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Opportunistic computational grids use idle resources from shared machines to execute applications that need large amounts of computational power and/or deal with large amounts of data. But executing computationally intensive parallel applications in dynamic and heterogeneous environments, such as opportunistic grids, is a daunting task. Machines may fail, become inaccessible, or change from idle to occupied unexpectedly, compromising the application execution. A fault tolerance mechanism that supports heterogeneous architectures is an important requisite for such systems. In this work, we analyze, implement and evaluate a checkpointing-based fault tolerance mechanism for parallel applications running on opportunistic grids. The mechanism monitors application execution and allows the migration of applications between heterogeneous nodes of the grid. But besides application execution, it is necessary to manage data generated and used by those applications. We want a low cost data storage infrastructure that utilizes the unused disk space of grid shared machines. The system should use the machines to store and recover data only during their idle periods, requiring the system to be redundant and fault-tolerant. To solve the data storage problem in opportunistic grids, we designed, implemented and evaluated the OppStore middleware. This middleware provides reliable distributed storage for application data, which can be accessed from any machine in the grid. The machines are organized in clusters, connected by a self-organizing and fault-tolerant peer-to-peer network. During storage, data is codified into redundant fragments, allowing the reconstruction of the original file using only a subset of those fragments. Finally, to deal with resource heterogeneity, we developed an extension to the Pastry peer-to-peer routing substrate, enabling heterogeneity-aware load-balancing message routing.

"Armazenamento distribuído de dados e checkpointing de aplicações paralelas em grades oportunistas"