Managing Service Levels in Grid Computing Systems Quota Policy and Computational Market Approaches

We study techniques to enforce and provision differentiated service levels in Computational Grid systems. The Grid offers simplified provisioning of peak-capacity for applications with computational requirements beyond local machines and clusters, by sharing resources across organizational boundaries. Current systems have focussed on access control, i.e., managing who is allowed to run applications on remote sites. Very little work has been done on providing differentiated service levels for those applications that are admitted. This leads to a number of problems when scheduling jobs in a fair and efficient way. For example, users with a large number of long-running jobs could starve out others, both intentionally and non-intentionally. We investigate the requirements of High Performance Computing (HPC) applications that run in academic Grid systems, and propose two models of service-level management. Our first model is based on global real-time quota enforcement, where projects are granted resource quota, such as CPU hours, across the Grid by a centralized allocation authority. We implement the SweGrid Accounting System to enforce quota allocated by the Swedish National Allocations Committee in the SweGrid production Grid, which connects six Swedish HPC centers. A flexible authorization policy framework allows provisioning and enforcement of two different service levels across the SweGrid clusters; high-priority and low-priority jobs. As a solution to more fine-grained control over service levels we propose and implement a Grid Market system, using a market-based resource allocator called Tycoon. The conclusion of our research is that although the Grid accounting solution offers better service level enforcement support than state-of-the-art production Grid systems, it turned out to be complex to set the resource price and other policies manually, while ensuring fairness and efficiency of the system. Our Grid Market on the other hand sets the price according to the dynamic demand, and it is further incentive compatible, in that the overall system state remains healthy even in the presence of strategic users.