满足工作流执行时限的可抢占虚拟机实例配置和调度方法研究

随着云计算的迅速发展，将工作流部署到云计算平台已经成为了常见的选择。相比于传统的本地工作流，云工作流不仅要考虑计算时长等要求，还要考虑其产生的经济开销。而云计算服务商为了提高资源利用率，提供了可抢占虚拟机实例这种非常廉价但是不稳定的资源。针对工作流在云计算中的调度和执行问题，提出一种满足工作流执行时限的可抢占虚拟机实例配置和调度方法。该方法使用马尔科夫模型和动态规划方法，对可抢占虚拟机实例的价格进行预测，并得到成本最低的出价策略。同时，结合工作流的执行时限要求，在估计的出价策略下对工作流中使用的实例进行配置。实验结果显示，相比于全部使用按需付费虚拟机实例，该方法在满足工作流执行时限的前提下最高可以节省89.9%的计算成本。

Configuration and scheduling mechanism of spotinstances meeting the execution time limit of workflow

With the development of cloud computing, deploying workflows onto cloud computing platforms has become a popular choice. Compared with the traditional local workflow, cloud workflow not only needs to consider the requirements such as the execution time, but also considers the economic cost. In order to improve the resource utilization, cloud computing service providers provide spot instances, which are very cheap but unstable. Aiming at the problem of workflow scheduling and execution in cloud computing, this paper proposes a spot instance configuration and scheduling method that meets the workflow execution time budget. This method uses Markov models and dynamic programming methods to predict the price of spot instances and obtain the lowest cost bid strategy. At the same time, to satisfy the execution time budget of the workflow, the instances used in the workflow are configured under the estimated bid strategy. Experimental results show that, compared with using on demand instances, our method can save up to 89.9% computation cost, while meeting the workflow execution time budget.