Enabling End-to-End Trustworthiness in Data-Oriented Scientific Computing

Data-driven computational science on community computational resources is frequently of a magnitude and scale that it requires that computations be done remotely, generating resulting data collections that are too large to be shipped back to a user’s workstation. Service-oriented middleware is well equipped to carry out actions on behalf of a user, but SOA middleware does not address user trust in the privacy of their actions and security of their data. In this paper we first identify the role of trust in a large distributed computation then develop a model that represents the trust relationship between the users and their remote resources in the Grid system. We show how one can construct a trusted relationship from the model, with an emphasis on the importance of context to a specific trust relationship. We provide a case study of a data-driven scientific application that executed across multiple organizations. Keywords— Data-Oriented Grid Computing, LEAD, Grid Security, Grid Trust