Self-Adaptive Applications on the Grid

Grids are inherently heterogeneous and dynamic. One important problem in grid computing is resource selection, that is, finding an appropriate resource set for the application. Another problem is adaptation to the changing characteristics of the grid environment. Existing solutions to these two problems require that a performance model for an application is known. However, constructing such models is a complex task. In this paper, we investigate an approach that does not require performance models. We start an application on any set of resources. During the application run, we periodically collect the statistics about the application run and deduce application requirements from these statistics. Then, we adjust the resource set to better fit the application needs. This approach allows LIS to avoid performance bottlenecks, such as overloaded WAN links or very slow processors, and therefore can yield significant performance improvements. We evaluate our approach in a number of scenarios typical for the Grid.