Task scheduling for optimizing recovery time in cloud computing

To achieve high performance, thousands of servers in cloud datacenters coordinate tasks to provide reliable and highly available cloud computing services, especially, in terms of multitasking. Effective mechanisms are now required to prepare for a failure of such computing nodes. A number of studies have been done to address this problem, but it cannot always guarantee an acceptable performance. In this paper, we present a scheduling algorithm, based on cost and bandwidth, which makes efficient recovery possible on heterogeneous computing environments. Our algorithm not only considers the network bandwidth, but also takes into account the monetary cost as well. We justify our proposed work through extensive simulations and compare our work with the existing studies. The results can improve the potential benefit of our approach.