84 resultados para distributed application
Resumo:
The goal of this paper is twofold. Firstly, to survey in a systematic and uniform way the main results regarding the way membranes can be placed on processors in order to get a software/hardware simulation of P-Systems in a distributed environment. Secondly, we improve some results about the membrane dissolution problem, prove that it is connected, and discuss the possibility of simulating this property in the distributed model. All this yields an improvement in the system parallelism implementation since it gets an increment of the parallelism of the external communication among processors. Also, the number of processors grows in such a way that is notorious the increment of the parallelism in the application of the evolution rules and the internal communica-tionsstudy because it gets an increment of the parallelism in the application of the evolution rules and the internal communications. Proposed ideas improve previous architectures to tackle the communication bottleneck problem, such as reduction of the total time of an evolution step, increase of the number of membranes that could run on a processor and reduction of the number of processors
Resumo:
Belief propagation (BP) is a technique for distributed inference in wireless networks and is often used even when the underlying graphical model contains cycles. In this paper, we propose a uniformly reweighted BP scheme that reduces the impact of cycles by weighting messages by a constant ?edge appearance probability? rho ? 1. We apply this algorithm to distributed binary hypothesis testing problems (e.g., distributed detection) in wireless networks with Markov random field models. We demonstrate that in the considered setting the proposed method outperforms standard BP, while maintaining similar complexity. We then show that the optimal ? can be approximated as a simple function of the average node degree, and can hence be computed in a distributed fashion through a consensus algorithm.
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This article proposes a MAS architecture for network diagnosis under uncertainty. Network diagnosis is divided into two inference processes: hypothesis generation and hypothesis confirmation. The first process is distributed among several agents based on a MSBN, while the second one is carried out by agents using semantic reasoning. A diagnosis ontology has been defined in order to combine both inference processes. To drive the deliberation process, dynamic data about the influence of observations are taken during diagnosis process. In order to achieve quick and reliable diagnoses, this influence is used to choose the best action to perform. This approach has been evaluated in a P2P video streaming scenario. Computational and time improvements are highlight as conclusions.
Resumo:
Many of the emerging telecom services make use of Outer Edge Networks, in particular Home Area Networks. The configuration and maintenance of such services may not be under full control of the telecom operator which still needs to guarantee the service quality experienced by the consumer. Diagnosing service faults in these scenarios becomes especially difficult since there may be not full visibility between different domains. This paper describes the fault diagnosis solution developed in the MAGNETO project, based on the application of Bayesian Inference to deal with the uncertainty. It also takes advantage of a distributed framework to deploy diagnosis components in the different domains and network elements involved, spanning both the telecom operator and the Outer Edge networks. In addition, MAGNETO features self-learning capabilities to automatically improve diagnosis knowledge over time and a partition mechanism that allows breaking down the overall diagnosis knowledge into smaller subsets. The MAGNETO solution has been prototyped and adapted to a particular outer edge scenario, and has been further validated on a real testbed. Evaluation of the results shows the potential of our approach to deal with fault management of outer edge networks.
Resumo:
Animal tracking has been addressed by different initiatives over the last two decades. Most of them rely on satellite connectivity on every single node and lack of energy-saving strategies. This paper presents several new contributions on the tracking of dynamic heterogeneous asynchronous networks (primary nodes with GPS and secondary nodes with a kinetic generator) motivated by the animal tracking paradigm with random transmissions. A simple approach based on connectivity and coverage intersection is compared with more sophisticated algorithms based on ad-hoc implementations of distributed Kalman-based filters that integrate measurement information using Consensus principles in order to provide enhanced accuracy. Several simulations varying the coverage range, the random behavior of the kinetic generator (modeled as a Poisson Process) and the periodic activation of GPS are included. In addition, this study is enhanced with HW developments and implementations on commercial off-the-shelf equipment which show the feasibility for performing these proposals on real hardware.
Resumo:
This paper introduces a method to analyze and predict stability and transient performance of a distributed system where COTS (Commercial-off-the-shelf) modules share an input filter. The presented procedure is based on the measured data from the input and output terminals of the power modules. The required information for the analysis is obtained by performing frequency response measurements for each converter. This attained data is utilized to compute special transfer functions, which partly determine the source and load interactions within the converters. The system level dynamic description is constructed based on the measured and computed transfer functions introducing cross-coupling mechanisms within the system. System stability can be studied based on the well-known impedance- related minor-loop gain at an arbitrary interface within the system.
Resumo:
We use an automatic weather station and surface mass balance dataset spanning four melt seasons collected on Hurd Peninsula Glaciers, South Shetland Islands, to investigate the point surface energy balance, to determine the absolute and relative contribution of the various energy fluxes acting on the glacier surface and to estimate the sensitivity of melt to ambient temperature changes. Long-wave incoming radiation is the main energy source for melt, while short-wave radiation is the most important flux controlling the variation of both seasonal and daily mean surface energy balance. Short-wave and long-wave radiation fluxes do, in general, balance each other, resulting in a high correspondence between daily mean net radiation flux and available melt energy flux. We calibrate a distributed melt model driven by air temperature and an expression for the incoming short-wave radiation. The model is calibrated with the data from one of the melt seasons and validated with the data of the three remaining seasons. The model results deviate at most 140 mm w.e. from the corresponding observations using the glaciological method. The model is very sensitive to changes in ambient temperature: a 0.5 ◦ C increase results in 56 % higher melt rates.
Resumo:
We discuss from a practical point of view a number of ssues involved in writing distributed Internet and WWW applications using LP/CLP systems. We describe PiLLoW, a publicdomain Internet and WWW programming library for LP/CLP systems that we have designed in order to simplify the process of writing such applications. PiLLoW provides facilities for accessing documents and code on the WWW; parsing, manipulating and generating HTML and XML structured documents and data; producing HTML forms; writing form handlers and CGI-scripts; and processing HTML/XML templates. An important contribution of PÍ'LLOW is to model HTML/XML code (and, thus, the content of WWW pages) as terms. The PÍ'LLOW library has been developed in the context of the Ciao Prolog system, but it has been adapted to a number of popular LP/CLP systems, supporting most of its functionality. We also describe the use of concurrency and a highlevel model of client-server interaction, Ciao Prolog's active modules, in the context of WWW programming. We propose a solution for client-side downloading and execution of Prolog code, using generic browsers. Finally, we also provide an overview of related work on the topic.
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In recent years, applications in domains such as telecommunications, network security or large scale sensor networks showed the limits of the traditional store-then-process paradigm. In this context, Stream Processing Engines emerged as a candidate solution for all these applications demanding for high processing capacity with low processing latency guarantees. With Stream Processing Engines, data streams are not persisted but rather processed on the fly, producing results continuously. Current Stream Processing Engines, either centralized or distributed, do not scale with the input load due to single-node bottlenecks. Moreover, they are based on static configurations that lead to either under or over-provisioning. This Ph.D. thesis discusses StreamCloud, an elastic paralleldistributed stream processing engine that enables for processing of large data stream volumes. Stream- Cloud minimizes the distribution and parallelization overhead introducing novel techniques that split queries into parallel subqueries and allocate them to independent sets of nodes. Moreover, Stream- Cloud elastic and dynamic load balancing protocols enable for effective adjustment of resources depending on the incoming load. Together with the parallelization and elasticity techniques, Stream- Cloud defines a novel fault tolerance protocol that introduces minimal overhead while providing fast recovery. StreamCloud has been fully implemented and evaluated using several real word applications such as fraud detection applications or network analysis applications. The evaluation, conducted using a cluster with more than 300 cores, demonstrates the large scalability, the elasticity and fault tolerance effectiveness of StreamCloud. Resumen En los útimos años, aplicaciones en dominios tales como telecomunicaciones, seguridad de redes y redes de sensores de gran escala se han encontrado con múltiples limitaciones en el paradigma tradicional de bases de datos. En este contexto, los sistemas de procesamiento de flujos de datos han emergido como solución a estas aplicaciones que demandan una alta capacidad de procesamiento con una baja latencia. En los sistemas de procesamiento de flujos de datos, los datos no se persisten y luego se procesan, en su lugar los datos son procesados al vuelo en memoria produciendo resultados de forma continua. Los actuales sistemas de procesamiento de flujos de datos, tanto los centralizados, como los distribuidos, no escalan respecto a la carga de entrada del sistema debido a un cuello de botella producido por la concentración de flujos de datos completos en nodos individuales. Por otra parte, éstos están basados en configuraciones estáticas lo que conducen a un sobre o bajo aprovisionamiento. Esta tesis doctoral presenta StreamCloud, un sistema elástico paralelo-distribuido para el procesamiento de flujos de datos que es capaz de procesar grandes volúmenes de datos. StreamCloud minimiza el coste de distribución y paralelización por medio de una técnica novedosa la cual particiona las queries en subqueries paralelas repartiéndolas en subconjuntos de nodos independientes. Ademas, Stream- Cloud posee protocolos de elasticidad y equilibrado de carga que permiten una optimización de los recursos dependiendo de la carga del sistema. Unidos a los protocolos de paralelización y elasticidad, StreamCloud define un protocolo de tolerancia a fallos que introduce un coste mínimo mientras que proporciona una rápida recuperación. StreamCloud ha sido implementado y evaluado mediante varias aplicaciones del mundo real tales como aplicaciones de detección de fraude o aplicaciones de análisis del tráfico de red. La evaluación ha sido realizada en un cluster con más de 300 núcleos, demostrando la alta escalabilidad y la efectividad tanto de la elasticidad, como de la tolerancia a fallos de StreamCloud.
Resumo:
Distributed parallel execution systems speed up applications by splitting tasks into processes whose execution is assigned to different receiving nodes in a high-bandwidth network. On the distributing side, a fundamental problem is grouping and scheduling such tasks such that each one involves sufñcient computational cost when compared to the task creation and communication costs and other such practical overheads. On the receiving side, an important issue is to have some assurance of the correctness and characteristics of the code received and also of the kind of load the particular task is going to pose, which can be specified by means of certificates. In this paper we present in a tutorial way a number of general solutions to these problems, and illustrate them through their implementation in the Ciao multi-paradigm language and program development environment. This system includes facilities for parallel and distributed execution, an assertion language for specifying complex programs properties (including safety and resource-related properties), and compile-time and run-time tools for performing automated parallelization and resource control, as well as certification of programs with resource consumption assurances and efñcient checking of such certificates.
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We present an overview of the stack-based memory management techniques that we used in our non-deterministic and-parallel Prolog systems: &-Prolog and DASWAM. We believe that the problems associated with non-deterministic and-parallel systems are more general than those encountered in or-parallel and deterministic and-parallel systems, which can be seen as subsets of this more general case. We develop on the previously proposed "marker scheme", lifting some of the restrictions associated with the selection of goals while keeping (virtual) memory consumption down. We also review some of the other problems associated with the stack-based management scheme, such as handling of forward and backward execution, cut, and roll-backs.
Resumo:
We present the design of a distributed object system for Prolog, based on adding remote execution and distribution capabilities to a previously existing object system. Remote execution brings RPC into a Prolog system, and its semantics is easy to express in terms of well-known Prolog builtins. The final distributed object design features state mobility and user-transparent network behavior. We sketch an implementation which provides distributed garbage collection and some degree of tolerance to network failures. We provide a preliminary study of the overhead of the communication mechanism for some test cases.
Resumo:
This paper describes the current prototype of the distributed CIAO system. It introduces the concepts of "teams" and "active modules" (or active objects), which conveniently encapsulate different types of functionalities desirable from a distributed system, from parallelism for achieving speedup to client-server applications. The user primitives available are presented and their implementation described. This implementation uses attributed variables and, as an example of a communication abstraction, a blackboard that follows the Linda model. Finally, the CIAO WWW interface is also briefly described. The unctionalities of the system are illustrated through examples, using the implemented primitives.
Resumo:
This paper describes the current prototype of the distributed CIAO system. It introduces the concepts of "teams" and "active modules" (or active objects), which conveniently encapsulate different types of functionalities desirable from a distributed system, from parallelism for achieving speedup to client-server applications. It presents the user primitives available and describes their implementation. This implementation uses attributed variables and, as an example of a communication abstraction, a blackboard that follows the Linda model. The functionalities of the system are illustrated through examples, using the implemented primitives. The implementation of most of the primitives is also described in detail.
Resumo:
Accurate characterization of the radio channel in tunnels is of great importance for new signaling and train control communications systems. To model this environment, measurements have been taken at 2.4 GHz in a real environment in Madrid subway. The measurements were carried out with four base station transmitters installed in a 2-km tunnel and using a mobile receiver installed on a standard train. First, with an optimum antenna configuration, all the propagation characteristics of a complex subway environment, including near shadowing, path loss,shadow fading, fast fading, level crossing rate (LCR), and average fade duration (AFD), have been measured and computed. Thereafter, comparisons of propagation characteristics in a double-track tunnel (9.8-m width) and a single-track tunnel (4.8-m width) have been made. Finally, all the measurement results have been shown in a complete table for accurate statistical modeling.