Research on task scheduling algorithms of grid computing based on multipled QoS constrain and genetic algorithms

In grid computing, task scheduling is a NP-Hard question. Currently most of the existing algorithms cannot combine multiple QoS constrains with genetic algorithms to improve the user satisfaction. In this paper we propose a resource scheduling model based on multiple QoS constrains. A model of satisfaction optimization is introduced to seek the satisfactory goal, based on which a MQoS-Genetic-Algorithm is employed as the scheduling algorithm. The experimental results illustrated that our algorithm outperforms in the aspects of efficiency and user satisfaction.