A scheduling algorithm aimed at time and cost for meta-tasks in grid computing using fuzzy applicability

In this paper, a novel concept is proposed to express the matching degree between available resources and meta-tasks which uses weighted average fuzzy applicability. Furthermore, a new scheduling algorithm aimed at time and cost for meta-tasks in grid computing is designed on the basis of layered task scheduling model. The scheduling aim can be chosen according to user's requirement through setting different weights, for example, Time-Weight, Cost-Weight, etc. The comparison metric is the value of fuzzy applicability, and the optimum solution is the scheme which has the maximum. The experiment result shows that the algorithm can consider the factors of time and cost as a whole. It also ensures that, given the aim with different weights, the algorithm's performance is better than some existent heuristic algorithms.