Predictive autonomic transmission for low-cost low-margin metro optical networks

Low-cost low-margin implementation plays an essential role in upgrading optical metro networks required for future 5G ecosystem. In this regard, low-resolution analog-to-digital converters can be used in coherent optical transponders to reduce cost and power consumption. However, the resulting transmission systems become more sensitive to physical layer fluctuations like the events caused by fiber stressing. Such fluctuations might have a strong impact on the quality of transmission (QoT) of the signals. To guarantee robust operation, soft decision forward error correction (FEC) techniques are required to guarantee zero post-FEC bit error rate (BER) transmission, which could increase the power consumption of the receiver and thus operational expenses. In this paper, we aim at minimizing power consumption while keeping zero post-FEC errors by means of a predictive autonomic transmission agent (ATA) based on machine learning. We present a sophisticated ATA model that, taking advantage of real-time monitoring of state of polarization traces and the corresponding pre-FEC BER, predicts the right FEC configuration for short-term operation, thus requiring minimum power consumption. In addition, we propose a complementary long-term prediction of excessive pre-FEC BER to enable remote reconfiguration at the transmitter side through the network controller. A set of experimental measurements is used to train and validate the proposed ATA system. Exhaustive numerical analysis allows concluding that ATA based on artificial neural network predictors achieves the maximum QoT robustness with 80% power consumption reductions compared to static FEC configuration.The research leading to these results has received funding from the European Commission for the H2020-ICT-2016-2 METRO-HAUL project (G.A. 761727), from the AEI/FEDER TWINS project (TEC2017-90097-R), and from the Catalan Institution for Research and Advanced Studies (ICREA).Peer ReviewedPostprint (author's final draft

In-operation planning in flexgrid optical core networks

New generation applications, such as cloud computing or video distribution, can run in a telecom cloud infrastructure where the datacenters (DCs) of telecom operators are integrated in their networks thus, increasing connections' dynamicity and resulting in time-varying traffic capacities, which might also entail changes in the traffic direction along the day. As a result, a flexible optical technology able to dynamically set-up variable-capacity connections, such as flexgrid, is needed. Nonetheless, network dynamicity might entail network performance degradation thus, requiring re-optimizing the network while it is in operation. This thesis is devoted to devise new algorithms to solve in-operation network planning problems aiming at enhancing the performance of optical networks and at studying their feasibility in experimental environments. In-operation network planning requires from an architecture enabling the deployment of algorithms that must be solved in stringent times. That architecture can be based on a Path Computation Element (PCE) or a Software Defined Networks controller. In this thesis, we assume the former split in a front-end PCE, in charge of provisioning paths and handling network events, and a specialized planning tool in the form of a back-end PCE responsible for solving in-operation planning problems. After the architecture to support in-operation planning is assessed, we focus on studying the following applications: 1) Spectrum fragmentation is one of the most important problems in optical networks. To alleviate it to some extent without traffic disruption, we propose a hitless spectrum defragmentation strategy. 2) Each connection affected by a failure can be recovered using multiple paths to increase traffic restorability at the cost of poor resource utilization. We propose re-optimizing the network after repairing the failure to aggregate and reroute those connections to release spectral resources. 3) We study two approaches to provide multicast services: establishing a point-to-multipoint connections at the optical layer and using multi-purpose virtual network topologies (VNT) to serve both unicast and multicast connectivity requests. 4) The telecom cloud infrastructure, enables placing contents closer to the users. Based on it, we propose a hierarchical content distribution architecture where VNTs permanently interconnect core DCs and metro DCs periodically synchronize contents to the core DCs. 5) When the capacity of the optical backbone network becomes exhausted, we propose using a planning tool with access to inventory and operation databases to periodically decide the equipment and connectivity to be installed at the minimum cost reducing capacity overprovisioning. 6) In multi-domain multi-operator scenarios, a broker on top of the optical domains can provision multi-domain connections. We propose performing intra-domain spectrum defragmentation when no contiguous spectrum can be found for a new connection request. 7) Packet nodes belonging to a VNT can collect and send incoming traffic monitoring data to a big data repository. We propose using the collected data to predict next period traffic and to adapt the VNT to future conditions. The methodology followed in this thesis consists in proposing a problem statement and/or a mathematical formulation for the problems identified and then, devising algorithms for solving them. Those algorithms are simulated and then, they are experimentally assessed in real test-beds. This thesis demonstrates the feasibility of performing in-operation planning in optical networks, shows that it enhances the performance of the network and validates the feasibility of its deployment in real networks. It shall be mentioned that part of the work reported in this thesis has been done within the framework of several research projects, namely IDEALIST (FP7-ICT-2011-8) and GEANT (238875) funded by the EC and SYNERGY (TEC2014-59995-R) funded by the MINECO.Les aplicacions de nova generació, com ara el cloud computing o la distribució de vídeo, es poden executar a infraestructures de telecom cloud (TCI) on operadors integren els seus datacenters (DC) a les seves xarxes. Aquestes aplicacions fan que incrementi tant la dinamicitat de les connexions, com la variabilitat de les seves capacitats en el temps, arribant a canviar de direcció al llarg del dia. Llavors, cal disposar de tecnologies òptiques flexibles, tals com flexgrid, que suportin aquesta dinamicitat a les connexions. Aquesta dinamicitat pot degradar el rendiment de la xarxa, obligant a re-optimitzar-la mentre és en operació. Aquesta tesis està dedicada a idear nous algorismes per a resoldre problemes de planificació sobre xarxes en operació (in-operation network planning) per millorar el rendiment de les xarxes òptiques i a estudiar la seva factibilitat en entorns experimentals. Aquests problemes requereixen d’una arquitectura que permeti desplegar algorismes que donin solucions en temps restrictius. L’arquitectura pot estar basada en un Element de Computació de Rutes (PCE) o en un controlador de Xarxes Definides per Software. En aquesta tesis, assumim un PCE principal encarregat d’aprovisionar rutes i gestionar esdeveniments de la xarxa, i una eina de planificació especialitzada en forma de PCE de suport per resoldre problemes d’in-operation planning. Un cop validada l’arquitectura que dona suport a in-operation planning, estudiarem les següents aplicacions: 1) La fragmentació d’espectre és un dels principals problemes a les xarxes òptiques. Proposem reduir-la en certa mesura, fent servir una estratègia que no afecta al tràfic durant la desfragmentació. 2) Cada connexió afectada per una fallada pot ser recuperada fent servir múltiples rutes incrementant la restaurabilitat de la xarxa, tot i empitjorar-ne la utilització de recursos. Proposem re-optimitzar la xarxa després de reparar una fallada per agregar i re-enrutar aquestes connexions tractant d’alliberar recursos espectrals. 3) Estudiem dues solucions per aprovisionar serveis multicast: establir connexions punt-a-multipunt sobre la xarxa òptica i utilitzar Virtual Network Topologies (VNT) multi-propòsit per a servir peticions de connectivitat tant unicast com multicast. 4) La TCI permet mantenir els continguts a prop dels usuaris. Proposem una arquitectura jeràrquica de distribució de continguts basada en la TCI, on els DC principals s’interconnecten per mitjà de VNTs permanents i els DCs metropolitans periòdicament sincronitzen continguts amb els principals. 5) Quan la capacitat de la xarxa òptica s’exhaureix, proposem utilitzar una eina de planificació amb accés a bases de dades d’inventari i operacionals per decidir periòdicament l’equipament i connectivitats a instal·lar al mínim cost i reduir el sobre-aprovisionament de capacitat. 6) En entorns multi-domini multi-operador, un broker per sobre dels dominis òptics pot aprovisionar connexions multi-domini. Proposem aplicar desfragmentació d’espectre intra-domini quan no es pot trobar espectre contigu per a noves peticions de connexió. 7) Els nodes d’una VNT poden recollir i enviar informació de monitorització de tràfic entrant a un repositori de big data. Proposem utilitzar aquesta informació per adaptar la VNT per a futures condicions. La metodologia que hem seguit en aquesta tesis consisteix en formalitzar matemàticament els problemes un cop aquests son identificats i, després, idear algorismes per a resoldre’ls. Aquests algorismes son simulats i finalment validats experimentalment en entorns reals. Aquesta tesis demostra la factibilitat d’implementar mecanismes d’in-operation planning en xarxes òptiques, mostra els beneficis que aquests aporten i valida la seva aplicabilitat en xarxes reals. Part del treball presentat en aquesta tesis ha estat dut a terme en el marc dels projectes de recerca IDEALIST (FP7-ICT-2011-8) i GEANT (238875), finançats per la CE, i SYNERGY (TEC2014-59995-R), finançat per el MINECO.Postprint (published version

Digital transformation and SME internationalisation:unravelling the moderated-mediation role of digital capabilities, digital resilience and digital maturity

PurposeThis study has two main objectives. First, to examine the indirect effects of digital platform capability and digital resilience on digital transformation (DT) outcomes for small- and medium-sized enterprises (SMEs), and second, to investigate how digital business model maturity influences these indirect effects.Design/methodology/approachThe study adopts a quantitative design and collects data through a self-reporting survey from individuals in the technological industries. The Partial Least Squares-Structural Equation Modelling (PLS-SEM) and PLS multi-group analysis examine the measurement and structural models and the significance of differences in indirect paths based on the digital business model maturity level, serving as a moderator.FindingsThe findings of this study provide valuable insights into the internationalisation of digital SMEs. They indicate that digital platform capability and resilience fully mediate, connecting digital resources to SME growth. The study also confirms the digital business model maturity’s positive and significant moderating effect on these indirect relationships.Originality/valueThis research contributes to the existing literature by focusing on the international outcomes of platform ecosystems in developing markets. It explores how digital platform capability and resilience support the digital transformation of SMEs, considering their vulnerability due to their small size. The study also fills a research gap by investigating the relationship between big data, digital leadership and the international growth of digital platforms. Lastly, it explores the role of digital maturity in the relationships between antecedents, determinants and outcomes of digitalisation.<br/

Optimal user association, backhaul routing and switching off in 5G heterogeneous networks with mesh millimeter wave backhaul links

Next generation, i.e., fifth generation (5G), cellular networks will provide a significant higher capacity per area to support the ever-increasing traffic demands. In order to achieve that, many small cells need to be deployed that are connected using a combination of optical fiber links and millimeter-wave (mmWave) backhaul architecture to forward heterogeneous traffic over mesh topologies. In this paper, we present a general optimization framework for the design of policies that optimally solve the problem of where to associate a user, over which links to route its traffic towards which mesh gateway, and which base stations and backhaul links to switch o¿ in order to minimize the energy cost for the network operator and still satisfy the user demands. We develop an optimal policy based on mixed integer linear programming (MILP) which considers different user distribution and traffic demands over multiple time periods. We develop also a fast iterative two-phase solution heuristic, which associates users and calculates backhaul routes to maximize energy savings. Our strategies optimize the backhaul network configuration at each timeslot based on the current demands and user locations. We discuss the application of our policies to backhaul management of mmWave cellular networks in light of current trend of network softwarization (Software-Defined Networking, SDN). Finally, we present extensive numerical simulations of our proposed policies, which show how the algorithms can efficiently trade-off energy consumption with required capacity, while satisfying flow demand requirements.Postprint (author's final draft

Micro Smart Micro-grid and Its Cyber Security Aspects in a Port Infrastructure

Maritime ports are intensive energy areas with a plenty of electrical systems that require an average power of many tens of megawatts (MW). Competitiveness, profits, reduction of pollution, reliability of operations, carbon emission trading are important energy related considerations for any port authority. Current technology allows the deployment of a local micro-grid of the size of tenths of MW, capable of islanded operation in case of emergency and to grant an increasing energy independency. Ownership of the grid permits a large flexibility on prices of energy sold inside the port, trading on local electric market and reduction of pollution. Renewable energy generation has a large impact on costs since features a low marginal cost. Unfortunately the smart grid is a critical asset within the port infrastructure and its intelligence is a high-level target for cyberattacks. Such attacks are often based on malicious software (malware), which makes use of a controlling entity on the network to coordinate and propagate. In this document, we will outline some features of a port smart grid and typical characteristics of cyber-attacks including potential ways to recognize it and suggestion for effective countermeasures

Metabolic connectivity of resting-state networks in alpha synucleinopathies, from prodromal to dementia phase

Previous evidence suggests that the derangement of large-scale brain networks reflects structural, molecular, and functional mechanisms underlying neurodegenerative diseases. Although the alterations of multiple large-scale brain networks in Parkinson’s disease (PD) and Dementia with Lewy Bodies (DLB) are reported, a comprehensive study on connectivity reconfiguration starting from the preclinical phase is still lacking. We aimed to investigate shared and disease-specific changes in the large-scale networks across the Lewy Bodies (LB) disorders spectrum using a brain metabolic connectivity approach. We included 30 patients with isolated REM sleep behavior disorder (iRBD), 28 with stable PD, 30 with DLB, and 30 healthy controls for comparison. We applied seed-based interregional correlation analyses (IRCA) to evaluate the metabolic connectivity in the large-scale resting-state networks, as assessed by [18F]FDG-PET, in each clinical group compared to controls. We assessed metabolic connectivity changes by applying the IRCA and specific connectivity metrics, such as the weighted and unweighted Dice similarity coefficients (DC), for the topographical similarities. All the investigated large-scale brain resting-state networks showed metabolic connectivity alterations, supporting the widespread involvement of brain connectivity within the alpha-synuclein spectrum. Connectivity alterations were already evident in iRBD, severely affecting the posterior default mode, attentive and limbic networks. Strong similarities emerged in iRBD and DLB that showed comparable connectivity alterations in most large-scale networks, particularly in the posterior default mode and attentive networks. Contrarily, PD showed the main connectivity alterations limited to motor and somatosensory networks. The present findings reveal that metabolic connectivity alterations in the large-scale networks are already present in the early iRBD phase, resembling the DLB metabolic connectivity changes. This suggests and confirms iRBD as a risk condition for progression to the severe LB disease phenotype. Of note, the neurobiology of stable PD supports its more benign phenotype

Trust-based mechanisms for secure communication in cognitive radio networks

Cognitive radio (CR) technology was introduced to solve the problem of spectrum scarcity to support the growth of wireless communication. However, the inherent properties of CR technology make such networks more vulnerable to attacks. This thesis is an effort to develop a trust-based framework to ensure secure communication in CRN by authenticating trustworthy nodes to share spectrum securely and increasing system's availability and reliability by selecting the trustworthy key nodes in CRNs