A taxonomy of the quality attributes for distributed applications

The software engineering community has paid little attention to non-functional requirements, or quality attributes, compared with studies performed on capture, analysis and validation of functional requirements. This circumstance becomes more intense in the case of distributed applications. In these applications we have to take into account, besides the quality attributes such as correctness, robustness, extendibility, reusability, compatibility, efficiency, portability and ease of use, others like reliability, scalability, transparency, security, interoperability, concurrency, etc. In this work we will show how these last attributes are related to different abstractions that coexist in the problem domain. To achieve this goal, we have established a taxonomy of quality attributes of distributed applications and have determined the set of necessary services to support such attributes.

A swarm intelligence approach based on coupled oscillators: an application in demand side management with photovoltaic distributed generation

Esta Tesis aborda los problemas de eficiencia de las redes eléctrica desde el punto de vista del consumo. En particular, dicha eficiencia es mejorada mediante el suavizado de la curva de consumo agregado. Este objetivo de suavizado de consumo implica dos grandes mejoras en el uso de las redes eléctricas: i) a corto plazo, un mejor uso de la infraestructura existente y ii) a largo plazo, la reducción de la infraestructura necesaria para suplir las mismas necesidades energéticas. Además, esta Tesis se enfrenta a un nuevo paradigma energético, donde la presencia de generación distribuida está muy extendida en las redes eléctricas, en particular, la generación fotovoltaica (FV). Este tipo de fuente energética afecta al funcionamiento de la red, incrementando su variabilidad. Esto implica que altas tasas de penetración de electricidad de origen fotovoltaico es perjudicial para la estabilidad de la red eléctrica. Esta Tesis trata de suavizar la curva de consumo agregado considerando esta fuente energética. Por lo tanto, no sólo se mejora la eficiencia de la red eléctrica, sino que también puede ser aumentada la penetración de electricidad de origen fotovoltaico en la red. Esta propuesta conlleva grandes beneficios en los campos económicos, social y ambiental. Las acciones que influyen en el modo en que los consumidores hacen uso de la electricidad con el objetivo producir un ahorro energético o un aumento de eficiencia son llamadas Gestión de la Demanda Eléctrica (GDE). Esta Tesis propone dos algoritmos de GDE diferentes para cumplir con el objetivo de suavizado de la curva de consumo agregado. La diferencia entre ambos algoritmos de GDE reside en el marco en el cual estos tienen lugar: el marco local y el marco de red. Dependiendo de este marco de GDE, el objetivo energético y la forma en la que se alcanza este objetivo son diferentes. En el marco local, el algoritmo de GDE sólo usa información local. Este no tiene en cuenta a otros consumidores o a la curva de consumo agregado de la red eléctrica. Aunque esta afirmación pueda diferir de la definición general de GDE, esta vuelve a tomar sentido en instalaciones locales equipadas con Recursos Energéticos Distribuidos (REDs). En este caso, la GDE está enfocada en la maximización del uso de la energía local, reduciéndose la dependencia con la red. El algoritmo de GDE propuesto mejora significativamente el auto-consumo del generador FV local. Experimentos simulados y reales muestran que el auto-consumo es una importante estrategia de gestión energética, reduciendo el transporte de electricidad y alentando al usuario a controlar su comportamiento energético. Sin embargo, a pesar de todas las ventajas del aumento de auto-consumo, éstas no contribuyen al suavizado del consumo agregado. Se han estudiado los efectos de las instalaciones locales en la red eléctrica cuando el algoritmo de GDE está enfocado en el aumento del auto-consumo. Este enfoque puede tener efectos no deseados, incrementando la variabilidad en el consumo agregado en vez de reducirlo. Este efecto se produce porque el algoritmo de GDE sólo considera variables locales en el marco local. Los resultados sugieren que se requiere una coordinación entre las instalaciones. A través de esta coordinación, el consumo debe ser modificado teniendo en cuenta otros elementos de la red y buscando el suavizado del consumo agregado. En el marco de la red, el algoritmo de GDE tiene en cuenta tanto información local como de la red eléctrica. En esta Tesis se ha desarrollado un algoritmo autoorganizado para controlar el consumo de la red eléctrica de manera distribuida. El objetivo de este algoritmo es el suavizado del consumo agregado, como en las implementaciones clásicas de GDE. El enfoque distribuido significa que la GDE se realiza desde el lado de los consumidores sin seguir órdenes directas emitidas por una entidad central. Por lo tanto, esta Tesis propone una estructura de gestión paralela en lugar de una jerárquica como en las redes eléctricas clásicas. Esto implica que se requiere un mecanismo de coordinación entre instalaciones. Esta Tesis pretende minimizar la cantidad de información necesaria para esta coordinación. Para lograr este objetivo, se han utilizado dos técnicas de coordinación colectiva: osciladores acoplados e inteligencia de enjambre. La combinación de estas técnicas para llevar a cabo la coordinación de un sistema con las características de la red eléctrica es en sí mismo un enfoque novedoso. Por lo tanto, este objetivo de coordinación no es sólo una contribución en el campo de la gestión energética, sino también en el campo de los sistemas colectivos. Los resultados muestran que el algoritmo de GDE propuesto reduce la diferencia entre máximos y mínimos de la red eléctrica en proporción a la cantidad de energía controlada por el algoritmo. Por lo tanto, conforme mayor es la cantidad de energía controlada por el algoritmo, mayor es la mejora de eficiencia en la red eléctrica. Además de las ventajas resultantes del suavizado del consumo agregado, otras ventajas surgen de la solución distribuida seguida en esta Tesis. Estas ventajas se resumen en las siguientes características del algoritmo de GDE propuesto: • Robustez: en un sistema centralizado, un fallo o rotura del nodo central provoca un mal funcionamiento de todo el sistema. La gestión de una red desde un punto de vista distribuido implica que no existe un nodo de control central. Un fallo en cualquier instalación no afecta el funcionamiento global de la red. • Privacidad de datos: el uso de una topología distribuida causa de que no hay un nodo central con información sensible de todos los consumidores. Esta Tesis va más allá y el algoritmo propuesto de GDE no utiliza información específica acerca de los comportamientos de los consumidores, siendo la coordinación entre las instalaciones completamente anónimos. • Escalabilidad: el algoritmo propuesto de GDE opera con cualquier número de instalaciones. Esto implica que se permite la incorporación de nuevas instalaciones sin afectar a su funcionamiento. • Bajo coste: el algoritmo de GDE propuesto se adapta a las redes actuales sin requisitos topológicos. Además, todas las instalaciones calculan su propia gestión con un bajo requerimiento computacional. Por lo tanto, no se requiere un nodo central con un alto poder de cómputo. • Rápido despliegue: las características de escalabilidad y bajo coste de los algoritmos de GDE propuestos permiten una implementación rápida. No se requiere una planificación compleja para el despliegue de este sistema. ABSTRACT This Thesis addresses the efficiency problems of the electrical grids from the consumption point of view. In particular, such efficiency is improved by means of the aggregated consumption smoothing. This objective of consumption smoothing entails two major improvements in the use of electrical grids: i) in the short term, a better use of the existing infrastructure and ii) in long term, the reduction of the required infrastructure to supply the same energy needs. In addition, this Thesis faces a new energy paradigm, where the presence of distributed generation is widespread over the electrical grids, in particular, the Photovoltaic (PV) generation. This kind of energy source affects to the operation of the grid by increasing its variability. This implies that a high penetration rate of photovoltaic electricity is pernicious for the electrical grid stability. This Thesis seeks to smooth the aggregated consumption considering this energy source. Therefore, not only the efficiency of the electrical grid is improved, but also the penetration of photovoltaic electricity into the grid can be increased. This proposal brings great benefits in the economic, social and environmental fields. The actions that influence the way that consumers use electricity in order to achieve energy savings or higher efficiency in energy use are called Demand-Side Management (DSM). This Thesis proposes two different DSM algorithms to meet the aggregated consumption smoothing objective. The difference between both DSM algorithms lie in the framework in which they take place: the local framework and the grid framework. Depending on the DSM framework, the energy goal and the procedure to reach this goal are different. In the local framework, the DSM algorithm only uses local information. It does not take into account other consumers or the aggregated consumption of the electrical grid. Although this statement may differ from the general definition of DSM, it makes sense in local facilities equipped with Distributed Energy Resources (DERs). In this case, the DSM is focused on the maximization of the local energy use, reducing the grid dependence. The proposed DSM algorithm significantly improves the self-consumption of the local PV generator. Simulated and real experiments show that self-consumption serves as an important energy management strategy, reducing the electricity transport and encouraging the user to control his energy behavior. However, despite all the advantages of the self-consumption increase, they do not contribute to the smooth of the aggregated consumption. The effects of the local facilities on the electrical grid are studied when the DSM algorithm is focused on self-consumption maximization. This approach may have undesirable effects, increasing the variability in the aggregated consumption instead of reducing it. This effect occurs because the algorithm only considers local variables in the local framework. The results suggest that coordination between these facilities is required. Through this coordination, the consumption should be modified by taking into account other elements of the grid and seeking for an aggregated consumption smoothing. In the grid framework, the DSM algorithm takes into account both local and grid information. This Thesis develops a self-organized algorithm to manage the consumption of an electrical grid in a distributed way. The goal of this algorithm is the aggregated consumption smoothing, as the classical DSM implementations. The distributed approach means that the DSM is performed from the consumers side without following direct commands issued by a central entity. Therefore, this Thesis proposes a parallel management structure rather than a hierarchical one as in the classical electrical grids. This implies that a coordination mechanism between facilities is required. This Thesis seeks for minimizing the amount of information necessary for this coordination. To achieve this objective, two collective coordination techniques have been used: coupled oscillators and swarm intelligence. The combination of these techniques to perform the coordination of a system with the characteristics of the electric grid is itself a novel approach. Therefore, this coordination objective is not only a contribution in the energy management field, but in the collective systems too. Results show that the proposed DSM algorithm reduces the difference between the maximums and minimums of the electrical grid proportionally to the amount of energy controlled by the system. Thus, the greater the amount of energy controlled by the algorithm, the greater the improvement of the efficiency of the electrical grid. In addition to the advantages resulting from the smoothing of the aggregated consumption, other advantages arise from the distributed approach followed in this Thesis. These advantages are summarized in the following features of the proposed DSM algorithm: • Robustness: in a centralized system, a failure or breakage of the central node causes a malfunction of the whole system. The management of a grid from a distributed point of view implies that there is not a central control node. A failure in any facility does not affect the overall operation of the grid. • Data privacy: the use of a distributed topology causes that there is not a central node with sensitive information of all consumers. This Thesis goes a step further and the proposed DSM algorithm does not use specific information about the consumer behaviors, being the coordination between facilities completely anonymous. • Scalability: the proposed DSM algorithm operates with any number of facilities. This implies that it allows the incorporation of new facilities without affecting its operation. • Low cost: the proposed DSM algorithm adapts to the current grids without any topological requirements. In addition, every facility calculates its own management with low computational requirements. Thus, a central computational node with a high computational power is not required. • Quick deployment: the scalability and low cost features of the proposed DSM algorithms allow a quick deployment. A complex schedule of the deployment of this system is not required.

Cooperative Multi-robot Patrolling: A study of distributed approaches based on mathematical models of game theory to protect infrastructures

El principio de Teoría de Juegos permite desarrollar modelos estocásticos de patrullaje multi-robot para proteger infraestructuras criticas. La protección de infraestructuras criticas representa un gran reto para los países al rededor del mundo, principalmente después de los ataques terroristas llevados a cabo la década pasada. En este documento el termino infraestructura hace referencia a aeropuertos, plantas nucleares u otros instalaciones. El problema de patrullaje se define como la actividad de patrullar un entorno determinado para monitorear cualquier actividad o sensar algunas variables ambientales. En esta actividad, un grupo de robots debe visitar un conjunto de puntos de interés definidos en un entorno en intervalos de tiempo irregulares con propósitos de seguridad. Los modelos de partullaje multi-robot son utilizados para resolver este problema. Hasta el momento existen trabajos que resuelven este problema utilizando diversos principios matemáticos. Los modelos de patrullaje multi-robot desarrollados en esos trabajos representan un gran avance en este campo de investigación. Sin embargo, los modelos con los mejores resultados no son viables para aplicaciones de seguridad debido a su naturaleza centralizada y determinista. Esta tesis presenta cinco modelos de patrullaje multi-robot distribuidos e impredecibles basados en modelos matemáticos de aprendizaje de Teoría de Juegos. El objetivo del desarrollo de estos modelos está en resolver los inconvenientes presentes en trabajos preliminares. Con esta finalidad, el problema de patrullaje multi-robot se formuló utilizando conceptos de Teoría de Grafos, en la cual se definieron varios juegos en cada vértice de un grafo. Los modelos de patrullaje multi-robot desarrollados en este trabajo de investigación se han validado y comparado con los mejores modelos disponibles en la literatura. Para llevar a cabo tanto la validación como la comparación se ha utilizado un simulador de patrullaje y un grupo de robots reales. Los resultados experimentales muestran que los modelos de patrullaje desarrollados en este trabajo de investigación trabajan mejor que modelos de trabajos previos en el 80% de 150 casos de estudio. Además de esto, estos modelos cuentan con varias características importantes tales como distribución, robustez, escalabilidad y dinamismo. Los avances logrados con este trabajo de investigación dan evidencia del potencial de Teoría de Juegos para desarrollar modelos de patrullaje útiles para proteger infraestructuras. ABSTRACT Game theory principle allows to developing stochastic multi-robot patrolling models to protect critical infrastructures. Critical infrastructures protection is a great concern for countries around the world, mainly due to terrorist attacks in the last decade. In this document, the term infrastructures includes airports, nuclear power plants, and many other facilities. The patrolling problem is defined as the activity of traversing a given environment to monitoring any activity or sensing some environmental variables If this activity were performed by a fleet of robots, they would have to visit some places of interest of an environment at irregular intervals of time for security purposes. This problem is solved using multi-robot patrolling models. To date, literature works have been solved this problem applying various mathematical principles.The multi-robot patrolling models developed in those works represent great advances in this field. However, the models that obtain the best results are unfeasible for security applications due to their centralized and predictable nature. This thesis presents five distributed and unpredictable multi-robot patrolling models based on mathematical learning models derived from Game Theory. These multi-robot patrolling models aim at overcoming the disadvantages of previous work. To this end, the multi-robot patrolling problem was formulated using concepts of Graph Theory to represent the environment. Several normal-form games were defined at each vertex of a graph in this formulation. The multi-robot patrolling models developed in this research work have been validated and compared with best ranked multi-robot patrolling models in the literature. Both validation and comparison were preformed by using both a patrolling simulator and real robots. Experimental results show that the multirobot patrolling models developed in this research work improve previous ones in as many as 80% of 150 cases of study. Moreover, these multi-robot patrolling models rely on several features to highlight in security applications such as distribution, robustness, scalability, and dynamism. The achievements obtained in this research work validate the potential of Game Theory to develop patrolling models to protect infrastructures.

Distributed control strategies for photovoltaic systems in urban environments : Versión definitiva

Este trabajo es una contribución a los sistemas fotovoltaicos (FV) con seguimiento distribuido del punto de máxima potencia (DMPPT), una topología que se caracteriza porque lleva a cabo el MPPT a nivel de módulo, al contrario de las topologías más tradicionales que llevan a cabo el MPPT para un número más elevado de módulos, pudiendo ser hasta cientos de módulos. Las dos tecnologías DMPPT que existen en el mercado son conocidos como microinversores y optimizadores de potencia, y ofrecen ciertas ventajas sobre sistemas de MPPT central como: mayor producción en situaciones de mismatch, monitorización individual de cada módulo, flexibilidad de diseño, mayor seguridad del sistema, etc. Aunque los sistemas DMPPT no están limitados a los entornos urbanos, se ha enfatizado en el título ya que es su mercado natural, siendo difícil una justificación de su sobrecoste en grandes huertas solares en suelo. Desde el año 2010 el mercado de estos sistemas ha incrementado notablemente y sigue creciendo de una forma continuada. Sin embargo, todavía falta un conocimiento profundo de cómo funcionan estos sistemas, especialmente en el caso de los optimizadores de potencia, de las ganancias energéticas esperables en condiciones de mismatch y de las posibilidades avanzadas de diagnóstico de fallos. El principal objetivo de esta tesis es presentar un estudio completo de cómo funcionan los sistemas DMPPT, sus límites y sus ventajas, así como experimentos varios que verifican la teoría y el desarrollo de herramientas para valorar las ventajas de utilizar DMPPT en cada instalación. Las ecuaciones que modelan el funcionamiento de los sistemas FVs con optimizadores de potencia se han desarrollado y utilizado para resaltar los límites de los mismos a la hora de resolver ciertas situaciones de mismatch. Se presenta un estudio profundo sobre el efecto de las sombras en los sistemas FVs: en la curva I-V y en los algoritmos MPPT. Se han llevado a cabo experimentos sobre el funcionamiento de los algoritmos MPPT en situaciones de sombreado, señalando su ineficiencia en estas situaciones. Un análisis de la ventaja del uso de DMPPT frente a los puntos calientes es presentado y verificado. También se presenta un análisis sobre las posibles ganancias en potencia y energía con el uso de DMPPT en condiciones de sombreado y este también es verificado experimentalmente, así como un breve estudio de su viabilidad económica. Para ayudar a llevar a cabo todos los análisis y experimentos descritos previamente se han desarrollado una serie de herramientas software. Una siendo un programa en LabView para controlar un simulador solar y almacenar las medidas. También se ha desarrollado un programa que simula curvas I-V de módulos y generador FVs afectados por sombras y este se ha verificado experimentalmente. Este mismo programa se ha utilizado para desarrollar un programa todavía más completo que estima las pérdidas anuales y las ganancias obtenidas con DMPPT en instalaciones FVs afectadas por sombras. Finalmente, se han desarrollado y verificado unos algoritmos para diagnosticar fallos en sistemas FVs con DMPPT. Esta herramienta puede diagnosticar los siguientes fallos: sombras debido a objetos fijos (con estimación de la distancia al objeto), suciedad localizada, suciedad general, posible punto caliente, degradación de módulos y pérdidas en el cableado de DC. Además, alerta al usuario de las pérdidas producidas por cada fallo y no requiere del uso de sensores de irradiancia y temperatura. ABSTRACT This work is a contribution to photovoltaic (PV) systems with distributed maximum power point tracking (DMPPT), a system topology characterized by performing the MPPT at module level, instead of the more traditional topologies which perform MPPT for a larger number of modules. The two DMPPT technologies available at the moment are known as microinverters and power optimizers, also known as module level power electronics (MLPE), and they provide certain advantages over central MPPT systems like: higher energy production in mismatch situations, monitoring of each individual module, system design flexibility, higher system safety, etc. Although DMPPT is not limited to urban environments, it has been emphasized in the title as it is their natural market, since in large ground-mounted PV plants the extra cost is difficult to justify. Since 2010 MLPE have increased their market share steadily and continuing to grow steadily. However, there still lacks a profound understanding of how they work, especially in the case of power optimizers, the achievable energy gains with their use and the possibilities in failure diagnosis. The main objective of this thesis is to provide a complete understanding of DMPPT technologies: how they function, their limitations and their advantages. A series of equations used to model PV arrays with power optimizers have been derived and used to point out limitations in solving certain mismatch situation. Because one of the most emphasized benefits of DMPPT is their ability to mitigate shading losses, an extensive study on the effects of shadows on PV systems is presented; both on the I-V curve and on MPPT algorithms. Experimental tests have been performed on the MPPT algorithms of central inverters and MLPE, highlighting their inefficiency in I-V curves with local maxima. An analysis of the possible mitigation of hot-spots with DMPPT is discussed and experimentally verified. And a theoretical analysis of the possible power and energy gains is presented as well as experiments in real PV systems. A short economic analysis of the benefits of DMPPT has also been performed. In order to aide in the previous task, a program which simulates I-V curves under shaded conditions has been developed and experimentally verified. This same program has been used to develop a software tool especially designed for PV systems affected by shading, which estimates the losses due to shading and the energy gains obtained with DMPPT. Finally, a set of algorithms for diagnosing system faults in PV systems with DMPPT has been developed and experimentally verified. The tool can diagnose the following failures: fixed object shading (with distance estimation), localized dirt, generalized dirt, possible hot-spots, module degradation and excessive losses in DC cables. In addition, it alerts the user of the power losses produced by each failure and classifies the failures by their severity and it does not require the use of irradiance or temperature sensors.

Distributed Estimation of Distribution Algorithms for continuous optimization: how does the exchanged information influence their behavior?

One of the most promising areas in which probabilistic graphical models have shown an incipient activity is the field of heuristic optimization and, in particular, in Estimation of Distribution Algorithms. Due to their inherent parallelism, different research lines have been studied trying to improve Estimation of Distribution Algorithms from the point of view of execution time and/or accuracy. Among these proposals, we focus on the so-called distributed or island-based models. This approach defines several islands (algorithms instances) running independently and exchanging information with a given frequency. The information sent by the islands can be either a set of individuals or a probabilistic model. This paper presents a comparative study for a distributed univariate Estimation of Distribution Algorithm and a multivariate version, paying special attention to the comparison of two alternative methods for exchanging information, over a wide set of parameters and problems ? the standard benchmark developed for the IEEE Workshop on Evolutionary Algorithms and other Metaheuristics for Continuous Optimization Problems of the ISDA 2009 Conference. Several analyses from different points of view have been conducted to analyze both the influence of the parameters and the relationships between them including a characterization of the configurations according to their behavior on the proposed benchmark.

Heated fiber optic distributed temperature sensing for measuring soil volumetric heat capacity and water content: A dual probe heat-pulse approach

The first feasibility study of using dual-probe heated fiber optics with distributed temperature sensing to measure soil volumetric heat capacity and soil water content is presented. Although results using different combinations of cables demonstrate feasibility, further work is needed to gain accuracy, including a model to account for the finite dimension and the thermal influence of the probes. Implementation of the dual-probe heat-pulse (DPHP) approach for measurement of volumetric heat capacity (C) and water content (θ) with distributed temperature sensing heated fiber optic (FO) systems presents an unprecedented opportunity for environmental monitoring (e.g., simultaneous measurement at thousands of points). We applied uniform heat pulses along a FO cable and monitored the thermal response at adjacent cables. We tested the DPHP method in the laboratory using multiple FO cables at a range of spacings. The amplitude and phase shift in the heat signal with distance was found to be a function of the soil volumetric heat capacity. Estimations of C at a range of moisture contents (θ = 0.09– 0.34 m3 m−3) suggest the feasibility of measurement via responsiveness to the changes in θ, although we observed error with decreasing soil water contents (up to 26% at θ = 0.09 m3 m−3). Optimization will require further models to account for the finite radius and thermal influence of the FO cables. Although the results indicate that the method shows great promise, further study is needed to quantify the effects of soil type, cable spacing, and jacket configurations on accuracy.

Context-awareness in task automation services by distributed event processing

Everybody has to coordinate several tasks everyday, usually in a manual manner. Recently, the concept of Task Automation Services has been introduced to automate and personalize the task coordination problem. Several user centered platforms and applications have arisen in the last years, that let their users configure their very own automations based on third party services. In this paper, we propose a new system architecture for Task Automation Services in a heterogeneous mobile, smart devices, and cloud services environment. Our architecture is based on the novel idea to employ distributed Complex Event Processing to implement innovative mixed execution profiles. The major advantage of the approach is its ability to incorporate context-awareness and real-time coordination in Task Automation Services.

Enhancing Guideline-based decision support with distributed computation through local mobile application

We introduce the need for a distributed guideline-based decision sup-port (DSS) process, describe its characteristics, and explain how we implement-ed this process within the European Union?s MobiGuide project. In particular, we have developed a mechanism of sequential, piecemeal projection, i.e., 'downloading' small portions of the guideline from the central DSS server, to the local DSS in the patient's mobile device, which then applies that portion, us-ing the mobile device's local resources. The mobile device sends a callback to the central DSS when it encounters a triggering pattern predefined in the pro-jected module, which leads to an appropriate predefined action by the central DSS, including sending a new projected module, or directly controlling the rest of the workflow. We suggest that such a distributed architecture that explicitly defines a dialog between a central DSS server and a local DSS module, better balances the computational load and exploits the relative advantages of the cen-tral server and of the local mobile device.

Advanced Characterisation of a Coffee Fermenting Tank by Multi-distributed Wireless Sensors: Spatial Interpolation and Phase Space Graphs

The fermentation stage is considered to be one of the critical steps in coffee processing due to its impact on the final quality of the product. The objective of this work is to characterise the temperature gradients in a fermentation tank by multi-distributed, low-cost and autonomous wireless sensors (23 semi-passive TurboTag® radio-frequency identifier (RFID) temperature loggers). Spatial interpolation in polar coordinates and an innovative methodology based on phase space diagrams are used. A real coffee fermentation process was supervised in the Cauca region (Colombia) with sensors submerged directly in the fermenting mass, leading to a 4.6 °C temperature range within the fermentation process. Spatial interpolation shows a maximum instant radial temperature gradient of 0.1 °C/cm from the centre to the perimeter of the tank and a vertical temperature gradient of 0.25 °C/cm for sensors with equal polar coordinates. The combination of spatial interpolation and phase space graphs consistently enables the identification of five local behaviours during fermentation (hot and cold spots).

Distributed, layered and reliable computing nets to represent neuronal receptive fields

Abstract. Receptive fields of retinal and other sensory neurons show a large variety of spatiotemporal linear and non linear types of responses to local stimuli. In visual neurons, these responses present either asymmetric sensitive zones or center-surround organization. In most cases, the nature of the responses suggests the existence of a kind of distributed computation prior to the integration by the final cell which is evidently supported by the anatomy. We describe a new kind of discrete and continuous filters to model the kind of computations taking place in the receptive fields of retinal cells. To show their performance in the analysis of diferent non-trivial neuron-like structures, we use a computer tool specifically programmed by the authors to that efect. This tool is also extended to study the efect of lesions on the whole performance of our model nets.

Emission regimes in a distributed feedback tapered master-oscillator power-amplifier at 1.5 µm

Integrated master-oscillator power amplifiers driven under steady-state injection conditions are known to show a complex dynamics resulting in a variety of emission regimes. We present experimental results on the emission characteristics of a 1.5 µm distributed feedback tapered master-oscillator power-amplifier in a wide range of steady-state injection conditions, showing different dynamic behaviors. The study combines the optical and radio-frequency spectra recorded under different levels of injected current into the master oscillator and the power amplifier sections. Under low injection current of the master oscillator the correlation between the optical and radio-frequency spectral maps allows to identify operation regimes in which the device emission arises from either the master oscillator mode or from the compound cavity modes allowed by the residual reflectance of the amplifier front facet. The quasi-periodic occurrence of these emission regimes as a function of the amplifier current is interpreted in terms of a thermally tuned competition between the modes of the master oscillator and the compound cavity modes. Under high injection current of the masteroscillator, two different regimes alternate quasi-periodically as a function of the injected current in the power amplifier: a stable regime with a single mode emission at the master oscillator frequency, and an unstable and complex self-pulsating regime showing strong peaks in the radio-frequency spectra as well as multiple frequencies in the optical spectra.

Some applications of distributed signal processing

In this work we review some earlier distributed algorithms developed by the authors and collaborators, which are based on two different approaches, namely, distributed moment estimation and distributed stochastic approximations. We show applications of these algorithms on image compression, linear classification and stochastic optimal control. In all cases, the benefit of cooperation is clear: even when the nodes have access to small portions of the data, by exchanging their estimates, they achieve the same performance as that of a centralized architecture, which would gather all the data from all the nodes.

Distributed cognitive radio systems with temperature-interference constraints and overlay scheme

Cognitive radio represents a promising paradigm to further increase transmission rates in wireless networks, as well as to facilitate the deployment of self-organized networks such as femtocells. Within this framework, secondary users (SU) may exploit the channel under the premise to maintain the quality of service (QoS) on primary users (PU) above a certain level. To achieve this goal, we present a noncooperative game where SU maximize their transmission rates, and may act as well as relays of the PU in order to hold their perceived QoS above the given threshold. In the paper, we analyze the properties of the game within the theory of variational inequalities, and provide an algorithm that converges to one Nash Equilibrium of the game. Finally, we present some simulations and compare the algorithm with another method that does not consider SU acting as relays.

Multi-distributed wireless sensors for monitoring a long distance transport in a reefer container

The study of the temperature gradients in cold stores and containers is a critical issue in the food industry for the quality assurance of products during transport and for minimising losses. This work presents an analysis of the temperatures during the refrigerated transport of 4,320 kg of blueberries in a reefer (set point temperature at ?1ºC) on a container ship from Montevideo (Uruguay) to Verona (Italy). The monitoring was performed by using semi-passive RFID loggers (TurboTag cards). The objective was to carry out a multi-distributed supervision using low-cost, wireless and autonomous sensors for the characterisation of the distribution and spatial gradients of temperatures during a long distance transport. Data analysis shows spatial (phase space) and temporal sequencing diagrams and reveals a significant heterogeneity of temperature at different locations in the container, which highlights the ineffectiveness of a temperature control system based on a single sensor, as is usually done.

Agreement Abstractions in Anonymous and Homonymous Distributed Systems Prone to Failures

The distributed computing models typically assume every process in the system has a distinct identifier (ID) or each process is programmed differently, which is named as eponymous system. In such kind of distributed systems, the unique ID is helpful to solve problems: it can be incorporated into messages to make them trackable (i.e., to or from which process they are sent) to facilitate the message transmission; several problems (leader election, consensus, etc.) can be solved without the information of network property in priori if processes have unique IDs; messages in the register of one process will not be overwritten by others process if this process announces; it is useful to break the symmetry. Hence, eponymous systems have influenced the distributed computing community significantly either in theory or in practice. However, every thing in the world has its own two sides. The unique ID also has disadvantages: it can leak information of the network(size); processes in the system have no privacy; assign unique ID is costly in bulk-production(e.g, sensors). Hence, homonymous system is appeared. If some processes share the same ID and programmed identically is called homonymous system. Furthermore, if all processes shared the same ID or have no ID is named as anonymous system. In homonymous or anonymous distributed systems, the symmetry problem (i.e., how to distinguish messages sent from which process) is the main obstacle in the design of algorithms. This thesis is aimed to propose different symmetry break methods (e.g., random function, counting technique, etc.) to solve agreement problem. Agreement is a fundamental problem in distributed computing including a family of abstractions. In this thesis, we mainly focus on the design of consensus, set agreement, broadcast algorithms in anonymous and homonymous distributed systems. Firstly, the fault-tolerant broadcast abstraction is studied in anonymous systems with reliable or fair lossy communication channels separately. Two classes of anonymous failure detectors AΘ and AP∗ are proposed, and both of them together with a already proposed failure detector ψ are implemented and used to enrich the system model to implement broadcast abstraction. Then, in the study of the consensus abstraction, it is proved the AΩ′ failure detector class is strictly weaker than AΩ and AΩ′ is implementable. The first implementation of consensus in anonymous asynchronous distributed systems augmented with AΩ′ and where a majority of processes does not crash. Finally, a general consensus problem– k-set agreement is researched and the weakest failure detector L used to solve it, in asynchronous message passing systems where processes may crash and recover, with homonyms (i.e., processes may have equal identities), and without a complete initial knowledge of the membership.