云平台下服务资源用户查询提取仿真研究  

Research on the Simulation of User Query Extraction Based on Cloud Platform

作　　者：孟令玺[1] 李洪亮[1] 孟令威[1] 

机构地区：[1]长春工业大学人文信息学院,吉林长春130012

出　　处：《计算机仿真》2017年第9期398-401,共4页Computer Simulation

基　　金：吉林省高等教育学会高教科研课题(JGJX2016D206);吉林省高等教育学会高教科研课题(JGJX2016D207)

摘　　要：云平台下对服务资源用户查询提取过程的研究,可更好地提升云计算平台的服务质量。对服务资源用户查询的提取,需要依据搜索策略,构建簇内消息转发机制,完成云平台下服务资源用户查询提取。传统方法先通过属性的相似度计算出彼此之间的邻接关系,促使每个邻居代表资源属性的一种变化趋势,但忽略了构建簇内消息转发机制,导致提取精度较低。提出基于模糊聚类的云平台下服务资源用户查询提取方法。上述方法先采用特征加权模糊方法对不同类型的资源节点集合进行划分,获取资源的静态数值特征与类属特征,确定与资源请求属性特征值最相似的类簇,构建簇内消息转发机制,并在簇内提取请求不能被满足时,将请求发送到与其兴趣最为相似的其它簇内,有效地完成对云平台下资源的最优提取。仿真证明,所提方法提取精度高,为提升云计算平台的服务质量奠定了基础。A query and extraction method of service resource user on cloud platform is put forward based on fuzzy clustering. The feature weighting fuzzy method is to divide different types of sets of resource node, and the static nu- meric feature and the generic attribute of resource are acquired, then the class cluster that is most similar to value of attribute feature of resource request is confirmed. In addition, the forwarding mechanism of intra-cluster message is built, and request is sent into other clusters that are most similar to interest of the request when extraction request in cluster cannot be satisfied. Thus, the optimal extraction of resource on cloud platform is completed effectively. Simu- lation proves that the method has high extraction precision. It improves quality of service of cloud computing platform.

关 键 词：云计算平台 服务资源用户 查询提取 

分 类 号：TP391[自动化与计算机技术—计算机应用技术]