.Peer ReviewedPostprint (author's final draft

    Utilization balancing algorithms for dynamic multicast scheduling problem in EON

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    Dynamic data transfer demands are often being a challenge for present communication networks, as they appear in unpredictable time and must be satisfied prior to deadline. Important kind are the multi-target demands occurring in task of replication, backup, database synchronization or file transferring in pear-to-pear networks. Optimal scheduling usually depends of the nature of transport network. In the paper we consider dynamic deadline-driven multicast scheduling problem over elastic optical network. We propose the method for improving link utilization by traffic balance for multicast demands. We present few heuristic algorithms and results of experiments, proving the benefits of balancing concept

    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

    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

    Towards Terabit Carrier Ethernet and Energy Efficient Optical Transport Networks

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    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

    Enhanced WDM-OFDM-PON System Based on Higher Data Transmitted with Modulation Technique

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    ABSTRACT:- Studies among the field communication system existing technique and proposes and by experimentation demonstrate a multiuser wavelengthdivision-multiplexing passive optical network (WDM-PON) system combining with orthogonal frequency division multiple (OFDM) technique. A tunable multiwavelength optical comb is intended to provide flat optical lines for helping the configuration of the multiple source-free optical network units WDM-OFDM-PON system supported normal single-mode fiber (SSMF). In WDM based on fiber, optical network communications using wavelength with multiplex or demultiplex may be a technology that multiplexes a variety of optical carrier signals onto one fiber by victimization completely different wavelengths of optical device lightweight. this system allows bidirectional communications over one strand of fiber, also as multiplication of capability and calculate BER (Bit Error Rate) and OSNR (optical signal noise ratio) finally; a comparison of by experimentation achieved receiver sensitivities and transmission distances victimization these receivers is given. The very best spectral potency and longest transmission distance at the very best bit rate. WDM based applications like transmission data, medical imaging data, and digital audio data and video conferencing data are information measure-intensive with the Advance in optical technology providing verdant bandwidth, it's natural to increase the multicast construct to optical networks so as to realize increased performance. Our projected scheme (PGA) based on information load transmitted capability improve supported higher information transmitted over these channels and high data up to develop in Matlab tool and using optical Interleaved the OFDM model and analysis the performance of the WDM-PON system

    QuickCast: Fast and Efficient Inter-Datacenter Transfers using Forwarding Tree Cohorts

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    Large inter-datacenter transfers are crucial for cloud service efficiency and are increasingly used by organizations that have dedicated wide area networks between datacenters. A recent work uses multicast forwarding trees to reduce the bandwidth needs and improve completion times of point-to-multipoint transfers. Using a single forwarding tree per transfer, however, leads to poor performance because the slowest receiver dictates the completion time for all receivers. Using multiple forwarding trees per transfer alleviates this concern--the average receiver could finish early; however, if done naively, bandwidth usage would also increase and it is apriori unclear how best to partition receivers, how to construct the multiple trees and how to determine the rate and schedule of flows on these trees. This paper presents QuickCast, a first solution to these problems. Using simulations on real-world network topologies, we see that QuickCast can speed up the average receiver's completion time by as much as 10×10\times while only using 1.04×1.04\times more bandwidth; further, the completion time for all receivers also improves by as much as 1.6×1.6\times faster at high loads.Comment: [Extended Version] Accepted for presentation in IEEE INFOCOM 2018, Honolulu, H
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