A grid workflow Quality-of-Service estimation based on resource availability prediction

Accurate estimation of workflow Quality of Service (QoS) enhances the efficiency of scheduling algorithms. The availability and performance variations of Grid computing resources have made this estimation a great challenge. Most workflow QoS estimation algorithms are based on static performance of resources. In this paper, based on resources availability prediction, we propose an algorithm called WQE for estimating the QoS of a Grid workflow. WQE consists of two phases: resource monitoring and analysis and workflow QoS computation. In the first phase, two prediction algorithms are proposed to stochastically predict the availability state of resources. In the second phase, the QoS of each activity is estimated based on the host availability prediction result. The QoS of basic structures is computed by aggregating the QoS of their operands. Using a tree structure corresponding to the workflow, the QoS of basic structures is used to compute the total QoS of the workflow. The simulation results on Notre Dame University trace showed that the proposed method has higher estimation accuracy in comparison with HEFT.

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