基于遗传算法的容器云资源配置优化

提出一种基于遗传算法的容器云资源配置优化方法。充分考虑虚拟机配置于物理主机以及容器配置于虚拟机的资源分配情况，将容器云平台数据中心整体能耗最低作为目标函数，设置物理主机与虚拟机对应、虚拟机与容器对应等约束条件，利用遗传算法通过染色体表达、初始化、交叉操作、变异操作以及设置适应度函数5个步骤求解目标函数，获取最优容器云环境资源配置结果。实验结果表明，本文方法可实现容器云资源的合理配置，提高物理资源的利用效率，实现数据中心节能的目标。

Optimization of Container Cloud Resource Allocation Based on Genetic Algorithm

This paper proposes a genetic algorithm approach for resource allocation optimization in container-based cloud environment. Considering resource allocation when VMS are configured on physical hosts and containers are configured on VMS, the objective function is to minimize the overall energy consumption of the container cloud platform data center. The machine should correspond to the container and other constraints, and the genetic algorithm is used to solve the objective function through five steps of chromosome expression, initialization, crossover operation, mutation operation and setting fitness function to obtain the optimal virtual resource allocation result. The experimental results show that the proposed method can realize the reasonable allocation of virtual resources in the container cloud environment and keep the energy consumption of the container cloud platform data center to a minimum and achieve the goal of resource efficient utilization.