65 resultados para Distributed systems

em Repositório Institucional UNESP - Universidade Estadual Paulista "Julio de Mesquita Filho"


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Predictability is related to the uncertainty in the outcome of future events during the evolution of the state of a system. The cluster weighted modeling (CWM) is interpreted as a tool to detect such an uncertainty and used it in spatially distributed systems. As such, the simple prediction algorithm in conjunction with the CWM forms a powerful set of methods to relate predictability and dimension.

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In large distributed systems, where shared resources are owned by distinct entities, there is a need to reflect resource ownership in resource allocation. An appropriate resource management system should guarantee that resource's owners have access to a share of resources proportional to the share they provide. In order to achieve that some policies can be used for revoking access to resources currently used by other users. In this paper, a scheduling policy based in the concept of distributed ownership is introduced called Owner Share Enforcement Policy (OSEP). OSEP goal is to guarantee that owner do not have their jobs postponed for longer periods of time. We evaluate the results achieved with the application of this policy using metrics that describe policy violation, loss of capacity, policy cost and user satisfaction in environments with and without job checkpointing. We also evaluate and compare the OSEP policy with the Fair-Share policy, and from these results it is possible to capture the trade-offs from different ways to achieve fairness based on the user satisfaction. © 2009 IEEE.

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Simulation of large and complex systems, such as computing grids, is a difficult task. Current simulators, despite providing accurate results, are significantly hard to use. They usually demand a strong knowledge of programming, what is not a standard pattern in today's users of grids and high performance computing. The need for computer expertise prevents these users from simulating how the environment will respond to their applications, what may imply in large loss of efficiency, wasting precious computational resources. In this paper we introduce iSPD, iconic Simulator of Parallel and Distributed Systems, which is a simulator where grid models are produced through an iconic interface. We describe the simulator and its intermediate model languages. Results presented here provide an insight in its easy-of-use and accuracy.

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Digital image processing is a field that demands great processing capacity. As such it becomes relevant to implement software that is based on the distribution of the processing into several nodes divided by computers belonging to the same network. Specifically discussed in this work are distributed algorithms of compression and expansion of images using the discrete cosine transform. The results show that the savings in processing time obtained due to the parallel algorithms in comparison to its sequential equivalents is a function that depends on the resolution of the image and the complexity of the involved calculation; that is efficiency is greater the longer the processing period is in terms of the time involved for the communication between the network points.

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Although cluster environments have an enormous potential processing power, real applications that take advantage of this power remain an elusive goal. This is due, in part, to the lack of understanding about the characteristics of the applications best suited for these environments. This paper focuses on Master/Slave applications for large heterogeneous clusters. It defines application, cluster and execution models to derive an analytic expression for the execution time. It defines speedup and derives speedup bounds based on the inherent parallelism of the application and the aggregated computing power of the cluster. The paper derives an analytical expression for efficiency and uses it to define scalability of the algorithm-cluster combination based on the isoefficiency metric. Furthermore, the paper establishes necessary and sufficient conditions for an algorithm-cluster combination to be scalable which are easy to verify and use in practice. Finally, it covers the impact of network contention as the number of processors grow. (C) 2007 Elsevier B.V. All rights reserved.

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Increased accessibility to high-performance computing resources has created a demand for user support through performance evaluation tools like the iSPD (iconic Simulator for Parallel and Distributed systems), a simulator based on iconic modelling for distributed environments such as computer grids. It was developed to make it easier for general users to create their grid models, including allocation and scheduling algorithms. This paper describes how schedulers are managed by iSPD and how users can easily adopt the scheduling policy that improves the system being simulated. A thorough description of iSPD is given, detailing its scheduler manager. Some comparisons between iSPD and Simgrid simulations, including runs of the simulated environment in a real cluster, are also presented. © 2012 IEEE.

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Pós-graduação em Engenharia Elétrica - FEIS

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Pós-graduação em Ciência da Computação - IBILCE

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Fundação de Amparo à Pesquisa do Estado de São Paulo (FAPESP)

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Coordenação de Aperfeiçoamento de Pessoal de Nível Superior (CAPES)

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Conselho Nacional de Desenvolvimento Científico e Tecnológico (CNPq)

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This work presents a study about the use of standards and directions on parallel programming in distributed systems, using the MPI standard and PETSc toolkit, performing an analysis of their performances over certain mathematic operations involving matrices. The concepts are used to develop applications to solve problems involving Principal Components Analysis (PCA), which are executed in a Beowulf cluster. The results are compared to the ones of an analogous application with sequencial execution, and then it is analized if there was any performance boost on the parallel application

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In this paper an efficient algorithm for probabilistic analysis of unbalanced three-phase weakly-meshed distribution systems is presented. This algorithm uses the technique of Two-Point Estimate Method for calculating the probabilistic behavior of the system random variables. Additionally, the deterministic analysis of the state variables is performed by means of a Compensation-Based Radial Load Flow (CBRLF). Such load flow efficiently exploits the topological characteristics of the network. To deal with distributed generation, a strategy to incorporate a simplified model of a generator in the CBRLF is proposed. Thus, depending on the type of control and generator operation conditions, the node with distributed generation can be modeled either as a PV or PQ node. To validate the efficiency of the proposed algorithm, the IEEE 37 bus test system is used. The probabilistic results are compared with those obtained using the Monte Carlo method.

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In this paper, we introduce a DAI approach called hereinafter Fuzzy Distributed Artificial Intelligence (FDAI). Through the use of fuzzy logic, we have been able to develop mechanisms that we feel may effectively improve current DAI systems, giving much more flexibility and providing the subsidies which a formal theory can bring. The appropriateness of the FDAI approach is explored in an important application, a fuzzy distributed traffic-light control system, where we have been able to aggregate and study several issues concerned with fuzzy and distributed artificial intelligence. We also present a number of current research directions necessary to develop the FDAI approach more fully.