Semantic scheduling of virtualized infrastructures for scientific workflows

Virtualized Infrastructures are a promising way for providing flexible and dynamic computing solutions for resourceconsuming tasks. Scientific Workflows are one of these kind of tasks, as they need a large amount of computational resources during certain periods of time. To provide the best infrastructure configuration for a workflow it is necessary to explore as many providers as possible taking into account different criteria like Quality of Service, pricing, response time, network latency, etc. Moreover, each one of these new resources must be tuned to provide the tools and dependencies required by each of the steps of the workflow. Working with different infrastructure providers, either public or private using their own concepts and terms, and with a set of heterogeneous applications requires a framework for integrating all the information about these elements. This work proposes semantic technologies for describing and integrating all the information about the different components of the overall system and a set of policies created by the user. Based on this information a scheduling process will be performed to generate an infrastructure configuration defining the set of virtual machines that must be run and the tools that must be deployed on them.

Contributions to Bayesian network learning with applications to neuroscience

Neuronal morphology is a key feature in the study of brain circuits, as it is highly related to information processing and functional identification. Neuronal morphology affects the process of integration of inputs from other neurons and determines the neurons which receive the output of the neurons. Different parts of the neurons can operate semi-independently according to the spatial location of the synaptic connections. As a result, there is considerable interest in the analysis of the microanatomy of nervous cells since it constitutes an excellent tool for better understanding cortical function. However, the morphologies, molecular features and electrophysiological properties of neuronal cells are extremely variable. Except for some special cases, this variability makes it hard to find a set of features that unambiguously define a neuronal type. In addition, there are distinct types of neurons in particular regions of the brain. This morphological variability makes the analysis and modeling of neuronal morphology a challenge. Uncertainty is a key feature in many complex real-world problems. Probability theory provides a framework for modeling and reasoning with uncertainty. Probabilistic graphical models combine statistical theory and graph theory to provide a tool for managing domains with uncertainty. In particular, we focus on Bayesian networks, the most commonly used probabilistic graphical model. In this dissertation, we design new methods for learning Bayesian networks and apply them to the problem of modeling and analyzing morphological data from neurons. The morphology of a neuron can be quantified using a number of measurements, e.g., the length of the dendrites and the axon, the number of bifurcations, the direction of the dendrites and the axon, etc. These measurements can be modeled as discrete or continuous data. The continuous data can be linear (e.g., the length or the width of a dendrite) or directional (e.g., the direction of the axon). These data may follow complex probability distributions and may not fit any known parametric distribution. Modeling this kind of problems using hybrid Bayesian networks with discrete, linear and directional variables poses a number of challenges regarding learning from data, inference, etc. In this dissertation, we propose a method for modeling and simulating basal dendritic trees from pyramidal neurons using Bayesian networks to capture the interactions between the variables in the problem domain. A complete set of variables is measured from the dendrites, and a learning algorithm is applied to find the structure and estimate the parameters of the probability distributions included in the Bayesian networks. Then, a simulation algorithm is used to build the virtual dendrites by sampling values from the Bayesian networks, and a thorough evaluation is performed to show the model’s ability to generate realistic dendrites. In this first approach, the variables are discretized so that discrete Bayesian networks can be learned and simulated. Then, we address the problem of learning hybrid Bayesian networks with different kinds of variables. Mixtures of polynomials have been proposed as a way of representing probability densities in hybrid Bayesian networks. We present a method for learning mixtures of polynomials approximations of one-dimensional, multidimensional and conditional probability densities from data. The method is based on basis spline interpolation, where a density is approximated as a linear combination of basis splines. The proposed algorithms are evaluated using artificial datasets. We also use the proposed methods as a non-parametric density estimation technique in Bayesian network classifiers. Next, we address the problem of including directional data in Bayesian networks. These data have some special properties that rule out the use of classical statistics. Therefore, different distributions and statistics, such as the univariate von Mises and the multivariate von Mises–Fisher distributions, should be used to deal with this kind of information. In particular, we extend the naive Bayes classifier to the case where the conditional probability distributions of the predictive variables given the class follow either of these distributions. We consider the simple scenario, where only directional predictive variables are used, and the hybrid case, where discrete, Gaussian and directional distributions are mixed. The classifier decision functions and their decision surfaces are studied at length. Artificial examples are used to illustrate the behavior of the classifiers. The proposed classifiers are empirically evaluated over real datasets. We also study the problem of interneuron classification. An extensive group of experts is asked to classify a set of neurons according to their most prominent anatomical features. A web application is developed to retrieve the experts’ classifications. We compute agreement measures to analyze the consensus between the experts when classifying the neurons. Using Bayesian networks and clustering algorithms on the resulting data, we investigate the suitability of the anatomical terms and neuron types commonly used in the literature. Additionally, we apply supervised learning approaches to automatically classify interneurons using the values of their morphological measurements. Then, a methodology for building a model which captures the opinions of all the experts is presented. First, one Bayesian network is learned for each expert, and we propose an algorithm for clustering Bayesian networks corresponding to experts with similar behaviors. Then, a Bayesian network which represents the opinions of each group of experts is induced. Finally, a consensus Bayesian multinet which models the opinions of the whole group of experts is built. A thorough analysis of the consensus model identifies different behaviors between the experts when classifying the interneurons in the experiment. A set of characterizing morphological traits for the neuronal types can be defined by performing inference in the Bayesian multinet. These findings are used to validate the model and to gain some insights into neuron morphology. Finally, we study a classification problem where the true class label of the training instances is not known. Instead, a set of class labels is available for each instance. This is inspired by the neuron classification problem, where a group of experts is asked to individually provide a class label for each instance. We propose a novel approach for learning Bayesian networks using count vectors which represent the number of experts who selected each class label for each instance. These Bayesian networks are evaluated using artificial datasets from supervised learning problems. Resumen La morfología neuronal es una característica clave en el estudio de los circuitos cerebrales, ya que está altamente relacionada con el procesado de información y con los roles funcionales. La morfología neuronal afecta al proceso de integración de las señales de entrada y determina las neuronas que reciben las salidas de otras neuronas. Las diferentes partes de la neurona pueden operar de forma semi-independiente de acuerdo a la localización espacial de las conexiones sinápticas. Por tanto, existe un interés considerable en el análisis de la microanatomía de las células nerviosas, ya que constituye una excelente herramienta para comprender mejor el funcionamiento de la corteza cerebral. Sin embargo, las propiedades morfológicas, moleculares y electrofisiológicas de las células neuronales son extremadamente variables. Excepto en algunos casos especiales, esta variabilidad morfológica dificulta la definición de un conjunto de características que distingan claramente un tipo neuronal. Además, existen diferentes tipos de neuronas en regiones particulares del cerebro. La variabilidad neuronal hace que el análisis y el modelado de la morfología neuronal sean un importante reto científico. La incertidumbre es una propiedad clave en muchos problemas reales. La teoría de la probabilidad proporciona un marco para modelar y razonar bajo incertidumbre. Los modelos gráficos probabilísticos combinan la teoría estadística y la teoría de grafos con el objetivo de proporcionar una herramienta con la que trabajar bajo incertidumbre. En particular, nos centraremos en las redes bayesianas, el modelo más utilizado dentro de los modelos gráficos probabilísticos. En esta tesis hemos diseñado nuevos métodos para aprender redes bayesianas, inspirados por y aplicados al problema del modelado y análisis de datos morfológicos de neuronas. La morfología de una neurona puede ser cuantificada usando una serie de medidas, por ejemplo, la longitud de las dendritas y el axón, el número de bifurcaciones, la dirección de las dendritas y el axón, etc. Estas medidas pueden ser modeladas como datos continuos o discretos. A su vez, los datos continuos pueden ser lineales (por ejemplo, la longitud o la anchura de una dendrita) o direccionales (por ejemplo, la dirección del axón). Estos datos pueden llegar a seguir distribuciones de probabilidad muy complejas y pueden no ajustarse a ninguna distribución paramétrica conocida. El modelado de este tipo de problemas con redes bayesianas híbridas incluyendo variables discretas, lineales y direccionales presenta una serie de retos en relación al aprendizaje a partir de datos, la inferencia, etc. En esta tesis se propone un método para modelar y simular árboles dendríticos basales de neuronas piramidales usando redes bayesianas para capturar las interacciones entre las variables del problema. Para ello, se mide un amplio conjunto de variables de las dendritas y se aplica un algoritmo de aprendizaje con el que se aprende la estructura y se estiman los parámetros de las distribuciones de probabilidad que constituyen las redes bayesianas. Después, se usa un algoritmo de simulación para construir dendritas virtuales mediante el muestreo de valores de las redes bayesianas. Finalmente, se lleva a cabo una profunda evaluaci ón para verificar la capacidad del modelo a la hora de generar dendritas realistas. En esta primera aproximación, las variables fueron discretizadas para poder aprender y muestrear las redes bayesianas. A continuación, se aborda el problema del aprendizaje de redes bayesianas con diferentes tipos de variables. Las mixturas de polinomios constituyen un método para representar densidades de probabilidad en redes bayesianas híbridas. Presentamos un método para aprender aproximaciones de densidades unidimensionales, multidimensionales y condicionales a partir de datos utilizando mixturas de polinomios. El método se basa en interpolación con splines, que aproxima una densidad como una combinación lineal de splines. Los algoritmos propuestos se evalúan utilizando bases de datos artificiales. Además, las mixturas de polinomios son utilizadas como un método no paramétrico de estimación de densidades para clasificadores basados en redes bayesianas. Después, se estudia el problema de incluir información direccional en redes bayesianas. Este tipo de datos presenta una serie de características especiales que impiden el uso de las técnicas estadísticas clásicas. Por ello, para manejar este tipo de información se deben usar estadísticos y distribuciones de probabilidad específicos, como la distribución univariante von Mises y la distribución multivariante von Mises–Fisher. En concreto, en esta tesis extendemos el clasificador naive Bayes al caso en el que las distribuciones de probabilidad condicionada de las variables predictoras dada la clase siguen alguna de estas distribuciones. Se estudia el caso base, en el que sólo se utilizan variables direccionales, y el caso híbrido, en el que variables discretas, lineales y direccionales aparecen mezcladas. También se estudian los clasificadores desde un punto de vista teórico, derivando sus funciones de decisión y las superficies de decisión asociadas. El comportamiento de los clasificadores se ilustra utilizando bases de datos artificiales. Además, los clasificadores son evaluados empíricamente utilizando bases de datos reales. También se estudia el problema de la clasificación de interneuronas. Desarrollamos una aplicación web que permite a un grupo de expertos clasificar un conjunto de neuronas de acuerdo a sus características morfológicas más destacadas. Se utilizan medidas de concordancia para analizar el consenso entre los expertos a la hora de clasificar las neuronas. Se investiga la idoneidad de los términos anatómicos y de los tipos neuronales utilizados frecuentemente en la literatura a través del análisis de redes bayesianas y la aplicación de algoritmos de clustering. Además, se aplican técnicas de aprendizaje supervisado con el objetivo de clasificar de forma automática las interneuronas a partir de sus valores morfológicos. A continuación, se presenta una metodología para construir un modelo que captura las opiniones de todos los expertos. Primero, se genera una red bayesiana para cada experto y se propone un algoritmo para agrupar las redes bayesianas que se corresponden con expertos con comportamientos similares. Después, se induce una red bayesiana que modela la opinión de cada grupo de expertos. Por último, se construye una multired bayesiana que modela las opiniones del conjunto completo de expertos. El análisis del modelo consensuado permite identificar diferentes comportamientos entre los expertos a la hora de clasificar las neuronas. Además, permite extraer un conjunto de características morfológicas relevantes para cada uno de los tipos neuronales mediante inferencia con la multired bayesiana. Estos descubrimientos se utilizan para validar el modelo y constituyen información relevante acerca de la morfología neuronal. Por último, se estudia un problema de clasificación en el que la etiqueta de clase de los datos de entrenamiento es incierta. En cambio, disponemos de un conjunto de etiquetas para cada instancia. Este problema está inspirado en el problema de la clasificación de neuronas, en el que un grupo de expertos proporciona una etiqueta de clase para cada instancia de manera individual. Se propone un método para aprender redes bayesianas utilizando vectores de cuentas, que representan el número de expertos que seleccionan cada etiqueta de clase para cada instancia. Estas redes bayesianas se evalúan utilizando bases de datos artificiales de problemas de aprendizaje supervisado.

An online failure prediction system for private IaaS platforms

The size and complexity of cloud environments make them prone to failures. The traditional approach to achieve a high dependability for these systems relies on constant monitoring. However, this method is purely reactive. A more proactive approach is provided by online failure prediction (OFP) techniques. In this paper, we describe a OFP system for private IaaS platforms, currently under development, that combines di_erent types of data input, including monitoring information, event logs, and failure data. In addition, this system operates at both the physical and virtual planes of the cloud, taking into account the relationships between nodes and failure propagation mechanisms that are unique to cloud environments.

EU support mechanisms to promote public private partnerships for financing Trans-European transport infrastructure

Since the mid 80ies the Trans ‐European Transport Network (TEN‐T) policy has been setting the framework for the development of infrastructure for the smooth functioning of the internal market within the European Union (EU). Public Private Partnerships (PPPs) have always been regarded by the EU as a key instrument to promote the TEN‐T.

Do Public Private Partnerships Improve Road Safety? The Case of Toll Concessions in Spain

El Transportation Research Board es un congreso de reconocido prestigio internacional en el ámbito de la investigación del transporte. Aunque las actas publicadas están en formato digital y sin ISSN ni ISBN, lo consideramos lo suficientemente importante como para que se considere en los indicadores. This paper focuses on the implementation of safety based incentives in Public Private Partnerships (PPPs). The aim of this paper is twofold. First, to evaluate whether PPPs lead to an improvement in road safety, when compared with other infrastructure management systems. Second, is to analyze whether the incentives to improve road safety in PPP contracts in Spain have been effective at improving safety performance. To this end, negative binomial regression models have been applied using information from the Spanish high-capacity network covering years 2007-2009. The results showed that even though road safety is highly influenced by variables that are not manageable by the private concessionaire such as the average annual daily traffic, the implementation of safety incentives in PPPs has a positive influence in the reduction of accidents.

How network operators can enhance ambient assisted living applications through next generation networks

Within the technological framework of Information and Communication Technologies (ICT), consumers are currently requesting multimedia services with simplicity of use, reliability, security and service availability through mobile and fixed access. Network operators are proposing the Next Generation Networks (NGN) to address the challenges of providing both services and network convergence. Apart from these considerations, there is a need to provide social and healthcare assistance services in order to support the progressive aging in the elderly population. In order to achieve this objective, the Ambient Assisted Living (AAL) initiative proposes ICT systems and services to promote autonomy and an independent life among the elderly. This paper describes the design and implementation of a group of services, called “service enablers”, which helps AAL applications to be supported in NGN. The presented enablers are identified to support the teleconsulting applications requirements in an NGN environment, involving the implementation of a virtual waiting room, a virtual whiteboard, a multimedia multiconference and a vital-signs monitoring presence status. A use case is defined and implemented to evaluate the developed enablers' performance.

Virtual science hub: an open source platform to enrich science teaching

This paper presents the Virtual Science Hub platform. It is an open source platform that combines a social network, an e-learning authoring tool, a videoconference service and a learning object repository for science teaching enrichment. These four main functionalities fit very well together. The platform was released in April 2012 and since then it has not stopped growing. Finally we present the results of the surveys conducted and the statistics gathered to validate this approach.

A proposal for a modular and application-aware autonomic manager of private cloud infrastructures

Recientemente, el paradigma de la computación en la nube ha recibido mucho interés por parte tanto de la industria como del mundo académico. Las infraestructuras cloud públicas están posibilitando nuevos modelos de negocio y ayudando a reducir costes. Sin embargo, una compañía podría desear ubicar sus datos y servicios en sus propias instalaciones, o tener que atenerse a leyes de protección de datos. Estas circunstancias hacen a las infraestructuras cloud privadas ciertamente deseables, ya sea para complementar a las públicas o para sustituirlas por completo. Por desgracia, las carencias en materia de estándares han impedido que las soluciones para la gestión de infraestructuras privadas se hayan desarrollado adecuadamente. Además, la multitud de opciones disponibles ha creado en los clientes el miedo a depender de una tecnología concreta (technology lock-in). Una de las causas de este problema es la falta de alineación entre la investigación académica y los productos comerciales, ya que aquella está centrada en el estudio de escenarios idealizados sin correspondencia con el mundo real, mientras que éstos consisten en soluciones desarrolladas sin tener en cuenta cómo van a encajar con los estándares más comunes o sin preocuparse de hacer públicos sus resultados. Con objeto de resolver este problema, propongo un sistema de gestión modular para infraestructuras cloud privadas enfocado en tratar con las aplicaciones en lugar de centrarse únicamente en los recursos hardware. Este sistema de gestión sigue el paradigma de la computación autónoma y está diseñado en torno a un modelo de información sencillo, desarrollado para ser compatible con los estándares más comunes. Este modelo divide el entorno en dos vistas, que sirven para separar aquello que debe preocupar a cada actor involucrado del resto de información, pero al mismo tiempo permitiendo relacionar el entorno físico con las máquinas virtuales que se despliegan encima de él. En dicho modelo, las aplicaciones cloud están divididas en tres tipos genéricos (Servicios, Trabajos de Big Data y Reservas de Instancias), para que así el sistema de gestión pueda sacar partido de las características propias de cada tipo. El modelo de información está complementado por un conjunto de acciones de gestión atómicas, reversibles e independientes, que determinan las operaciones que se pueden llevar a cabo sobre el entorno y que es usado para hacer posible la escalabilidad en el entorno. También describo un motor de gestión encargado de, a partir del estado del entorno y usando el ya mencionado conjunto de acciones, la colocación de recursos. Está dividido en dos niveles: la capa de Gestores de Aplicación, encargada de tratar sólo con las aplicaciones; y la capa del Gestor de Infraestructura, responsable de los recursos físicos. Dicho motor de gestión obedece un ciclo de vida con dos fases, para así modelar mejor el comportamiento de una infraestructura real. El problema de la colocación de recursos es atacado durante una de las fases (la de consolidación) por un resolutor de programación entera, y durante la otra (la online) por un heurístico hecho ex-profeso. Varias pruebas han demostrado que este acercamiento combinado es superior a otras estrategias. Para terminar, el sistema de gestión está acoplado a arquitecturas de monitorización y de actuadores. Aquella estando encargada de recolectar información del entorno, y ésta siendo modular en su diseño y capaz de conectarse con varias tecnologías y ofrecer varios modos de acceso. ABSTRACT The cloud computing paradigm has raised in popularity within the industry and the academia. Public cloud infrastructures are enabling new business models and helping to reduce costs. However, the desire to host company’s data and services on premises, and the need to abide to data protection laws, make private cloud infrastructures desirable, either to complement or even fully substitute public oferings. Unfortunately, a lack of standardization has precluded private infrastructure management solutions to be developed to a certain level, and a myriad of diferent options have induced the fear of lock-in in customers. One of the causes of this problem is the misalignment between academic research and industry ofering, with the former focusing in studying idealized scenarios dissimilar from real-world situations, and the latter developing solutions without taking care about how they f t with common standards, or even not disseminating their results. With the aim to solve this problem I propose a modular management system for private cloud infrastructures that is focused on the applications instead of just the hardware resources. This management system follows the autonomic system paradigm, and is designed around a simple information model developed to be compatible with common standards. This model splits the environment in two views that serve to separate the concerns of the stakeholders while at the same time enabling the traceability between the physical environment and the virtual machines deployed onto it. In it, cloud applications are classifed in three broad types (Services, Big Data Jobs and Instance Reservations), in order for the management system to take advantage of each type’s features. The information model is paired with a set of atomic, reversible and independent management actions which determine the operations that can be performed over the environment and is used to realize the cloud environment’s scalability. From the environment’s state and using the aforementioned set of actions, I also describe a management engine tasked with the resource placement. It is divided in two tiers: the Application Managers layer, concerned just with applications; and the Infrastructure Manager layer, responsible of the actual physical resources. This management engine follows a lifecycle with two phases, to better model the behavior of a real infrastructure. The placement problem is tackled during one phase (consolidation) by using an integer programming solver, and during the other (online) with a custom heuristic. Tests have demonstrated that this combined approach is superior to other strategies. Finally, the management system is paired with monitoring and actuators architectures. The former able to collect the necessary information from the environment, and the later modular in design and capable of interfacing with several technologies and ofering several access interfaces.

Diseño y configuración de una red de comunicaciones en un Centro de Contactos - Contact Center

Este proyecto muestra una solución de red para una empresa que presta servicios de Contact Center desde distintas sedes distribuidas geográficamente, utilizando la tecnología de telefonía sobre IP. El objetivo de este proyecto es el de convertirse en una guía de diseño para el despliegue de soluciones de red utilizando los actuales equipos de comunicaciones desarrollados por el fabricante Cisco Systems, Inc., los equipos de seguridad desarrollados por el fabricante Fortinet y los sistemas de telefonía desarrollados por Avaya Inc. y Oracle Corporation, debido a su gran penetración en el mercado y a las aportaciones que cada uno ha realizado en el sector de Contact Center. Para poder proveer interconexión entre las sedes de un Contact Center se procede a la contratación de un acceso a la red MPLS perteneciente a un operador de telecomunicaciones, quien provee conectividad entre las sedes utilizando la tecnología VPN MPLS con dos accesos diversificados entre sí desde cada una de las sedes del Contact Center. El resultado de esta contratación es el aprovechamiento de las ventajas que un operador de telecomunicaciones puede ofrecer a sus clientes, en relación a calidad de servicio, disponibilidad y expansión geográfica. De la misma manera, se definen una serie de criterios o niveles de servicio que aseguran a un Contact Center una comunicación de calidad entre sus sedes, entendiéndose por comunicación de calidad aquella que sea capaz de transmitirse con unos valores mínimos de pérdida de paquetes así como retraso en la transmisión, y una velocidad acorde a la demanda de los servicios de voz y datos. Como parte de la solución, se diseña una conexión redundante a Internet que proporciona acceso a todas las sedes del Contact Center. La solución de conectividad local en cada una de las sedes de un Contact Center se ha diseñado de manera general acorde al volumen de puestos de usuarios y escalabilidad que pueda tener cada una de las sedes. De esta manera se muestran varias opciones asociadas al equipamiento actual que ofrece el fabricante Cisco Systems, Inc.. Como parte de la solución se han definido los criterios de calidad para la elección de los Centros de Datos (Data Center). Un Contact Center tiene conexiones hacia o desde las empresas cliente a las que da servicio y provee de acceso a la red a sus tele-trabajadores. Este requerimiento junto con el acceso y servicios publicados en Internet necesita una infraestructura de seguridad. Este hecho da lugar al diseño de una solución que unifica todas las conexiones bajo una única infraestructura, dividiendo de manera lógica o virtual cada uno de los servicios. De la misma manera, se ha definido la utilización de protocolos como 802.1X para evitar accesos no autorizados a la red del Contact Center. La solución de voz elegida es heterogénea y capaz de soportar los protocolos de señalización más conocidos (SIP y H.323). De esta manera se busca tener la máxima flexibilidad para establecer enlaces de voz sobre IP (Trunk IP) con proveedores y clientes. Esto se logra gracias a la utilización de SBCs y a una infraestructura interna de voz basada en el fabricante Avaya Inc. Los sistemas de VoIP en un Contact Center son los elementos clave para poder realizar la prestación del servicio; por esta razón se elige una solución redundada bajo un entorno virtual. Esta solución permite desplegar el sistema de VoIP desde cualquiera de los Data Center del Contact Center. La solución llevada a cabo en este proyecto está principalmente basada en mi experiencia laboral adquirida durante los últimos siete años en el departamento de comunicaciones de una empresa de Contact Center. He tenido en cuenta los principales requerimientos que exigen hoy en día la mayor parte de empresas que desean contratar un servicio de Contact Center. Este proyecto está dividido en cuatro capítulos. El primer capítulo es una introducción donde se explican los principales escenarios de negocio y áreas técnicas necesarias para la prestación de servicios de Contact Center. El segundo capítulo describe de manera resumida, las principales tecnologías y protocolos que serán utilizados para llevar a cabo el diseño de la solución técnica de creación de una red de comunicaciones para una empresa de Contact Center. En el tercer capítulo se expone la solución técnica necesaria para permitir que una empresa de Contact Center preste sus servicios desde distintas ubicaciones distribuidas geográficamente, utilizando dos Data Centers donde se centralizan las aplicaciones de voz y datos. Finalmente, en el cuarto capítulo se presentan las conclusiones obtenidas tras la elaboración de la presente memoria, así como una propuesta de trabajos futuros, que permitirían junto con el proyecto actual, realizar una solución técnica completa incluyendo otras áreas tecnológicas necesarias en una empresa de Contact Center. Todas las ilustraciones y tablas de este proyecto son de elaboración propia a partir de mi experiencia profesional y de la información obtenida en diversos formatos de la bibliografía consultada, excepto en los casos en los que la fuente es mencionada. ABSTRACT This project shows a network solution for a company that provides Contact Center services from different locations geographically distributed, using the Telephone over Internet Protocol (ToIP) technology. The goal of this project is to become a design guide for performing network solutions using current communications equipment developed by the manufacturer Cisco Systems, Inc., firewalls developed by the manufacturer Fortinet and telephone systems developed by Avaya Inc. and Oracle Corporation, due to their great market reputation and their contributions that each one has made in the field of Contact Center. In order to provide interconnection between its different sites, the Contact Center needs to hire the services of a telecommunications’ operator, who will use the VPN MPLS technology, with two diversified access from each Contact Center’s site. The result of this hiring is the advantage of the benefits that a telecommunications operator can offer to its customers, regarding quality of service, availability and geographical expansion. Likewise, Service Level Agreement (SLA) has to be defined to ensure the Contact Center quality communication between their sites. A quality communication is understood as a communication that is capable of being transmitted with minimum values of packet loss and transmission delays, and a speed according to the demand for its voice and data services. As part of the solution, a redundant Internet connection has to be designed to provide access to every Contact Center’s site. The local connectivity solution in each of the Contact Center’s sites has to be designed according to its volume of users and scalability that each one may have. Thereby, the manufacturer Cisco Systems, Inc. offers several options associated with the current equipment. As part of the solution, quality criteria are being defined for the choice of the Data Centers. A Contact Center has connections to/from the client companies that provide network access to teleworkers. This requires along the access and services published on the Internet, needs a security infrastructure. Therefore is been created a solution design that unifies all connections under a single infrastructure, dividing each services in a virtual way. Likewise, is been defined the use of protocols, such as 802.1X, to prevent unauthorized access to the Contact Center’s network. The voice solution chosen is heterogeneous and capable of supporting best-known signaling protocols (SIP and H.323) in order to have maximum flexibility to establish links of Voice over IP (IP Trunk) with suppliers and clients. This can be achieved through the use of SBC and an internal voice infrastructure based on Avaya Inc. The VoIP systems in a Contact Center are the key elements to be able to provide the service; for this reason a redundant solution under virtual environment is been chosen. This solution allows any of the Data Centers to deploy the VoIP system. The solution carried out in this project is mainly based on my own experience acquired during the past seven years in the communications department of a Contact Center company. I have taken into account the main requirements that most companies request nowadays when they hire a Contact Center service. This project is divided into four chapters. The first chapter is an introduction that explains the main business scenarios and technical areas required to provide Contact Center services. The second chapter describes briefly the key technologies and protocols that will be used to carry out the design of the technical solution for the creation of a communications network in a Contact Center company. The third chapter shows a technical solution required that allows a Contact Center company to provide services from across geographically distributed locations, using two Data Centers where data and voice applications are centralized. Lastly, the fourth chapter includes the conclusions gained after making this project, as well as a future projects proposal, which would allow along the current project, to perform a whole technical solution including other necessary technologic areas in a Contact Center company All illustrations and tables of this project have been made by myself from my professional experience and the information obtained in various formats of the bibliography, except in the cases where the source is indicated.

A COMUNICAÇÃO ORGANIZACIONAL INTERNA E O AMBIENTE VIRTUAL: NOVAS TENDÊNCIAS

Esta tese trata do impacto nas Comunicações Internas das Organizações em relação à virtualidade e teve como objetivo descrever e analisar as mudanças ocorridas na comunicação interna das organizações privadas com o advento das tecnologias. Para atingir nosso objetivo fizemos uso da pesquisa bibliográfica, partindo do exame das teorias comunicacionais disponíveis e dos recursos técnicos inerentes à comunicação e às tecnologias da informação aplicadas à organização. Estabelecemos a convergência em relação às tendências e efeitos que poderão ser observados, por meio de um diálogo com especialistas da área Comunicacional através de um estudo qualitativo, onde fizemos uso da metodologia do Painel Delphi com o intuito de descrevermos e analisarmos as mudanças ocorridas nos meios, analisarmos seus impactos e traçarmos um cenário futuro em relação à utilização das tecnologias da informação e comunicação no ambiente organizacional interno. Os resultados de nossa pesquisa demonstraram que a comunicação interna organizacional deverá ser intensamente mediada por computador, mas não se limitará a ele, justamente pela realidade e condição cultural de cada organização, um mix comunicacional (com veículos tradicionais e virtuais) deverá ser a condição mais lógica para uma comunicação eficiente, uma vez que abrange todo o tipo de público e formato de mensagens.

A COMUNICAÇÃO ORGANIZACIONAL INTERNA E O AMBIENTE VIRTUAL: NOVAS TENDÊNCIAS

Esta tese trata do impacto nas Comunicações Internas das Organizações em relação à virtualidade e teve como objetivo descrever e analisar as mudanças ocorridas na comunicação interna das organizações privadas com o advento das tecnologias. Para atingir nosso objetivo fizemos uso da pesquisa bibliográfica, partindo do exame das teorias comunicacionais disponíveis e dos recursos técnicos inerentes à comunicação e às tecnologias da informação aplicadas à organização. Estabelecemos a convergência em relação às tendências e efeitos que poderão ser observados, por meio de um diálogo com especialistas da área Comunicacional através de um estudo qualitativo, onde fizemos uso da metodologia do Painel Delphi com o intuito de descrevermos e analisarmos as mudanças ocorridas nos meios, analisarmos seus impactos e traçarmos um cenário futuro em relação à utilização das tecnologias da informação e comunicação no ambiente organizacional interno. Os resultados de nossa pesquisa demonstraram que a comunicação interna organizacional deverá ser intensamente mediada por computador, mas não se limitará a ele, justamente pela realidade e condição cultural de cada organização, um mix comunicacional (com veículos tradicionais e virtuais) deverá ser a condição mais lógica para uma comunicação eficiente, uma vez que abrange todo o tipo de público e formato de mensagens.

Material matters for learning in virtual networks : A case study of a professional learning programme hosted in a Google+ online community

Date of Acceptance: 13/07/2015

AHEC library services: from circuit rider to virtual librarian

The North Carolina Area Health Education Centers Library and Information Services (NC AHEC LIS) Network provides library outreach services to rural health care providers in all nine AHEC regions of North Carolina. Over the last twenty-five years, the AHEC and university-based librarians have collaborated to create a model program for support of community-based clinical education and information access for rural health care providers. Through several collaborative projects, they have supported Internet access for rural health clinics. The NC AHEC Digital Library—under development by NC AHEC, University of North Carolina at Chapel Hill, Duke University, East Carolina University, and Wake Forest University—will further extend access to electronic biomedical information and resources to health professionals in a statewide digital library.

Open educational resources: the role of OCW, blogs and videos in computer network classrooms

This paper analyzes the learning experiences and opinions obtained from a group of undergraduate students in their interaction with several on-line multimedia resources included in a free on-line course about Computer Networks. These new educational resources employed are based on the Web 2.0 approach such as blogs, videos and virtual labs which have been added in a web-site for distance self-learning.

On Modeling an Innovative Monitoring Network for Protecting and Managing Cultural Heritage from Risk Events

In this paper the model of an Innovative Monitoring Network involving properly connected nodes to develop an Information and Communication Technology (ICT) solution for preventive maintenance of historical centres from early warnings is proposed. It is well known that the protection of historical centres generally goes from a large-scale monitoring to a local one and it could be supported by a unique ICT solution. More in detail, the models of a virtually organized monitoring system could enable the implementation of automated analyses by presenting various alert levels. An adequate ICT solution tool would allow to define a monitoring network for a shared processing of data and results. Thus, a possible retrofit solution could be planned for pilot cases shared among the nodes of the network on the basis of a suitable procedure utilizing a retrofit catalogue. The final objective would consist in providing a model of an innovative tool to identify hazards, damages and possible retrofit solutions for historical centres, assuring an easy early warning support for stakeholders. The action could proactively target the needs and requirements of users, such as decision makers responsible for damage mitigation and safeguarding of cultural heritage assets.