Providing 30Mbit/s to Spain’s final third. -A techno-economic assessment.

Since the Digital Agenda for Europe released the Europe2020 flagship, Member States are looking for ways of fulfilling their agreed commitments to fast and ultrafast internet deployment. However, Europe is not a homogenous reality. The economic, geographic, social and demographic features of each country make it a highly diverse region to develop best practices over Next Generation Access Networks (NGAN) deployments. There are special concerns about NGAN deployments for “the final third”, as referred to the last 25% of the country’s population who, usually, live in rural areas. This paper assesses, through a techno-economic analysis, the access cost of providing over 30 Mbps broadband for the final third of Spain`s population in municipalities, which are classified into area types, referred to as geotypes. Fixed and mobile technologies are compared in order to determine which is the most cost-effective technology for each geotype. The demographic limit for fixed networks (cable, fibre and copper) is also discussed. The assessment focuses on the supply side and the results show the access network cost only. The research completes a previous published assessment (Techno-economic analysis of next generation access networks roll-out. The case of platform competition, regulation and public policy in Spain) by including the LTE scenario. The LTE scenario is dimensioned to provide 30 Mbps (best effort) broadband, considering a network take-up of 25%. The Rocket techno-economic model is used to assess a ten-year study period deployment. Nevertheless, the deployment must start in 2014 and be completed by 2020, in order to fulfil the Digital Agenda’s goals. The feasibility of the deployment is defined as the ability to recoup the investment at the end of the study period. This ability is highly related to network take-up and, therefore, to service adoption. Network deployment in each geotype is compared with the cost of the deployment in the Urban geotype and broadband expected penetration rates for clarity and simplicity. Debating the cost-effective deployments for each geotype, while addressing the Digital Agenda’s goals regarding fast and ultrafast internet, is the main purpose of this paper. At the end of the last year, the independent Spanish regulation agency released the Spain broadband coverage report at the first half of 2013. This document claimed that 59% and 52% of Spain’s population was already covered by NGAN capable of providing 30 Mbps and 100 Mbps broadband respectively. HFC, with 47% of population coverage, and FTTH, with 14%, were considered as a 100 Mbps capable NGAN. Meanwhile VDSL, with 12% of the population covered, was the only NGAN network considered for the 30 Mbps segment. Despite not being an NGAN, the 99% population coverage of HSPA networks was also noted in the report. Since mobile operators are also required to provide 30 Mbps broadband to 90% of the population in rural areas by the end of 2020, mobile networks will play a significant role on the achievement of the 30 Mbps goal in Spain’s final third. The assessment indicates the cost of the deployment per cumulative households coverage with 4 different NGANs: FTTH, HFC, VDSL and LTE. Research shows that an investment ranging from €2,700 (VDSL) to €5,400 (HFC) million will be needed to cover the first half of the population with any fixed technology assessed. The results state that at least €3,000 million will be required to cover these areas with the least expensive technology (LTE). However, if we consider the throughput that fixed networks could provide and achievement of the Digital Agenda’s objectives, fixed network deployments are recommended for up to 90% of the population. Fibre and cable deployments could cover up to a maximum of 88% of the Spanish population cost efficiently. As there are some concerns about the service adoption, we recommend VDSL and mobile network deployments for the final third of the population. Despite LTE being able to provide the most economical roll-out, VDSL could also provide 50 Mbps from 75% to 90% of the Spanish population cost efficiently. For this population gap, facility based competition between VDSL providers and LTE providers must be encouraged. Regarding 90% to 98.5% of the Spanish population, LTE deployment is the most appropriate. Since costumers in less populated the municipalities are more sensitive to the cost of the service, we consider that a single network deployment could be most appropriate. Finally, it has become clear that it is not possible to deliver 30Mbps to the final 1.5% of the population cost-efficiently and adoption predictions are not optimistic either. As there are other broadband alternatives able to deliver up to 20 Mbps, in the authors’ opinion, it is not necessary to cover the extreme rural areas, where public financing would be required.

Comparative Analysis of Tolerances Allocation in Mechanical Assemblies based on Cost-tolerance Curves

El presente trabajo propone un método para la determinación de los valores de las tolerancias individuales de las piezas que forman un conjunto ensamblado a partir de valores de tolerancias especificados en el conjunto final, optimizando el coste total de fabricación de las piezas individuales a partir de funciones de coste-tolerancia basadas en el proceso de fabricación de cada una de ellas. Para ello se parte de los principales trabajos desarrollados en la línea de asignación de tolerancias y se realiza la propuesta del modelo de trabajo, basado en la optimización de costes a partir de la aplicación del método de los multiplicadores de Lagrange a diversas curvas de coste-tolerancia

A cost-effective methodology applied to videoconference services over hybrid clouds

This paper tackles the optimization of applications in multi-provider hybrid cloud scenarios from an economic point of view. In these scenarios the great majority of solutions offer the automatic allocation of resources on different cloud providers based on their current prices. However our approach is intended to introduce a novel solution by making maximum use of divide and rule. This paper describes a methodology to create cost aware cloud applications that can be broken down into the three most important components in cloud infrastructures: computation, network and storage. A real videoconference system has been modified in order to evaluate this idea with both theoretical and empirical experiments. This system has become a widely used tool in several national and European projects for e-learning and collaboration purposes.

SCA security verification on wireless sensor network node

Side Channel Attack (SCA) differs from traditional mathematic attacks. It gets around of the exhaustive mathematic calculation and precisely pin to certain points in the cryptographic algorithm to reveal confidential information from the running crypto-devices. Since the introduction of SCA by Paul Kocher et al [1], it has been considered to be one of the most critical threats to the resource restricted but security demanding applications, such as wireless sensor networks. In this paper, we focus our work on the SCA-concerned security verification on WSN (wireless sensor network). A detailed setup of the platform and an analysis of the results of DPA (power attack) and EMA (electromagnetic attack) is presented. The setup follows the way of low-cost setup to make effective SCAs. Meanwhile, surveying the weaknesses of WSNs in resisting SCA attacks, especially for the EM attack. Finally, SCA-Prevention suggestions based on Differential Security Strategy for the FPGA hardware implementation in WSN will be given, helping to get an improved compromise between security and cost.

Power system stability of a small sized isolated network supplied by a combined wind-pumped storage generation system: a case study in the Canary Islands

Massive integration of renewable energy sources in electrical power systems of remote islands is a subject of current interest. The increasing cost of fossil fuels, transport costs to isolated sites and environmental concerns constitute a serious drawback to the use of conventional fossil fuel plants. In a weak electrical grid, as it is typical on an island, if a large amount of conventional generation is substituted by renewable energy sources, power system safety and stability can be compromised, in the case of large grid disturbances. In this work, a model for transient stability analysis of an isolated electrical grid exclusively fed from a combination of renewable energy sources has been studied. This new generation model will be installed in El Hierro Island, in Spain. Additionally, an operation strategy to coordinate the generation units (wind, hydro) is also established. Attention is given to the assessment of inertial energy and reactive current to guarantee power system stability against large disturbances. The effectiveness of the proposed strategy is shown by means of simulation results.

Performance assessment of a kinetically-powered network for herd localization

Developing a herd localization system capable to operate unattended in communication-challenged areas arises from the necessity of improving current systems in terms of cost, autonomy or any other facilities that a certain target group (or overall users) may demand. A network architecture of herd localization is proposed with its corresponding hardware and a methodology to assess performance in different operating conditions. The system is designed taking into account an eventual environmental impact hence most nodes are simple, cheap and kinetically powered from animal movements-neither batteries nor sophisticated processor chips are needed. Other network elements integrating GPS and batteries operate with selectable duty cycles, thus reducing maintenance duties. Equipment has been tested on Scandinavian reindeer in Lapland and its element modeling is integrated into a simulator to analyze such localization network applicability for different use cases. Performance indicators (detection frequency, localization accuracy and delay) are fitted to assess the overall performance; system relative costs are enclosed also for a range of deployments.

Feature selection in the reconstruction of complex network representations of spectral data

Complex networks have been extensively used in the last decade to characterize and analyze complex systems, and they have been recently proposed as a novel instrument for the analysis of spectra extracted from biological samples. Yet, the high number of measurements composing spectra, and the consequent high computational cost, make a direct network analysis unfeasible. We here present a comparative analysis of three customary feature selection algorithms, including the binning of spectral data and the use of information theory metrics. Such algorithms are compared by assessing the score obtained in a classification task, where healthy subjects and people suffering from different types of cancers should be discriminated. Results indicate that a feature selection strategy based on Mutual Information outperforms the more classical data binning, while allowing a reduction of the dimensionality of the data set in two orders of magnitude

The Phase Space as a New Representation of the Dynamical Behaviour of Temperature and Enthalpy in a Reefer monitored with a Multidistributed Sensors Network

The study of temperature gradients in cold stores and containers is a critical issue in the food industry for the quality assurance of products during transport, as well as forminimizing losses. The objective of this work is to develop a new methodology of data analysis based on phase space graphs of temperature and enthalpy, collected by means of multidistributed, low cost and autonomous wireless sensors and loggers. A transoceanic refrigerated transport of lemons in a reefer container ship from Montevideo (Uruguay) to Cartagena (Spain) was monitored with a network of 39 semi-passive TurboTag RFID loggers and 13 i-button loggers. Transport included intermodal transit from transoceanic to short shipping vessels and a truck trip. Data analysis is carried out using qualitative phase diagrams computed on the basis of Takens?Ruelle reconstruction of attractors. Fruit stress is quantified in terms of the phase diagram area which characterizes the cyclic behaviour of temperature. Areas within the enthalpy phase diagram computed for the short sea shipping transport were 5 times higher than those computed for the long sea shipping, with coefficients of variation above 100% for both periods. This new methodology for data analysis highlights the significant heterogeneity of thermohygrometric conditions at different locations in the container.

Evaluating alternative industrial network organizations and information systems

Purpose – The purpose of this paper is to present a simulation‐based evaluation method for the comparison of different organizational forms and software support levels in the field of supply chain management (SCM). Design/methodology/approach – Apart from widely known logistic performance indicators, the discrete event simulation model considers explicitly coordination cost as stemming from iterative administration procedures. Findings - The method is applied to an exemplary supply chain configuration considering various parameter settings. Curiously, additional coordination cost does not always result in improved logistic performance. Influence factor variations lead to different organizational recommendations. The results confirm the high importance of (up to now) disregarded dimensions when evaluating SCM concepts and IT tools. Research limitations/implications – The model is based on simplified product and network structures. Future research shall include more complex, real world configurations. Practical implications – The developed method is designed for the identification of improvement potential when SCM software is employed. Coordination schemes based only on ERP systems are valid alternatives in industrial practice because significant investment IT can be avoided. Therefore, the evaluation of these coordination procedures, in particular the cost due to iterations, is of high managerial interest and the method provides a comprehensive tool for strategic IT decision making. Originality/value – Reviewed literature is mostly focused on the benefits of SCM software implementations. However, ERP system based supply chain coordination is still widespread industrial practice but associated coordination cost has not been addressed by researchers.

Wireless Sensor Network Solution for Sustainable Food Production

Environmental monitoring has become a key aspect in food production over the last few years. Due to their low cost, low power consumption and flexibility, Wireless Sensor Networks (WSNs) have turned up as a very convenient tool to be used in these environments where no intrusion is a must. In this work, a WSN application in a food factory is presented. The paper gives an overview of the system set up, covering from the initial study of the parameters and sensors, to the hardware-software design and development needed for the final tests in the factory facilities.

Proposal for a Wavelength Multiplexed Quantum Metropolitan Area Network

Quantum Key Distribution (QKD) is maturing quickly. However, the current approaches to its network use require conditions that make it an expensive technology. All the QKD networks deployed to date are designed as a collection of dedicated point-to-point links that use the trusted repeater paradigm. Instead, we propose a novel network model in which QKD systems use simultaneously quantum and conventional signals that are wavelength multiplexed over a common communication infrastructure. Signals are transmitted end-to-end within a metropolitan area using optical components. The model resembles a commercial telecom network and takes advantage of existing components, thus allowing for a cost-effective and reliable deployment.

Quantum metropolitan optical network based on wavelength division multiplexing

Quantum Key Distribution (QKD) is maturing quickly. However, the current approaches to its application in optical networks make it an expensive technology. QKD networks deployed to date are designed as a collection of point-to-point, dedicated QKD links where non-neighboring nodes communicate using the trusted repeater paradigm. We propose a novel optical network model in which QKD systems share the communication infrastructure by wavelength multiplexing their quantum and classical signals. The routing is done using optical components within a metropolitan area which allows for a dynamically any-to-any communication scheme. Moreover, it resembles a commercial telecom network, takes advantage of existing infrastructure and utilizes commercial components, allowing for an easy, cost-effective and reliable deployment.

Self-organizing cultured neural networks: Image analysis techniques for longitudinal tracking and modeling of the underlying network structure

Esta tesis estudia la evolución estructural de conjuntos de neuronas como la capacidad de auto-organización desde conjuntos de neuronas separadas hasta que forman una red (clusterizada) compleja. Esta tesis contribuye con el diseño e implementación de un algoritmo no supervisado de segmentación basado en grafos con un coste computacional muy bajo. Este algoritmo proporciona de forma automática la estructura completa de la red a partir de imágenes de cultivos neuronales tomadas con microscopios de fase con una resolución muy alta. La estructura de la red es representada mediante un objeto matemático (matriz) cuyos nodos representan a las neuronas o grupos de neuronas y los enlaces son las conexiones reconstruidas entre ellos. Este algoritmo extrae también otras medidas morfológicas importantes que caracterizan a las neuronas y a las neuritas. A diferencia de otros algoritmos hasta el momento, que necesitan de fluorescencia y técnicas inmunocitoquímicas, el algoritmo propuesto permite el estudio longitudinal de forma no invasiva posibilitando el estudio durante la formación de un cultivo. Además, esta tesis, estudia de forma sistemática un grupo de variables topológicas que garantizan la posibilidad de cuantificar e investigar la progresión de las características principales durante el proceso de auto-organización del cultivo. Nuestros resultados muestran la existencia de un estado concreto correspondiente a redes con configuracin small-world y la emergencia de propiedades a micro- y meso-escala de la estructura de la red. Finalmente, identificamos los procesos físicos principales que guían las transformaciones morfológicas de los cultivos y proponemos un modelo de crecimiento de red que reproduce el comportamiento cuantitativamente de las observaciones experimentales. ABSTRACT The thesis analyzes the morphological evolution of assemblies of living neurons, as they self-organize from collections of separated cells into elaborated, clustered, networks. In particular, it contributes with the design and implementation of a graph-based unsupervised segmentation algorithm, having an associated very low computational cost. The processing automatically retrieves the whole network structure from large scale phase-contrast images taken at high resolution throughout the entire life of a cultured neuronal network. The network structure is represented by a mathematical object (a matrix) in which nodes are identified neurons or neurons clusters, and links are the reconstructed connections between them. The algorithm is also able to extract any other relevant morphological information characterizing neurons and neurites. More importantly, and at variance with other segmentation methods that require fluorescence imaging from immunocyto- chemistry techniques, our measures are non invasive and entitle us to carry out a fully longitudinal analysis during the maturation of a single culture. In turn, a systematic statistical analysis of a group of topological observables grants us the possibility of quantifying and tracking the progression of the main networks characteristics during the self-organization process of the culture. Our results point to the existence of a particular state corresponding to a small-world network configuration, in which several relevant graphs micro- and meso-scale properties emerge. Finally, we identify the main physical processes taking place during the cultures morphological transformations, and embed them into a simplified growth model that quantitatively reproduces the overall set of experimental observations.

Self-organizing cultured neural networks: Image analysis techniques for longitudinal tracking and modeling of the underlying network structure (versión actualizada)

Esta tesis estudia la evolución estructural de conjuntos de neuronas como la capacidad de auto-organización desde conjuntos de neuronas separadas hasta que forman una red (clusterizada) compleja. Esta tesis contribuye con el diseño e implementación de un algoritmo no supervisado de segmentación basado en grafos con un coste computacional muy bajo. Este algoritmo proporciona de forma automática la estructura completa de la red a partir de imágenes de cultivos neuronales tomadas con microscopios de fase con una resolución muy alta. La estructura de la red es representada mediante un objeto matemático (matriz) cuyos nodos representan a las neuronas o grupos de neuronas y los enlaces son las conexiones reconstruidas entre ellos. Este algoritmo extrae también otras medidas morfológicas importantes que caracterizan a las neuronas y a las neuritas. A diferencia de otros algoritmos hasta el momento, que necesitan de fluorescencia y técnicas inmunocitoquímicas, el algoritmo propuesto permite el estudio longitudinal de forma no invasiva posibilitando el estudio durante la formación de un cultivo. Además, esta tesis, estudia de forma sistemática un grupo de variables topológicas que garantizan la posibilidad de cuantificar e investigar la progresión de las características principales durante el proceso de auto-organización del cultivo. Nuestros resultados muestran la existencia de un estado concreto correspondiente a redes con configuracin small-world y la emergencia de propiedades a micro- y meso-escala de la estructura de la red. Finalmente, identificamos los procesos físicos principales que guían las transformaciones morfológicas de los cultivos y proponemos un modelo de crecimiento de red que reproduce el comportamiento cuantitativamente de las observaciones experimentales. ABSTRACT The thesis analyzes the morphological evolution of assemblies of living neurons, as they self-organize from collections of separated cells into elaborated, clustered, networks. In particular, it contributes with the design and implementation of a graph-based unsupervised segmentation algorithm, having an associated very low computational cost. The processing automatically retrieves the whole network structure from large scale phase-contrast images taken at high resolution throughout the entire life of a cultured neuronal network. The network structure is represented by a mathematical object (a matrix) in which nodes are identified neurons or neurons clusters, and links are the reconstructed connections between them. The algorithm is also able to extract any other relevant morphological information characterizing neurons and neurites. More importantly, and at variance with other segmentation methods that require fluorescence imaging from immunocyto- chemistry techniques, our measures are non invasive and entitle us to carry out a fully longitudinal analysis during the maturation of a single culture. In turn, a systematic statistical analysis of a group of topological observables grants us the possibility of quantifying and tracking the progression of the main networks characteristics during the self-organization process of the culture. Our results point to the existence of a particular state corresponding to a small-world network configuration, in which several relevant graphs micro- and meso-scale properties emerge. Finally, we identify the main physical processes taking place during the cultures morphological transformations, and embed them into a simplified growth model that quantitatively reproduces the overall set of experimental observations.

Predicting EQ-5D from the Parkinson's disease questionnaire PDQ-8 using multi-dimensional Bayesian network classifiers

The impact of the Parkinson's disease and its treatment on the patients' health-related quality of life can be estimated either by means of generic measures such as the european quality of Life-5 Dimensions (EQ-5D) or specific measures such as the 8-item Parkinson's disease questionnaire (PDQ-8). In clinical studies, PDQ-8 could be used in detriment of EQ-5D due to the lack of resources, time or clinical interest in generic measures. Nevertheless, PDQ-8 cannot be applied in cost-effectiveness analyses which require generic measures and quantitative utility scores, such as EQ-5D. To deal with this problem, a commonly used solution is the prediction of EQ-5D from PDQ-8. In this paper, we propose a new probabilistic method to predict EQ-5D from PDQ-8 using multi-dimensional Bayesian network classifiers. Our approach is evaluated using five-fold cross-validation experiments carried out on a Parkinson's data set containing 488 patients, and is compared with two additional Bayesian network-based approaches, two commonly used mapping methods namely, ordinary least squares and censored least absolute deviations, and a deterministic model. Experimental results are promising in terms of predictive performance as well as the identification of dependence relationships among EQ-5D and PDQ-8 items that the mapping approaches are unable to detect