大数据背景下的云联盟数据资源服务组合模型  

Cloud computing federation data resource server composition in big data background

作　　者：张影[1] 翟丽丽[1,2] 王京[1] ZHANG Ying ZHAI Lili WANG Jing(School of Management, Harbin University o{ Science and Technology, Harbin 150080, China High-tech. Industrial Development Research Center, Harbin University of Science and Technology, Harbin 150080, China)

机构地区：[1]哈尔滨理工大学管理学院,黑龙江哈尔滨150080 [2]哈尔滨理工大学高新技术产业发展研究中心,黑龙江哈尔滨150080

出　　处：《计算机集成制造系统》2016年第12期2920-2929,共10页Computer Integrated Manufacturing Systems

基　　金：国家自然科学基金资助项目(71272191;71672050);黑龙江省高等学校哲学社会科学创新团队建设计划资助项目(TD20123)~~

摘　　要：针对大数据背景下的云联盟数据资源多服务问题,提出基于Agent的云联盟数据资源服务体系结构,在分析云联盟数据资源服务特征及组合流程的基础上,从任务请求过量和强QoS约束两种组合情形出发,构建了云联盟数据资源服务组合模型,并采用量子多目标进化算法进行求解。通过仿真实验,证明了模型及算法的可行性与有效性。To cope with multi-server oriented cloud computing federation problem in big data background, a cloud computing federation resource service system structure based on Agent was put forward. Through analyzing the characteristics and process of cloud computing federation data resource service, a service composition optimization model was established from the perspective of services shortage relative to tasks and service Qos constrains on tasks, and the quantum multi-objective evolutionary algorithm was adopted to solve this model. Simulation experiments results showed the feasibility and effectiveness of proposed model and algorithm.

关 键 词：大数据 云联盟 数据资源服务组合 量子多目标进化算法 

分 类 号：G203[文化科学—传播学]