基于任务分类的虚拟 CPU 调度模型.

In order to bridge the semantic gap and improve the performance, different scheduling strategies should be applied to virtual CPUs( vCPU ) which execute different types of tasks. Thus, the scheduling of vCPU should be optimized . This paper proposed the STC (virtual CPU scheduler based on task classification), a scheduling model of virtual CPUs which was based on task classification. In STC, vCPUs and physical CPUs were classified into two types, that were short vC PU and long vCPU, which were accordingly mapped to short CPU and long CPU . Moreover, STC built classifier based on machine learning, and tasks were classified into I/0-bound ones and CPU-bound ones, which were allocated to short vCPUs and long vC PUs. STC improved the 110 responding speed without influencing the computing performance. Compared with default CFS algorithm, the experiment results show that STC has achieved time delay 18% decrease, bandwidth 17% - 25% improvement, and ensures the fairness of the whole system. [ABSTRACT FROM AUTHOR]