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Displaying similar documents to “Data intensive scientific analysis with grid computing”

Bringing introspection into BlobSeer: Towards a self-adaptive distributed data management system

Alexandra Carpen-Amarie, Alexandru Costan, Jing Cai, Gabriel Antoniu, Luc Bougé (2011)

International Journal of Applied Mathematics and Computer Science

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Introspection is the prerequisite of autonomic behavior, the first step towards performance improvement and resource usage optimization for large-scale distributed systems. In grid environments, the task of observing the application behavior is assigned to monitoring systems. However, most of them are designed to provide general resource information and do not consider specific information for higher-level services. More precisely, in the context of data-intensive applications, a specific...

Data mining techniques using decision tree model in materialised projection and selection view.

Y. W. Teh (2004)

Mathware and Soft Computing

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With the availability of very large data storage today, redundant data structures are no longer a big issue. However, an intelligent way of managing materialised projection and selection views that can lead to fast access of data is the central issue dealt with in this paper. A set of implementation steps for the data warehouse administrators or decision makers to improve the response time of queries is also defined. The study concludes that both attributes and tuples, are important...

Summarizing sensors data in vehicular ad hoc networks

Dorsaf Zekri, Bruno Defude, Thierry Delot (2010)

RAIRO - Operations Research - Recherche Opérationnelle

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This article focuses on data aggregation in vehicular networks. In such networks, sensor data are usually produced and exchanged between vehicles in order to warn or inform the drivers when an event is detected (, ). In the following, we present a solution to aggregate and store these data in order to have a history of past events. We therefore use Flajolet-Martin sketches. Our goal is to generate additional knowledge to assist drivers by providing them useful information even if no...

Performance evaluation of MapReduce using full virtualisation on a departmental cloud

Horacio González-Vélez, Maryam Kontagora (2011)

International Journal of Applied Mathematics and Computer Science

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This work analyses the performance of Hadoop, an implementation of the MapReduce programming model for distributed parallel computing, executing on a virtualisation environment comprised of 1 + 16 nodes running the VMWare workstation software. A set of experiments using the standard Hadoop benchmarks has been designed in order to determine whether or not significant reductions in the execution time of computations are experienced when using Hadoop on this virtualisation platform on a...