云计算下的一种基于改进的量子遗传算法在资源分配的研究  

An Improved Quantum Genetic Algorithm in Resource Allocation in Cloud Computing

作　　者：毛莉君[1] 王林兵 张燕[1] 

机构地区：[1]西安培华学院,西安710065 [2]西北工业大学航空学院,西安710072

出　　处：《科技通报》2017年第11期141-144,274,共5页Bulletin of Science and Technology

摘　　要：如何提高云计算中的资源调度分配的情况,提出采用值聚类和遗传算法相结合的方式,将遗传算法中求解个体适应度与云计算中的资源序列进行对应。首先针对遗传算法的不足,采用聚类中心旋转坐标的值聚类算法对种群进行分解,有效的保持种群的多样性,其次,通过旋转角动态调整、量子变异和交叉改进的遗传算法的全局搜索能力,有效的避免陷入了局部最优,通过与遗传算法的比较,说明本文的算法在云计算资源分配方面具有一定的优越性。As how to improve the resource scheduling and allocation in cloud computing, this paper proposes the combination of K-value aggregation and genetic algorithm, and corresponds individual solution fitness in genetic algorithm with resource sequence in cloud computing. First of all, aiming at the deficiency of genetic algorithm, this paper adopts the K-value aggregation algorithm of clustering center rotation coordinate to decompose the population, which can effectively maintain diversity of the population. Secondly, genetic algorithm's global searching ability is improved through dynamically adjusting the rotation angle, quantum mutation and crossover, effectively avoiding the local optimization.Compared with genetic algorithm, algorithm in this paper has certain advantages in cloud computing resource allocation.

关 键 词：云计算 K值聚类 量子遗传 

分 类 号：TP301.6[自动化与计算机技术—计算机系统结构]