Cost-Aware Grid Workflow Resource Allocation

Smart and swift resource allocation is a fundamental issue to accomplish high performance on grid workflow. In this paper, we study the cost-aware grid workflow resource allocation problem based on a market model of grid resource management architectures. We model the problem as the multiple choice knapsack problem (MCKP) and design the resource allocation optimization algorithm to minimize the average turnaround time of the grid workflow. The complexity analysis shows that the optimization algorithm leads to more efficient and appropriate resource allocation than many current algorithms.