Rejuvenation is a technique expected to mitigate failures in HPC systems by replacing, repairing, or resetting system components. Because of the small overhead required by software rejuvenation, we primarily focus on ...
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Grids are typically used for solving large-scale resource and computing intensive problems in science, engineering, and commerce as they seem to be cost-effective for industrial users. In order to be able to meet this...
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ISBN:
(纸本)0780390741
Grids are typically used for solving large-scale resource and computing intensive problems in science, engineering, and commerce as they seem to be cost-effective for industrial users. In order to be able to meet this requirement the software modules developed should be designed to meet the requisites for commercial business processes on the Grid. In this paper we present a module for predicting computational workload of jobs assigned for execution on commercially exploited Grid infrastructures. The module aims to identify the complexity of a given job and predict the workload that it is going to stress on the Grid infrastructure. The prediction is achieved with the use of a trained Artificial Neural Network which has been implemented with the use of the open source software package Joone. The approach has been implemented and validated within the framework of GRIA IST project for a specific industrial based application namely, 3D image rendering. The evaluation of the approach showed very promising results not only for the adoption of an open source package in a commercial application but also concerning the accuracy of the prediction and the benefit that it can provide in Grids for business.
Arbitrarily divisible workloads are present in a large class of scientific applications, such as N-body simulations, Monte Carlo simulations, CFD applications, and others. Divisible load theory (DLT) provides a tracta...
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With a camera mobile phone, which has become a, "must-have" device, 2D-barcode works as an interface to bridge the physical and digital world. As the notion of ubiquitous computing has permeated, developing ...
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ISBN:
(纸本)9780769534718
With a camera mobile phone, which has become a, "must-have" device, 2D-barcode works as an interface to bridge the physical and digital world. As the notion of ubiquitous computing has permeated, developing a new 2D-barcode and its applications has been a growing trend worldwide. A 2D-barcode symbol consists of two broad areas: data area and guide area. The components of the latter is collectively called "finder pattern" and used in locating the 2D-barcode symbol. The failure of finding the target symbol prevents a barcode reader from successfully decoding the barcode. Hence, designing a functional finder pattern is Me of the key for improving the robustness of barcode reading, and thus, the entire 2D-barcode system. We have designed a novel finder pattern integrated with a color 2D-barcode for camera mobile phone applications. Through the development and evaluation of the finder pattern for effective color 2D-barcode detection, this paper discusses keys to improve the functionality and reliability of finder patterns, which should be kept in mind when designing a finder pattern for any 2D-barcode symbol.
Hadoop-stock is a reliable, scalable, and open source implementation of the MapReduce framework to process data-intensive applications in a distributed and parallel environment. In a common environment between multipl...
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It is useful for researcher to predict amount of general program supported by NSFC. This paper explores the history data of amount of general program supported by NSFC, builds a regression equation of general program ...
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It is useful for researcher to predict amount of general program supported by NSFC. This paper explores the history data of amount of general program supported by NSFC, builds a regression equation of general program amount, analyses regression parameters by employing variance analysis method, and obtains predicting amount domain of general program supported by NSFC. The result of example shows the predicting accuracy is over 98%.
Hamid Mcheick is currently an associate professor in computer science department at the University of Quebec AtChicoutimi (UQAC), Quebec, Canada. He holds a PhD degree in software engineering and distributed system fr...
Hamid Mcheick is currently an associate professor in computer science department at the University of Quebec At
Chicoutimi (UQAC), Quebec, Canada. He holds a PhD degree in software engineering and distributed system from
Montreal University, Canada. He holds a master degree from the University of Quebec at Montreal, Canada in information
retrieval system. Professor Mcheick is interested in distributed software architecture, mobiles applications and
pervasive computing, as well as in separation of concerns (component, services, aspect, etc.). He works also in ubiquitous
computing, service composition of business process. He has given many talks in congresses and conferences as a
keynote or invited speaker. He is a chief in editor and guest editor of several international journals. His research is
supported by many research grants he has received from the Canadian government, University of Montreal, CRIM
(Centre de Recherche informatique de Montreal), University of UQAM, and University of Quebec At Chicoutimi,
Canada.
The missions of Bentham Journal volume aim to bring, for both academics as well as for industrial practitioners, a set
of articles discussing and answering the recent patents on core topics of software computing and intelligence and improving
the state-of-the-art of worldwide research in the areas of computer science issues by publishing high-quality articles
in this area, and by exposing the readers to various methodologies, tools, technologies, algorithms, results, and types of
articles.
It is our pleasure to highlight in June 2014, the 7th volume of the Journal Recent Patents on Computer science (CSENG)
that includes a selected and reviewed research papers. This issue includes papers of Software Defined Networks for Data
Center Optimization, Intelligent techniques and systems in credit risk analysis and forecasting, Cultivating Software Solutions
Development in the Scientific Academia, Information Security and Threats in Mobile Appli
A distributed, real-time, collaborative visualization (DRCV) system for four dimensional datasets like fMRI images, can be a valuable tool to support scientific and medical research. Software applications supporting D...
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Modern software engineering is getting increasingly complicated. Especially in the HPC field, we are dealing with cutting edge infrastructure and a novel problem with unprecedented scale. The ability to monitor and an...
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ISBN:
(纸本)9781450391993
Modern software engineering is getting increasingly complicated. Especially in the HPC field, we are dealing with cutting edge infrastructure and a novel problem with unprecedented scale. The ability to monitor and analyze the performance of such applications and infrastructure is imperative for the future of improvement, design, and maintenance. In the current era, the writing and maintenance of these applications have ceased to be the job solely of computer scientists and has grown to encompass a wide variety of experts in mathematics, science, and other engineering disciplines. The fact that many developers from these disciplines have not received a formal education in computer science and rely increasingly on the tools created by computer scientists to analyze and optimize their code shows that there's a need for a forum to work together.
The k-means clustering algorithm is a widely used scheme to solve the clustering problem which classifies a given set of n data points in m-dimensional space into k clusters, whose centers are obtained by the centroid...
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