We recently focused on two problems:
Data cube queries represent an important class of On-Line Analytical Processing (OLAP) queries in decision support systems. They consist in a pre-computation of the different group-bys of a database (aggregation for every combination of GROUP BY attributes) that is a very consuming task. For instance, databases of some megabytes may lead to the construction of a datacube requiring terabytes of memory  and parallel computation has been proposed but for a static and well-identified platform  . This application is typically an interesting example for which the distributed computation and storage can be useful in an heterogeneous and dynamic setting. We just started a collaboration with Sofian Maabout (Assistant Professor in Bordeaux) and Noel Novelli (Assistant Professor of Marseille University) who is a specialist of datacube computation. Our goal is to rely on the set of services defined in Section 6.2.2 to compute and maintain huge datacubes. For the moment, we developped a centralized tool that sums up an whole datacube until dimension 20 and that outperforms usual data cube reduction scheme.
Some work is required to share our tool to a wide public. We plan to do it within the next two years.