基于包簇框架的云计算能耗优化算法

文中针对以虚拟机为中心的云计算分配模式中结构复杂、分配困难等问题,采用了一种基于包簇结构的分配框架。在此基础上提出了一个有效的能耗模型,并将二进制粒子群算法进行改进,通过调节自适应的权重,提高了包簇分配算法的速度和准确性。实验表明,改进的二进制粒子群算法在收敛速度和寻优能力方面更加优于传统的二进制粒子群算法。相较于以虚拟机为中心的分配算法,基于包簇框架下的改进二进制粒子群分配算法提升了CPU使用率,有效降低了能耗,更加绿色节能。

Cloud Computing Energy Consumption Optimization Algorithm Based on Package-Cluster Mapping

ing at the problem of flat layout and complex structure in the virtual machine placement strategy, this paper adopted a virtual machine allocation framework based on package-cluster mapping to minimize the energy consumption of all physical machines. Based on this, an effective energy consumption model and an improved binary particle swarm optimization algorithm with adaptive weights were proposed to improve the speed and accuracy of package-cluster mapping framework. Experimental results showed that the improved binary particle swarm optimization algorithm was more superior to traditional binary particle swarm optimization in terms of convergence speed and optimization ability. Compared with the virtual machine allocation algorithm, the improved binary particle swarm allocation algorithm based on the clustering framework increased the CPU usage and effectively reduced energy consumption, which promoted the green energy saving.