Evaluating the Reliability of Large-Scale Heterogeneous Grid Computing Systems in Dynamic Workload Environments

With the increasing scale of grid systems, reliability evaluation for both grid systems and applications become more and more challenging, especially when taking the heterogeneity and dynamical workload into consideration. In this work, a workload-aware reliability evaluation model is proposed, in which queuing system is applied to describe the dynamic workload and working of grid resources. To supporting deadline-sensitive applications, a new class of resource fault, namely Deadline-Miss fault, is introduced to evaluate the reliability of these applications. The validity of the proposed model and its approach to calculate deadline-sensitive job’s reliability are presented theoretically. Extensive experiments are conducted to verify its performance, and the results show that the proposed model can significantly improve the accuracy of reliability evaluation in presence of dynamic workload. Also, scheduling algorithm based on this model can reduce mean response time and the deadline-miss rate for deadline-sensitive grid applications.