a mapping algorithm for highly heterogeneous computational grid: a learning automata approach

the computational grid provides a platform for exploiting various computational resources over wide area network.one concern in implementing computational grid environment is how to effectively map tasks onto resources in order to gain high utilization in the highly heterogeneous environment of the grid in this paper a mapping algorithm based on learning automata is proposed the results of experiments show that the proposed algorithm can obtain better performance compared to the two best existing algorithms in high task and machine heterogeneous environments .

کلیدواژه ها:

computational grid ، metatask ، mapping ، learning automata ، heterogeneous computing