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基于云平台的软件服务流引擎技术研究
引用本文:蔡茂,徐凌宇,东韩,陈亮,杜金峰.基于云平台的软件服务流引擎技术研究[J].合肥工业大学学报(自然科学版),2012(8):1017-1021.
作者姓名:蔡茂  徐凌宇  东韩  陈亮  杜金峰
作者单位:上海大学计算机工程与科学学院;国家海洋信息中心
基金项目:国家自然科学基金资助项目(40976108);国家“十二五”规划课题资助项目(201105033);上海市科技创新行动计划资助项目(11511500200)
摘    要:传统的工作流自动化处理大多是针对固定的较为简单的执行单元,不能适应复杂的SaaS服务要求。为同时向大规模访问用户提供可靠实时的云计算服务,文章设计了软件服务流,高效、实时、稳定的调度算法是软件服务流成功实施的关键。通过服务抽象过程把复杂的用户自定制请求匹配成云平台的可执行单元后,软件服务流引擎利用文中提出的EOE实时调度算法处理用户请求,交付下层执行,监控执行进程、系统状态,实现软件服务流的自动化高效运行。最后,给出了在海洋环境信息云服务体系框架下的实现。

关 键 词:云计算  软件即服务  工作流  软件服务流

A study of SaaS-flow engine technology based on cloud platform
CAI Mao,XU Ling-yu,DONG Han,CHEN Liang,DU Jin-feng.A study of SaaS-flow engine technology based on cloud platform[J].Journal of Hefei University of Technology(Natural Science),2012(8):1017-1021.
Authors:CAI Mao  XU Ling-yu  DONG Han  CHEN Liang  DU Jin-feng
Institution:1(1.School of Computer Engineering and Science,Shanghai University,Shanghai 200072,China;2.National Marine Information Center,Tianjin 300171,China)
Abstract:In traditional workflow automatic processing,all the execution units are simple and fixed,which is hard to meet the complex software as a service(SaaS) requirements.In order to meet the demand of providing reliable real-time cloud computing services to large-scale users at the same time,the SaaS-flow is designed in this paper.The high efficiency,realtimeness,stability of the scheduling algorithm is the key to the success of the execution of SaaS-flow.First step is to Abstract the complex user customization requests into executable units of cloud platform,and then the SaaS-flow engine will process the user’s request according the EOE real-time scheduling algorithm proposed in the paper.The last step is to deliver the request to lower executive,monitor the implementation process and system status,and realize the automatic efficient operation of the SaaS-flow.The application of the technology in cloud services system framework for marine environmental information is realized.
Keywords:cloud computing  software as a service(SaaS)  workflow  SaaS-flow
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