Multiple Computing Task Scheduling Method Based on Dynamic Data Replication and Hierarchical Strategy

As for the problem of how to carry out task scheduling and data replication effectively in the grid and to reduce task’s execution time, this thesis proposes the task scheduling algorithm and the optimum dynamic data replication algorithm and builds a scheme to effectively combine these two algorithms. First of all, the scheme adopts the ISS algorithm considering the number of tasks waiting queue, the location of task demand data and calculation capacity of site by adopting the method of network structure’s hierarchical scheduling to calculate the cost of comprehensive task with the proper weight efficiency and search out the best compute node area. And then the algorithm of ODHRA is adopted to analyze the data transmission time, memory access latency, waiting copy requests in the queue and the distance between nodes, choose out the best replications location in many copies combined with copy placement and copy management to reduce the file access time. The simulation results show that the proposed scheme compared with other algorithm has better performance in terms of average task execution time.