Reduced Task-Resource Assignment Graph based Static scheduling for grid workflow application

The dynamic and heterogeneous nature of grid resources is a great challenge to static scheduling strategies of dependent tasks. Based on the full consideration of dynamics and heterogeneity of grid resources, this paper proposes a reduced task-resource assignment graph based scheduling model and a performance oriented (re)scheduling algorithm is implemented using immune genetic algorithm. The experimentation shows that compared with related works, the proposed scheduling model and algorithm has better adaptability of resource heterogeneity and dynamic, and obtains better performance because of the objective consistency, and immune genetic algorithmpsilas contribution on global optimization.