Implementing effective data management policies in distributed and grid computing environments

A common programming model in distributed and grid computing is the client/server paradigm, where the client submits requests to several geographically remote servers for executing already deployed applications on its own data. In this context it is mandatory to avoid unnecessary data transfer because the data set can be very large. This work addresses the problem of implementing a strategy for data management in case of data dependencies among subproblems in the same application. To this purpose, some minor changes have been introduced to the Distributed Storage Infrastructure in NetSolve distributed computing environment.