On the Cost of Reliability in Large Data Grids

Global grid environments do not only provide massive aggregated computing power but also an unprecedented amount of distributed storage space. Unfortunately, dynamic changes caused by component failures, local decisions, and irregular data updates make it difficult to efficiently use this capacity. In this paper, we address the problem of improving data availability in the presence of unreliable components. We present an analytical model for determining an optimal combination of distributed replica catalogs, catalog sizes, and replica servers. Empirical simulation results confirm the accuracy of our theoretical analysis. Our model captures the characteristics of highly dynamic environments like peer-to-peer networks, but it can also be applied to more centralized, less dynamic grid environments like the European DataGrid.