A Grid Scheduling Optimization Strategy Based on Fuzzy Multi-Attribute Group Decision-Making

In grid environments, the grid scheduling technique is more complex than the conventional ones in high performance computing system, and grid scheduling is one of the major factors that would affect the grid performance. In order to optimize grid scheduling, we have to consider the various factors. By combining the analysis and prediction methods that are of different principles and approaches, we would be able to make comprehensive decisions on different scenarios and provide reference for scheduling optimization. In this paper, a method of fuzzy multi-attribute group decision-making is proposed, which introduces fuzzy set and its operations into decision-making process, and reflects a group or collective ranking of alternatives based on the individual preferences of those alternatives. The flexible selection models heighten the expressive force and adaptability greatly. The experiments show that the grid scheduling with this method has high performance.

It should be pointed out that the decision-making approach in this paper is built on the compensability between the decision attributes. But in some cases, the compensability between the decision attributes is conditional, and even non-compensable. Therefore, the other comprehensive decision-making approaches are needed for these features. These approaches will be our further research focus.