基于改进遗传算法的云仿真资源分配算法

Genetic Algorithm based Mapping Scheme for Dynamic Construction in Cloud Simulation Environments

近年来,云仿真技术作为一种新型网络化建模与仿真模式受到广泛关注,合理配置仿真资源已成为云仿真技术的核心问题之一。针对传统仿真系统资源分配中存在的资源重用性低、部署难度大等问题,提出一种改进遗传算法来求解仿真模型与虚拟机之间最优映射的算法。实验结果表明,该算法是云仿真运行环境下的一种有效资源调度算法。

In recent years, cloud simulation technology has been received extensive attention as a new type of networked simulation model. The rational allocation of the simulation resources has become one of the most important issues when it comes to applying cloud simulation technology, n this paper, we aim to design a genetic algorithm based algorithm to obtain the optimal mapping between simulation model and virtual machine. Unlike traditional static simulation system, The proposed algorithm ensures improved reusability and High availability under the construction of dynamic simulation. The experimental results show that, this algorithm is an efficient resource scheduling approach for building cloud simulation environments.