International audienceGrid computing and distributed systems provide great computational power at a low cost. Loosely-coupled parallel applications, such as Bag-of-Tasks applications are well-suited for these heterogeneous systems. A large number of applications could make use of the Bag-of-Tasks approach: data mining, simulations, massive research, image processing, fractal calculations, computational biology. This paper presents a fault-tolerant framework for Bag-of-Tasks applications using the Jini and JavaSpaces technologies. The main goal of this project is to supply a complete and fault tolerant framework that offers a simple interface for bag-of-tasks applications
The Big Data are increasing exponential every year so that data became very complex and difficult to be processed. To resolve this problem, data management and analysis offer opportunities to improve decisions in critical development areas such as: meteorology, medicine, finance, sociology or internet. But, classical statistics programs encounter their limits in processing large data-sets, so that introduction of such programs in non-sql database applications is required. Existing large-scale processing data-sets frameworks does not provide statistics tools to reduce the complexity of the large data-sets to meaningful results. More, nowadays statistics have meanings in context of predictions, forecasting and estimation requiring non-linear regressions to define the complex equations of such systems. Nonlinear regressions offer the best solution for our complex timeseries application where observational data are modeled by nonlinear functions and multiple independent variables. Our analytic application is based on data came from BTWord serial application, that collected public trackers to obtain information about the performance, scalability and reliability of BitTorrent. We show how descriptive, inductive and non-linear regression statistics may be integrated in our map-reduce application to generate statistics about evolution in time of BitTorrent network.
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