A quality-driven algorithm for task scheduling in grid market
网格市场中服务质量驱动下的任务调度算法

We propose a quality-driven algorithm for task scheduling in grid market, which is deadline- and budget-constrained and maximizes number of completed tasks (DBCN). This algorithm combines the high throughput advantage of Min-min algorithm and the global optimization advantage of linear programming. Meanwhile the algorithm considers not only all the tasks but also those prior ones. Compared with the Min-min and DBCT classical algorithms, DBCN completes about 10.6% and 22.0% more tasks and about 20% and 40% more prior tasks, respectively.