932 resultados para distributed computing projects
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We present a static analysis that infers both upper and lower bounds on the usage that a logic program makes of a set of user-definable resources. The inferred bounds will in general be functions of input data sizes. A resource in our approach is a quite general, user-defined notion which associates a basic cost function with elementary operations. The analysis then derives the related (upper- and lower-bound) resource usage functions for all predicates in the program. We also present an assertion language which is used to define both such resources and resourcerelated properties that the system can then check based on the results of the analysis. We have performed some preliminary experiments with some concrete resources such as execution steps, bytes sent or received by an application, number of files left open, number of accesses to a datábase, number of calis to a procedure, number of asserts/retracts, etc. Applications of our analysis include resource consumption verification and debugging (including for mobile code), resource control in parallel/distributed computing, and resource-oriented specialization.
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We present a generic analysis that infers both upper and lower bounds on the usage that a program makes of a set of user-definable resources. The inferred bounds will in general be functions of input data sizes. A resource in our approach is a quite general, user-defined notion which associates a basic cost function with elementary operations. The analysis then derives the related (upper- and lower- bound) cost functions for all procedures in the program. We also present an assertion language which is used to define both such resources and resource-related properties that the system can then check based on the results of the analysis. We have performed some experiments with some concrete resource-related properties such as execution steps, bits sent or received by an application, number of arithmetic operations performed, number of calls to a procedure, number of transactions, etc. presenting the resource usage functions inferred and the times taken to perform the analysis. Applications of our analysis include resource consumption verification and debugging (including for mobile code), resource control in parallel/distributed computing, and resource-oriented specialization.
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Many mobile devices embed nowadays inertial sensors. This enables new forms of human-computer interaction through the use of gestures (movements performed with the mobile device) as a way of communication. This paper presents an accelerometer-based gesture recognition system for mobile devices which is able to recognize a collection of 10 different hand gestures. The system was conceived to be light and to operate in a user -independent manner in real time. The recognition system was implemented in a smart phone and evaluated through a collection of user tests, which showed a recognition accuracy similar to other state-of-the art techniques and a lower computational complexity. The system was also used to build a human -robot interface that enables controlling a wheeled robot with the gestures made with the mobile phone.
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Over the last decade, Grid computing paved the way for a new level of large scale distributed systems. This infrastructure made it possible to securely and reliably take advantage of widely separated computational resources that are part of several different organizations. Resources can be incorporated to the Grid, building a theoretical virtual supercomputer. In time, cloud computing emerged as a new type of large scale distributed system, inheriting and expanding the expertise and knowledge that have been obtained so far. Some of the main characteristics of Grids naturally evolved into clouds, others were modified and adapted and others were simply discarded or postponed. Regardless of these technical specifics, both Grids and clouds together can be considered as one of the most important advances in large scale distributed computing of the past ten years; however, this step in distributed computing has came along with a completely new level of complexity. Grid and cloud management mechanisms play a key role, and correct analysis and understanding of the system behavior are needed. Large scale distributed systems must be able to self-manage, incorporating autonomic features capable of controlling and optimizing all resources and services. Traditional distributed computing management mechanisms analyze each resource separately and adjust specific parameters of each one of them. When trying to adapt the same procedures to Grid and cloud computing, the vast complexity of these systems can make this task extremely complicated. But large scale distributed systems complexity could only be a matter of perspective. It could be possible to understand the Grid or cloud behavior as a single entity, instead of a set of resources. This abstraction could provide a different understanding of the system, describing large scale behavior and global events that probably would not be detected analyzing each resource separately. In this work we define a theoretical framework that combines both ideas, multiple resources and single entity, to develop large scale distributed systems management techniques aimed at system performance optimization, increased dependability and Quality of Service (QoS). The resulting synergy could be the key 350 J. Montes et al. to address the most important difficulties of Grid and cloud management.
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Many macroscopic properties: hardness, corrosion, catalytic activity, etc. are directly related to the surface structure, that is, to the position and chemical identity of the outermost atoms of the material. Current experimental techniques for its determination produce a “signature” from which the structure must be inferred by solving an inverse problem: a solution is proposed, its corresponding signature computed and then compared to the experiment. This is a challenging optimization problem where the search space and the number of local minima grows exponentially with the number of atoms, hence its solution cannot be achieved for arbitrarily large structures. Nowadays, it is solved by using a mixture of human knowledge and local search techniques: an expert proposes a solution that is refined using a local minimizer. If the outcome does not fit the experiment, a new solution must be proposed again. Solving a small surface can take from days to weeks of this trial and error method. Here we describe our ongoing work in its solution. We use an hybrid algorithm that mixes evolutionary techniques with trusted region methods and reuses knowledge gained during the execution to avoid repeated search of structures. Its parallelization produces good results even when not requiring the gathering of the full population, hence it can be used in loosely coupled environments such as grids. With this algorithm, the solution of test cases that previously took weeks of expert time can be automatically solved in a day or two of uniprocessor time.
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This work describes a semantic extension for a user-smart object interaction model based on the ECA paradigm (Event-Condition-Action). In this approach, smart objects publish their sensing (event) and action capabilities in the cloud and mobile devices are prepared to retrieve them and act as mediators to configure personalized behaviours for the objects. In this paper, the information handled by this interaction system has been shaped according several semantic models that, together with the integration of an embedded ontological and rule-based reasoner, are exploited in order to (i) automatically detect incompatible ECA rules configurations and to (ii) support complex ECA rules definitions and execution. This semantic extension may significantly improve the management of smart spaces populated with numerous smart objects from mobile personal devices, as it facilitates the configuration of coherent ECA rules.
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When non linear physical systems of infinite extent are modelled, such as tunnels and perforations, it is necessary to simulate suitably the solution in the infinite as well as the non linearity. The finite element method (FEM) is a well known procedure for simulating the non linear behavior. However, the treatment of the infinite field with domain truncations is often questionable. On the other hand, the boundary element method (BEM) is suitable to simulate the infinite behavior without truncations. Because of this, by the combination of both methods, suitable use of the advantages of each one may be obtained. Several possibilities of FEM-BEM coupling and their performance in some practical cases are discussed in this paper. Parallelizable coupling algorithms based on domain decomposition are developed and compared with the most traditional coupling methods.
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We propose distributed algorithms for sampling networks based on a new class of random walks that we call Centrifugal Random Walks (CRW). A CRW is a random walk that starts at a source and always moves away from it. We propose CRW algorithms for connected networks with arbitrary probability distributions, and for grids and networks with regular concentric connectivity with distance based distributions. All CRW sampling algorithms select a node with the exact probability distribution, do not need warm-up, and end in a number of hops bounded by the network diameter.
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La computación distribuida ha estado presente desde hace unos cuantos años, pero es quizás en la actualidad cuando está contando con una mayor repercusión. En los últimos años el modelo de computación en la nube (Cloud computing) ha ganado mucha popularidad, prueba de ello es la cantidad de productos existentes. Todo sistema informático requiere ser controlado a través de sistemas de monitorización que permiten conocer el estado del mismo, de tal manera que pueda ser gestionado fácilmente. Hoy en día la mayoría de los productos de monitorización existentes limitan a la hora de visualizar una representación real de la arquitectura de los sistemas a monitorizar, lo que puede dificultar la tarea de los administradores. Es decir, la visualización que proporcionan de la arquitectura del sistema, en muchos casos se ve influenciada por el diseño del sistema de visualización, lo que impide ver los niveles de la arquitectura y las relaciones entre estos. En este trabajo se presenta un sistema de monitorización para sistemas distribuidos o Cloud, que pretende dar solución a esta problemática, no limitando la representación de la arquitectura del sistema a monitorizar. El sistema está formado por: agentes, que se encargan de la tarea de recolección de las métricas del sistema monitorizado; un servidor, al que los agentes le envían las métricas para que las almacenen en una base de datos; y una aplicación web, a través de la que se visualiza toda la información. El sistema ha sido probado satisfactoriamente con la monitorización de CumuloNimbo, una plataforma como servicio (PaaS), que ofrece interfaz SQL y procesamiento transaccional altamente escalable sobre almacenes clave valor. Este trabajo describe la arquitectura del sistema de monitorización, y en concreto, el desarrollo de la principal contribución al sistema, la aplicación web. ---ABSTRACT---Distributed computing has been around for quite a long time, but now it is becoming more and more important. In the last few years, cloud computing, a branch of distributed computing has become very popular, as its different products in the market can prove. Every computing system requires to be controlled through monitoring systems to keep them functioning correctly. Currently, most of the monitoring systems in the market only provide a view of the architectures of the systems monitored, which in most cases do not permit having a real view of the system. This lack of vision can make administrators’ tasks really difficult. If they do not know the architecture perfectly, controlling the system based on the view that the monitoring system provides is extremely complicated. The project introduces a new monitoring system for distributed or Cloud systems, which shows the real architecture of the system. This new system is composed of several elements: agents, which collect the metrics of the monitored system; a server, which receives the metrics from the agents and saves them in a database; and a web application, which shows all the data collected in an easy way. The monitoring system has been tested successfully with Cumulonimbo. CumuloNimbo is a platform as a service (PaaS) which offers an SQL interface and a high-scalable transactional process. This platform works over key-value storage. This project describes the architecture of the monitoring system, especially, the development of the web application, which is the main contribution to the system.
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En el trabajo que aquí presentamos se incluye la base teórica (sintaxis y semántica) y una implementación de un framework para codificar el razonamiento de la representación difusa o borrosa del mundo (tal y como nosotros, seres humanos, entendemos éste). El interés en la realización de éste trabajo parte de dos fuentes: eliminar la complejidad existente cuando se realiza una implementación con un lenguaje de programación de los llamados de propósito general y proporcionar una herramienta lo suficientemente inteligente para dar respuestas de forma constructiva a consultas difusas o borrosas. El framework, RFuzzy, permite codificar reglas y consultas en una sintaxis muy cercana al lenguaje natural usado por los seres humanos para expresar sus pensamientos, pero es bastante más que eso. Permite representar conceptos muy interesantes, como fuzzificaciones (funciones usadas para convertir conceptos no difusos en difusos), valores por defecto (que se usan para devolver resultados un poco menos válidos que los que devolveríamos si tuviésemos la información necesaria para calcular los más válidos), similaridad entre atributos (característica que utilizamos para buscar aquellos individuos en la base de datos con una característica similar a la buscada), sinónimos o antónimos y, además, nos permite extender el numero de conectivas y modificadores (incluyendo modificadores de negación) que podemos usar en las reglas y consultas. La personalización de la definición de conceptos difusos (muy útil para lidiar con el carácter subjetivo de los conceptos borrosos, donde nos encontramos con que cualificar a alguien de “alto” depende de la altura de la persona que cualifica) es otra de las facilidades incluida. Además, RFuzzy implementa la semántica multi-adjunta. El interés en esta reside en que introduce la posibilidad de obtener la credibilidad de una regla a partir de un conjunto de datos y una regla dada y no solo el grado de satisfacción de una regla a partir de el universo modelado en nuestro programa. De esa forma podemos obtener automáticamente la credibilidad de una regla para una determinada situación. Aún cuando la contribución teórica de la tesis es interesante en si misma, especialmente la inclusión del modificador de negacion, sus multiples usos practicos lo son también. Entre los diferentes usos que se han dado al framework destacamos el reconocimiento de emociones, el control de robots, el control granular en computacion paralela/distribuída y las busquedas difusas o borrosas en bases de datos. ABSTRACT In this work we provide a theoretical basis (syntax and semantics) and a practical implementation of a framework for encoding the reasoning and the fuzzy representation of the world (as human beings understand it). The interest for this work comes from two sources: removing the existing complexity when doing it with a general purpose programming language (one developed without focusing in providing special constructions for representing fuzzy information) and providing a tool intelligent enough to answer, in a constructive way, expressive queries over conventional data. The framework, RFuzzy, allows to encode rules and queries in a syntax very close to the natural language used by human beings to express their thoughts, but it is more than that. It allows to encode very interesting concepts, as fuzzifications (functions to easily fuzzify crisp concepts), default values (used for providing results less adequate but still valid when the information needed to provide results is missing), similarity between attributes (used to search for individuals with a characteristic similar to the one we are looking for), synonyms or antonyms and it allows to extend the number of connectives and modifiers (even negation) we can use in the rules. The personalization of the definition of fuzzy concepts (very useful for dealing with the subjective character of fuzziness, in which a concept like tall depends on the height of the person performing the query) is another of the facilities included. Besides, RFuzzy implements the multi-adjoint semantics. The interest in them is that in addition to obtaining the grade of satisfaction of a consequent from a rule, its credibility and the grade of satisfaction of the antecedents we can determine from a set of data how much credibility we must assign to a rule to model the behaviour of the set of data. So, we can determine automatically the credibility of a rule for a particular situation. Although the theoretical contribution is interesting by itself, specially the inclusion of the negation modifier, the practical usage of it is equally important. Between the different uses given to the framework we highlight emotion recognition, robocup control, granularity control in parallel/distributed computing and flexible searches in databases.
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Los resultados presentados en la memoria de esta tesis doctoral se enmarcan en la denominada computación celular con membranas una nueva rama de investigación dentro de la computación natural creada por Gh. Paun en 1998, de ahí que habitualmente reciba el nombre de sistemas P. Este nuevo modelo de cómputo distribuido está inspirado en la estructura y funcionamiento de la célula. El objetivo de esta tesis ha sido analizar el poder y la eficiencia computacional de estos sistemas de computación celular. En concreto, se han analizado dos tipos de sistemas P: por un lado los sistemas P de neuronas de impulsos, y por otro los sistemas P con proteínas en las membranas. Para el primer tipo, los resultados obtenidos demuestran que es posible que estos sistemas mantengan su universalidad aunque muchas de sus características se limiten o incluso se eliminen. Para el segundo tipo, se analiza la eficiencia computacional y se demuestra que son capaces de resolver problemas de la clase de complejidad ESPACIO-P (PSPACE) en tiempo polinómico. Análisis del poder computacional: Los sistemas P de neuronas de impulsos (en adelante SN P, acrónimo procedente del inglés «Spiking Neural P Systems») son sistemas inspirados en el funcionamiento neuronal y en la forma en la que los impulsos se propagan por las redes sinápticas. Los SN P bio-inpirados poseen un numeroso abanico de características que ha cen que dichos sistemas sean universales y por tanto equivalentes, en poder computacional, a una máquina de Turing. Estos sistemas son potentes a nivel computacional, pero tal y como se definen incorporan numerosas características, quizás demasiadas. En (Ibarra et al. 2007) se demostró que en estos sistemas sus funcionalidades podrían ser limitadas sin comprometer su universalidad. Los resultados presentados en esta memoria son continuistas con la línea de trabajo de (Ibarra et al. 2007) y aportan nuevas formas normales. Esto es, nuevas variantes simplificadas de los sistemas SN P con un conjunto mínimo de funcionalidades pero que mantienen su poder computacional universal. Análisis de la eficiencia computacional: En esta tesis se ha estudiado la eficiencia computacional de los denominados sistemas P con proteínas en las membranas. Se muestra que este modelo de cómputo es equivalente a las máquinas de acceso aleatorio paralelas (PRAM) o a las máquinas de Turing alterantes ya que se demuestra que un sistema P con proteínas, es capaz de resolver un problema ESPACIOP-Completo como el QSAT(problema de satisfacibilidad de fórmulas lógicas cuantificado) en tiempo polinómico. Esta variante de sistemas P con proteínas es muy eficiente gracias al poder de las proteínas a la hora de catalizar los procesos de comunicación intercelulares. ABSTRACT The results presented at this thesis belong to membrane computing a new research branch inside of Natural computing. This new branch was created by Gh. Paun on 1998, hence usually receives the name of P Systems. This new distributed computing model is inspired on structure and functioning of cell. The aim of this thesis is to analyze the efficiency and computational power of these computational cellular systems. Specifically there have been analyzed two different classes of P systems. On the one hand it has been analyzed the Neural Spiking P Systems, and on the other hand it has been analyzed the P systems with proteins on membranes. For the first class it is shown that it is possible to reduce or restrict the characteristics of these kind of systems without loss of computational power. For the second class it is analyzed the computational efficiency solving on polynomial time PSACE problems. Computational Power Analysis: The spiking neural P systems (SN P in short) are systems inspired by the way of neural cells operate sending spikes through the synaptic networks. The bio-inspired SN Ps possess a large range of features that make these systems to be universal and therefore equivalent in computational power to a Turing machine. Such systems are computationally powerful, but by definition they incorporate a lot of features, perhaps too much. In (Ibarra et al. in 2007) it was shown that their functionality may be limited without compromising its universality. The results presented herein continue the (Ibarra et al. 2007) line of work providing new formal forms. That is, new SN P simplified variants with a minimum set of functionalities but keeping the universal computational power. Computational Efficiency Analisys: In this thesis we study the computational efficiency of P systems with proteins on membranes. We show that this computational model is equivalent to parallel random access machine (PRAM) or alternating Turing machine because, we show P Systems with proteins can solve a PSPACE-Complete problem as QSAT (Quantified Propositional Satisfiability Problem) on polynomial time. This variant of P Systems with proteins is very efficient thanks to computational power of proteins to catalyze inter-cellular communication processes.
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Postprint
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Virtual Worlds Generator is a grammatical model that is proposed to define virtual worlds. It integrates the diversity of sensors and interaction devices, multimodality and a virtual simulation system. Its grammar allows the definition and abstraction in symbols strings of the scenes of the virtual world, independently of the hardware that is used to represent the world or to interact with it. A case study is presented to explain how to use the proposed model to formalize a robot navigation system with multimodal perception and a hybrid control scheme of the robot.
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Virtual Worlds Generator is a grammatical model that is proposed to define virtual worlds. It integrates the diversity of sensors and interaction devices, multimodality and a virtual simulation system. Its grammar allows the definition and abstraction in symbols strings of the scenes of the virtual world, independently of the hardware that is used to represent the world or to interact with it. A case study is presented to explain how to use the proposed model to formalize a robot navigation system with multimodal perception and a hybrid control scheme of the robot. The result is an instance of the model grammar that implements the robotic system and is independent of the sensing devices used for perception and interaction. As a conclusion the Virtual Worlds Generator adds value in the simulation of virtual worlds since the definition can be done formally and independently of the peculiarities of the supporting devices.
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his paper discusses a process to graphically view and analyze information obtained from a network of urban streets, using an algorithm that establishes a ranking of importance of the nodes of the network itself. The basis of this process is to quantify the network information obtained by assigning numerical values to each node, representing numerically the information. These values are used to construct a data matrix that allows us to apply a classification algorithm of nodes in a network in order of importance. From this numerical ranking of the nodes, the process finish with the graphical visualization of the network. An example is shown to illustrate the whole process.