In this paper, we present the design of Aneka, a .NET based service-oriented platform for desktop grid computing that provides: (i) a configurable service container hosting pluggable services for discovering, scheduli...
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In this paper, we present the design of Aneka, a .NET based service-oriented platform for desktop grid computing that provides: (i) a configurable service container hosting pluggable services for discovering, scheduling and balancing various types of workloads and (ii) a flexible and extensible framework/API supporting various programming models including threading, batch processing, MPI and dataflow. Users and developers can easily use different programming models and the services provided by the container to run their applications over desktop Grids managed by Aneka. We present the implementation of both the essential and advanced services within the platform. We evaluate the system with applications using the grid task and dataflow models on top of the infrastructure and conclude with some future directions of the current system.
This paper proposes a new approach for the optimization process of the interval addition and multiplication floating point units. For the interval addition/subtraction, an adder exploiting the parallelism of the doubl...
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This paper proposes a new approach for the optimization process of the interval addition and multiplication floating point units. For the interval addition/subtraction, an adder exploiting the parallelism of the double path adder structure is used. The two floating point additions needed are performed simultaneously on different data paths. Therefore, the performance of the proposed adder can be the same as that of two individual floating point adders, but with a much reduced cost overhead. Regarding the interval multiplication, a multiplier architecture was designed, in order to be suitable for pipelined structures. It consists of a floating point multiplier which computes two results for the same operation (rounded differently), and of two floating point comparators. In terms of performance, the proposed multiplier unit presents half of the performance of a conventional floating point multiplier. This is not a drawback, if we consider the fact that interval multiplication requires four floating point operations and six comparisons. This paper shows that interval arithmetic can be efficiently implemented in terms of performance and cost.
Utility computing has been anticipated to be the next generation of computing usage. Users have the freedom to easily switch to any commercial computing service to complete jobs whenever the need arises and simply pay...
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Utility computing has been anticipated to be the next generation of computing usage. Users have the freedom to easily switch to any commercial computing service to complete jobs whenever the need arises and simply pay only on usage, without any investment costs. A commercial computing service however has certain objectives or goals that it aims to achieve. In this paper, we identify three essential objectives for a commercial computing service: (i) meet SLA, (ii) maintain reliability, and (iii) earn profit. This leads to the problem of whether a resource management policy implemented in the commercial computing service is able to meet the required objectives or not. So, we also develop two evaluation methods that are simple and intuitive: (i) separate and (ii) integrated risk analysis to analyze the effectiveness of resource management policies in achieving the required objectives. Evaluation results based on five policies successfully demonstrate the applicability of separate and integrated risk analysis to assess policies in terms of the required objectives.
This paper presents a recursive clustering scheme that uses a genetic algorithm-based search in a dichotomous partition space. The proposed algorithm makes no assumption on the number of clusters present in the datase...
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This paper presents a recursive clustering scheme that uses a genetic algorithm-based search in a dichotomous partition space. The proposed algorithm makes no assumption on the number of clusters present in the dataset; instead it recursively uncovers subsets in the data until all isolated and separated regions have been classified as clusters. A test of spatial randomness serves as a termination criteria for the recursive process. Within each recursive step, a genetic algorithm searches the partition space for an optimal dichotomy of the dataset. A simple binary representation is used for the genetic algorithm, along with classical selection, crossover and mutation operators. Results of clustering on test cases, ranging from simple datasets in 2-D to large multidimensional datasets compare favorably with state of the art approaches in genetic algorithm-driven clustering.
Effective scheduling is a key concern for the execution of performance driven grid applications. In this paper, we propose a dynamic critical path (DCP) based workflow scheduling algorithm that determines efficient ma...
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Effective scheduling is a key concern for the execution of performance driven grid applications. In this paper, we propose a dynamic critical path (DCP) based workflow scheduling algorithm that determines efficient mapping of tasks by calculating the critical path in the workflow task graph at every step. It assigns priority to a task in the critical path which is estimated to complete earlier. Using simulation, we have compared the performance of our proposed approach with other existing heuristic and meta-heuristic based scheduling strategies for different type and size of workflows. Our results demonstrate that DCP based approach can generate better schedule for most of the type of workflows irrespective of their size particularly when resource availability changes frequently.
This paper presents a quantum algorithm for minimizing both exclusive-or sum of complex terms (ESCT) and exclusive-or sum of products (ESOP) expressions. The proposed algorithm, QMin, takes advantage of the inherent m...
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ISBN:
(纸本)9780769528960;0769528961
This paper presents a quantum algorithm for minimizing both exclusive-or sum of complex terms (ESCT) and exclusive-or sum of products (ESOP) expressions. The proposed algorithm, QMin, takes advantage of the inherent massive parallelism of quantum circuits. The ESCT expressions produced by QMin are presented in the related bibliography as an attractive architecture for implementing reversible and quantum circuits.
This paper describes a new approach to finding a global solution for the fuzzy least trimmed squares clustering. The least trimmed squares (LTS) estimator is known to be a high breakdown estimator, in both regression ...
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This paper describes a new approach to finding a global solution for the fuzzy least trimmed squares clustering. The least trimmed squares (LTS) estimator is known to be a high breakdown estimator, in both regression and clustering. From the point of view of implementation, the feasible solution algorithm is one of the few known techniques that guarantees a global solution for the LTS estimator. The feasible solution algorithm divides a noisy data set into two parts -the non-noisy retained set and the noisy trimmed set, by implementing a pairwise swap of datum between the two sets until a least squares estimator provides the best fit on the retained set. We present a novel genetic algorithm-based implementation of the feasible solution algorithm for fuzzy least trimmed squares clustering, and also substantiate the efficacy of our method by three examples.
Decision trees (DTs) provide an attractive classification scheme because clinicians responsible for making reliable decisions can easily interpret them. Bayesian averaging over DTs allows clinicians to evaluate the cl...
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Decision trees (DTs) provide an attractive classification scheme because clinicians responsible for making reliable decisions can easily interpret them. Bayesian averaging over DTs allows clinicians to evaluate the class posterior distribution and therefore to estimate the risk of making misleading decisions. The use of Markov chain Monte Carlo (MCMC) methodology of stochastic sampling makes the Bayesian DT technique feasible to perform. The Reversible Jump (RJ) extension of MCMC allows sampling from DTs of different sizes. However, the RJ MCMC process may become stuck in a particular DT far away from the region with maximal posterior. This negative effect can be mitigated by averaging the DTs obtained in different starts. In this paper we describe a new approach based on an adaptive sampling scheme. The performances of Bayesian DT techniques with the restarting and adaptive strategies are compared on a synthetic dataset as well as on some medical datasets. By quantitatively evaluating the classification uncertainty, we found that the adaptive strategy is superior to the restarting strategy.
In this paper,based on the multi-symplecticity of concatenating symplectic Runge-Kutta-Nystrom(SRKN)methods and symplectic Runge-Kutta-type methods for numerically solving Hamiltonian PDEs,explicit multi-symplectic sc...
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In this paper,based on the multi-symplecticity of concatenating symplectic Runge-Kutta-Nystrom(SRKN)methods and symplectic Runge-Kutta-type methods for numerically solving Hamiltonian PDEs,explicit multi-symplectic schemes are constructed and investigated,where the nonlinear wave equation is taken as a model *** comparisons are made to illustrate the effectiveness of our newly derived explicit multi-symplectic integrators.
Motivation - To improve the current practice of scenario-based usability evaluation by suggesting a new method for generating more comprehensive scenarios and using the scenarios more easily and systematically. Resear...
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ISBN:
(纸本)9781847998491
Motivation - To improve the current practice of scenario-based usability evaluation by suggesting a new method for generating more comprehensive scenarios and using the scenarios more easily and systematically. Research approach - Work domain analysis (WDA) concept in cognitive work analysis (CWA) framework was employed to develop a method for identifying functions and their relationships, which need to be reflected in scenarios. Two methodological tools were developed to help evaluators analyze functional structure and generate meaningful scenarios respectively. Findings/Design - A new method for generating and using scenarios was developed, which accompanies two new tools (function-control matrix and function order diagram). Research limitations/Implications - As the method was applied to only one word processing software, there is a lack of case studies;however, the method has features that may be generalized to other kinds of software. Originality/Value - This research contributes to making a scenario-based evaluation process more systematic by supplementing its current weak points. Also this research applied abstraction hierarchy concept to software systems to which little attention has been given. Take away message - Scenario-based usability evaluation can be enriched with the use of abstraction-based functional structure of software.
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