Classified Optimization Scheduling Algorithm Driven by Multi-QoS Attributes in Economical Grid

It is because the resources are geographic distributed, heterogeneous and dynamic in computational grid environments that makes QoS guided scheduling a complex and challenging problem, especially when the tasks have multiple QoS needs. The economic model was applied to solve the resource allocation problem controlled by QoS in grid. Integration function is used to quantitative QoS, which aims to achieve high system utilization. A classified optimization scheduling algorithm for a set of independent tasks under the limitation of time and cost is proposed which can satisfy the multi-QoS attributes effectively. The results of the simulation in virtual grid environment show that our algorithm can well tradeoff the actual executing cost and its budget in grid economy model.