the advent of Cloud computing has given to researchers the ability to access resources that satisfy their growing needs, which could not be satisfied by traditional computing resources such as PCs and locally managed ...
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ISBN:
(纸本)9783642328206
the advent of Cloud computing has given to researchers the ability to access resources that satisfy their growing needs, which could not be satisfied by traditional computing resources such as PCs and locally managed clusters. On the other side, such ability, has opened new challenges for the execution of their computational work and the managing of massive amounts of data into resources provided by different private and public infrastructures. COMP Superscalar (COMPSs) is a programming framework that provides a programming model and a runtime that ease the development of applications for distributed environments and their execution on a wide range of computational infrastructures. COMPSs has been recently extended in order to be interoperable with several cloud technologies like Amazon, OpenNebula, Emotive and other OCCI compliant offerings. this paper presents the extensions of this interoperability layer to support the execution of COMPSs applications into the Windows Azure Platform. the framework has been evaluated through the porting of a data mining workflow to COMPSs and the execution on an hybrid testbed.
Flexible and adaptive quality-of-service (QoS) is desirable for distributed real-time applications, such as e-commerce, or multimedia applications. the objective of this research is to dynamically instantiate composit...
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One approach to fully exploit the potential of Cloud technologies consists in leveraging on the Autonomic computing paradigm. It could be exploited in order to put in place reconfiguration strategies spanning the whol...
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ISBN:
(纸本)9783642297373;9783642297366
One approach to fully exploit the potential of Cloud technologies consists in leveraging on the Autonomic computing paradigm. It could be exploited in order to put in place reconfiguration strategies spanning the whole protocol stack, starting from the infrastructure and then going up to platform/application level protocols. On the other hand, the very base for the design and development of Cloud oriented Autonomic Managers is represented by monitoring sub-systems, able to provide audit data related to any layer within the stack. In this article we present the approach that has been taken while designing and implementing the monitoring sub-system for the Cloud-TM FP7 project, which is aimed at realizing a self-adapting, Cloud based middleware platform providing transactional data access to generic customer applications.
Combination of classifiers leads to a substantial reduction of classification errors in a wide range of applications. Among them SVM ensembles with bagging have shown better performance in classification than a single...
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In this paper we consider large scale distributed committee machines where no local data exchange is possible between neural network modules. Regularization neural networks are used for boththe modules as well as the...
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this paper examines the use of .NET's Task parallel Library (TPL) and Windows Communication Foundation (WCF) in finite element analysis. TPL is studied in terms of equation solvers. It is shown that there is no si...
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In light of the challenges of effectively managing Big Data, we are witnessing a gradual shift towards the increasingly popular Linked Open Data (LOD) paradigm. LOD aims to impose a machine-readable semantic layer ove...
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A model decomposition allows transforming a graph-based problem into a set of subproblems to be processed in parallel. Prepared model should guarantee good efficiency of communication and synchronization among agents ...
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Existing Grid monitoring approaches do not combine three desirable features: on-line access to monitoring data, advanced query capabilities and data reduction. We present a solution for on-line monitoring of large-sca...
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ISBN:
(纸本)9783642314995;9783642315008
Existing Grid monitoring approaches do not combine three desirable features: on-line access to monitoring data, advanced query capabilities and data reduction. We present a solution for on-line monitoring of large-scale computing infrastructures based on Complex Event Processing principles and technologies. We focus on leveraging CEP for distributed processing of client queries and monitoring data streams. this results in significant reduction of network traffic due to on-line monitoring. We discuss benefits of CEP-based approach to monitoring and describe details of processing queries in a distributed way. A case study monitoring of load caused by jobs in a Grid infrastructure is presented. Performance evaluation to investigate monitoring overhead in terms of CPU, memory and network traffic is also provided.
this paper discusses lung cancer detection in chest X-ray images with a parallel genetic algorithm (GA). the template matching method and local search techniques are combined to the algorithm and Java Spaces is used t...
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this paper discusses lung cancer detection in chest X-ray images with a parallel genetic algorithm (GA). the template matching method and local search techniques are combined to the algorithm and Java Spaces is used to construct the parallel system. the promising results are presented in the experiments.
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