To address the issue of resource co-allocation with constraints to budget and deadline in grid environments, a novel co-allocation model based on virtual resource agent was proposed. The model optimized resources depl...To address the issue of resource co-allocation with constraints to budget and deadline in grid environments, a novel co-allocation model based on virtual resource agent was proposed. The model optimized resources deployment and price scheme through a three-side co-allocation mechanism, and applied queuing system to model the work of grid resources for providing quantitative deadline guarantees for grid applications. The validity and solutions of the model were presented theoretically. Extensive simulations were conducted to examine the effectiveness and the performance of the model by comparing with other co-allocation policies in terms of deadline violation rate, resource benefit and resource utilization. Experimental results show that compared with the three typical co-allocation policies, the proposed model can reduce the deadline violation rate to about 3.5% for the grid applications with constraints to budget and deadline. Also, the system benefits can be increased by about 30% compared with the those widely-used co-allocation policies.展开更多
基金Project(60673165) supported by the National Natural Science Foundation of China
文摘To address the issue of resource co-allocation with constraints to budget and deadline in grid environments, a novel co-allocation model based on virtual resource agent was proposed. The model optimized resources deployment and price scheme through a three-side co-allocation mechanism, and applied queuing system to model the work of grid resources for providing quantitative deadline guarantees for grid applications. The validity and solutions of the model were presented theoretically. Extensive simulations were conducted to examine the effectiveness and the performance of the model by comparing with other co-allocation policies in terms of deadline violation rate, resource benefit and resource utilization. Experimental results show that compared with the three typical co-allocation policies, the proposed model can reduce the deadline violation rate to about 3.5% for the grid applications with constraints to budget and deadline. Also, the system benefits can be increased by about 30% compared with the those widely-used co-allocation policies.
