Job scheduling for grid computing on metacomputers

Scheduling is a fundamental issue in achieving high performance on metacomputers and computational grids. For the first time, the job scheduling problem for grid computing on metacomputers is studied as a combinatorial optimization problem. It is proven that the list scheduling algorithm can achieve reasonable worst-case performance bound in grid environments supporting distributed super computing with large applications. It is also observed that communication heterogeneity does have significant impact on schedule lengths.