Marc Ruiz

Bio: Marc Ruiz is an academic researcher from Polytechnic University of Catalonia. The author has contributed to research in topics: Network topology & Control reconfiguration. The author has an hindex of 24, co-authored 146 publications receiving 2094 citations.

Modeling the routing and spectrum allocation problem for flexgrid optical networks

Abstract: Flexgrid optical networks are attracting huge interest due to their higher spectrum efficiency and flexibility in comparison with traditional wavelength switched optical networks based on the wavelength division multiplexing technology. To properly analyze, design, plan, and operate flexible and elastic networks, efficient methods are required for the routing and spectrum allocation (RSA) problem. Specifically, the allocated spectral resources must be, in absence of spectrum converters, the same along the links in the route (the continuity constraint) and contiguous in the spectrum (the contiguity constraint). In light of the fact that the contiguity constraint adds huge complexity to the RSA problem, we introduce the concept of channels for the representation of contiguous spectral resources. In this paper, we show that the use of a pre-computed set of channels allows considerably reducing the problem complexity. In our study, we address an off-line RSA problem in which enough spectrum needs to be allocated for each demand of a given traffic matrix. To this end, we present novel integer lineal programming (ILP) formulations of RSA that are based on the assignment of channels. The evaluation results reveal that the proposed approach allows solving the RSA problem much more efficiently than previously proposed ILP-based methods and it can be applied even for realistic problem instances, contrary to previous ILP formulations.

Elastic Spectrum Allocation for Time-Varying Traffic in FlexGrid Optical Networks

Abstract: Elastic flexgrid optical networks (FG-ON) are considered a very promising solution for next-generation optical networks. In this article we focus on lightpath adaptation under variable traffic demands in FG-ON. Specifically, we explore the elastic spectrum allocation (SA) capability of FG-ON and, in this context, we study the effectiveness of three alternative SA schemes in terms of the network performance. To this end, we formulate a Multi-Hour Routing and Spectrum Allocation (MH-RSA) optimization problem and solve it by means of both Integer Linear Programming (ILP) and efficient heuristic algorithms. Since, as numerical results show, the effectiveness of SA schemes highly depends on the traffic demand profile, we formulate some indications on the applicability of elastic SA in FG-ON.

Virtual Network Topology Adaptability Based on Data Analytics for Traffic Prediction

Abstract: The introduction of new services requiring large and dynamic bitrate connectivity can cause changes in the direction of the traffic in metro and even core network segments throughout the day. This leads to large overprovisioning in statically managed virtual network topologies (VNTs), which are designed to cope with the traffic forecast. To reduce expenses while ensuring the required grade of service, in this paper we propose a VNT reconfiguration approach based on data analytics for traffic prediction (VENTURE). It regularly reconfigures the VNT based on the predicted traffic, thus adapting the topology to both the current and the predicted traffic volume and direction. A machine learning algorithm based on an artificial neural network is used to provide robust and adaptive traffic models. The reconfiguration problem that takes as its input the traffic prediction is modeled mathematically, and a heuristic is proposed to solve it in practical times. To support VENTURE, we propose an architecture that allows collecting and storing data from monitoring at the routers and that is used to train predictive models for every origin-destination pair. Exhaustive simulation results of the algorithm, together with the experimental assessment of the proposed architecture, are finally presented.

BER Degradation Detection and Failure Identification in Elastic Optical Networks

Abstract: Optical connections support virtual links in MPLS-over-optical multilayer networks and therefore, errors in the optical layer impact on the quality of the services deployed on such networks. Monitoring the performance of the physical layer allows verifying the proper operation of optical connections, as well as detecting bit error rate (BER) degradations and anticipating connection disruption. In addition, failure identification facilitates localizing the cause of the failure by providing a short list of potential failed elements and enables self-decision making to keep committed service level. In this paper, we analyze several failure causes affecting the quality of optical connections and propose two different algorithms: one focused on detecting significant BER changes in optical connections, named as BANDO, and the other focused on identifying the most probable failure pattern, named as LUCIDA. BANDO runs inside the network nodes to accelerate degradation detection and sends a notification to the LUCIDA algorithm running on the centralized controller. Experimental measures were carried out on two different setups to obtain values for BER and received power and used to generate synthetic data used in subsequent simulations. Results show significant improvement anticipating maximum BER violation with small failure identification errors.

The Design and Analysis of Experiments

Abstract: THE DESIGN AND ANALYSIS OF EXPERIMENTS. By Oscar Kempthorne. New York, John Wiley and Sons, Inc., 1952. 631 pp. $8.50. This book by a teacher of statistics (as well as a consultant for \"experimenters\") is a comprehensive study of the philosophical background for the statistical design of experiment. It is necessary to have some facility with algebraic notation and manipulation to be able to use the volume intelligently. The problems are presented from the theoretical point of view, without such practical examples as would be helpful for those not acquainted with mathematics. The mathematical justification for the techniques is given. As a somewhat advanced treatment of the design and analysis of experiments, this volume will be interesting and helpful for many who approach statistics theoretically as well as practically. With emphasis on the \"why,\" and with description given broadly, the author relates the subject matter to the general theory of statistics and to the general problem of experimental inference. MARGARET J. ROBERTSON

Non-Orthogonal Multiple Access (NOMA) for cellular future radio access

Abstract: Radio access technologies for cellular mobile communications are typically characterized by multiple access schemes, e.g., frequency division multiple access (FDMA), time division multiple access (TDMA), code division multiple access (CDMA), and OFDMA. In the 4th generation (4G) mobile communication systems such as Long-Term Evolution (LTE) (Au et al., Uplink contention based SCMA for 5G radio access. Globecom Workshops (GC Wkshps), 2014. doi:10.1109/GLOCOMW.2014.7063547) and LTE-Advanced (Baracca et al., IEEE Trans. Commun., 2011. doi:10.1109/TCOMM.2011.121410.090252; Barry et al., Digital Communication, Kluwer, Dordrecht, 2004), standardized by the 3rd Generation Partnership Project (3GPP), orthogonal multiple access based on OFDMA or single carrier (SC)-FDMA is adopted. Orthogonal multiple access was a reasonable choice for achieving good system-level throughput performance with simple single-user detection. However, considering the trend in 5G, achieving significant gains in capacity and system throughput performance is a high priority requirement in view of the recent exponential increase in the volume of mobile traffic. In addition the proposed system should be able to support enhanced delay-sensitive high-volume services such as video streaming and cloud computing. Another high-level target of 5G is reduced cost, higher energy efficiency and robustness against emergencies.

Routing and Spectrum Allocation in Elastic Optical Networks: A Tutorial

Abstract: Flexgrid technology is now considered to be a promising solution for future high-speed network design. In this context, we need a tutorial that covers the key aspects of elastic optical networks. This tutorial paper starts with a brief introduction of the elastic optical network and its unique characteristics. The paper then moves to the architecture of the elastic optical network and its operation principle. To complete the discussion of network architecture, this paper focuses on the different node architectures, and compares their performance in terms of scalability and flexibility. Thereafter, this paper reviews and classifies routing and spectrum allocation (RSA) approaches including their pros and cons. Furthermore, various aspects, namely, fragmentation, modulation, quality-of-transmission, traffic grooming, survivability, energy saving, and networking cost related to RSA, are presented. Finally, the paper explores the experimental demonstrations that have tested the functionality of the elastic optical network, and follows that with the research challenges and open issues posed by flexible networks.

An Overview on Application of Machine Learning Techniques in Optical Networks

Abstract: 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 this paper proposing new possible research directions.

Survey: Live Migration and Disaster Recovery over Long-Distance Networks

Abstract: We study the virtual machine live migration (LM) and disaster recovery (DR) from a networking perspective, considering long-distance networks, for example, between data centers. These networks are usually constrained by limited available bandwidth, increased latency and congestion, or high cost of use when dedicated network resources are used, while their exact characteristics cannot be controlled. LM and DR present several challenges due to the large amounts of data that need to be transferred over long-distance networks, which increase with the number of migrated or protected resources. In this context, our work presents the way LM and DR are currently being performed and their operation in long-distance networking environments, discussing related issues and bottlenecks and surveying other works. We also present the way networks are evolving today and the new technologies and protocols (e.g., software-defined networking, or SDN, and flexible optical networks) that can be used to boost the efficiency of LM and DR over long distances. Traffic redirection in a long-distance environment is also an important part of the whole equation, since it directly affects the transparency of LM and DR. Related works and solutions both from academia and the industry are presented.