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Big Data, Beyond the Data Center
Increasingly the next scientific discoveries and the next industrial innovative breakthroughs will depend on the capacity to extract knowledge and sense from gigantic amount of information. Examples vary from processing data provided by scientific instruments such as the CERN’s LHC; collecting data from large-scale sensor networks; grabbing, indexing and nearly instantaneously mining and searching the Web; building and traversing the billion-edges social network graphs; anticipating market and customer trends through multiple channels of information. Collecting information from various sources, recognizing patterns and distilling insights constitutes what is called the Big Data challenge. However, As the volume of data grows exponentially, the management of these data becomes more complex in proportion. A key challenge is to handle the complexity of data management on Hybrid distributed infrastructures, i.e assemblage of Cloud, Grid or Desktop Grids. In this talk, I will overview our works in this research area; starting with BitDew, a middleware for large scale data management on Clouds and Desktop Grids. Then I will present our approach to enable MapReduce on Desktop Grids. Finally, I will present our latest results around Active Data, a programming model for managing data life cycle on heterogeneous systems and infrastructures.