A framework for providing hard delay guarantees and user fairness in Grid computing

We present and theoretically and experimentally analyze a Quality of Service (QoS) framework for Grids that provides (i) deterministic delay bounds to Guaranteed Service (GS) users and (ii) fair sharing of resources to Best Effort (BE) users. The framework adopts concepts from Data Networks and applies them in the Grid environment. We initially describe the proposed framework assuming that task computational workloads are known (or can be estimated), and then provide extensions for the more realistic case where we have no a-priori knowledge of the task workloads. Task migration across multiple resources is also examined in this context. We also look at a specific implementation of the proposed QoS scheme, where we distinguish computational resources, based on the type of users (GS or BE) they serve and the priority they give to each type. We validate experimentally the proposed QoS framework for Grids, verifying that it satisfies the delay guarantees promised to GS users and provides fairness among BE users, while simultaneously improving performance in terms of deadlines missed and resource utilization. In our simulations, data from a real Grid Network are used.