A benefit function mapping heuristic for a class of meta-tasks in grid environments

The Computational Grid is an appealing high performance computational platform. Problem in implementing Computational Grid environment is how to effectively use various resources in the system, such as compute cycle, memory, communication network, and data repositories. A benefit function resource mapping heuristic for Computational Grid environments is presented to map a set of independent tasks (Meta-task) to resources. The algorithm considers the influence of input data repositories´ location and QOS of tasks to result of mapping. This semi-dynamic algorithm is more suitable for the dynamic adaptability and domain autonomy in the grid, and the benefit function heuristic adopted in the algorithm can assure the QOS of tasks more effectively