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Due to the emerging Big Data paradigm, traditional data management techniques result inadequate in many real life scenarios. In particular, the availability of huge amounts of data pertaining to social interactions among users calls for advanced analysis strategies. Furthermore, heterogeneity and high speed of this data require suitable data storage and management tools to be designed from scratch...
The advances in computational techniques both from a software and hardware viewpoint lead to the development of projects whose complexity could be quite challenging, e.g., biomedical simulations. In order to deal with the increased demand of computational power many collaborative approaches have been proposed in order apply proper partitioning strategy able to assign pieces of execution to a crowd...
Nowadays, many applications call for collaborative solutions in order to accomplish complex projects requiring huge amounts of computing resources, e.g., physical science simulation. Many approaches have been proposed in order to design a task partitioning strategy able to assign pieces of execution to the appropriate workers. In this paper, we describe our peer to peer solution for solving complex...
Due to the emerging Big Data applications traditional data management techniques result inadequate in many real life scenarios. In particular, OLAP techniques require substantial changes in order to offer useful analysis due to huge amount of data to be analyzed and their velocity and variety. In this paper, we describe an approach for dynamic Big Data searching that based on data collected by a suitable...
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