摘要
为了实现云计算环境下高效地变粒度服务,以满足各种用户的弹性需求,提出了一种基于AOV图和免疫优化算法的云计算服务组合方法;首先,采用AOV图计算目标节点的QoS聚合值,将其作为对应的服务组合方案的QoS值;然后,将服务组合方案映射为抗体,对抗体编码方式、抗体与抗原之间的多目标亲和度评价函数,以距离为基础的抗体之间的亲和度评价函数均进行了设计,并将所有服务组合方案中的支配方案存储到记忆细胞集中以加快收敛速度;最后,定义了采用AOV图计算QoS聚合值和采用免疫优化算法进行服务组合的具体算法;仿真实验表明文中方法能高效地实现云计算环境下的服务组合,且与其它方法比较,文中方法具有较高的亲和度0.829,具有较大的优越性。
In order to realize the granularity changing service in cloud computing to satisfy the elastic demand of all kinds of users, a service composition method based on AOV figure and immune optimization algorism was proposed. Firstly, the AOV figure was used to com- pute the QoS clustering value of goal node, and using it as the QoS value for the service composition, then the service composition was regar- ded as the antibody, the coding method of antibody, the multiple--goals affinity evaluation function between antibody and antigen, the affini- ty evaluation function between antibodies based on distance are designed, and the Pareto solution was saved in Set of memory cells. Finally, the specific algorism using the defined improved immune planning algorism to solve service composition was defined. The experiment shows the mett^od in this paper can realize service composition in cloud computing, and compared with the other methods, it has the high affinity value 0. 829. Therefore it is proved has big priority.
出处
《计算机测量与控制》
北大核心
2014年第3期857-859,共3页
Computer Measurement &Control
基金
河南省教育厅自然科学基础研究计划项目(201210919013)
河南省教育厅科学技术研究重点项目(12B520040)
关键词
云计算
服务选择
服务质量
免疫优化
cloud computing
service composition
service quality
immune optimization
