基于K-means和蝙蝠算法的云计算虚拟机智能调度

Cloud computing virtual machine intelligent scheduling based on K-means and bat algorithm

针对云计算虚拟机调度中存在的资源分配不均衡问题,提出了一种基于K-means和蝙蝠算法的云计算虚拟机智能调度方法。该方法充分考虑物理节点空闲资源和虚拟机所需资源的互补性,以物理节点作为初始聚类中心,使用资源的相关性定义二者的距离,利用蝙蝠算法的全局寻优能力迭代寻优,达到合理调度虚拟机的目的。模拟实验仿真的结果表明,该方法在降低物理节点数量和提高资源利用率方面具有一定的优势,是一种可行的方法。

To solve the resource allocation imbalance problem existing in cloud computing virtual machine scheduling, a cloud computing virtual machine intelligent scheduling method based on K-means and bat algorithm is proposed. The method ful- ly considers the complementarity of the physical node idle resource and the resource needed by virtual machine, selects the physical node as the initial clustering center, and uses the resource correlation to define the distance between them. The global searching ability of bat algorithm is used for iterative optimization to achieve the goal of reasonable virtual machine scheduling. The scheduling method was simulated. The experiment results show that the method has certain advantages in reducing the quan- tity of physieal nodes and improving the resource utilization, and is an effective method.