Challenges on preserving scientific data with data grids

Abstract

The emerging context of e-Science imposes new scenarios and requirements for digital preservation. In particular, the data must be reliably stored, for which redundancy is a key strategy. But managing redundancy must take into account the potential failure of component. Considering that correlated failures can affect multiple components and potentially cause a complete loss of data, we propose an innovative solution to manage redundancy strategies in heterogeneous environments such as data grids. This solution comprises a simulator that can be used to evaluate redundancy strategies according to preservation requirements and supports the process to design the best architecture to be deployed, which can latter be used as an observer of the deployed system, supporting its monitoring and management.