题名 | impacts separation framework for performance prediction of e-business systems |
作者 | Huang Xiang ; Zhang Wenbo ; Zhang Bo ; Wei Jun |
答辩日期 | 2009 |
关键词 | aspect-oriented modeling performance prediction E-Business Systems |
出版地 | 10662 LOS VAQUEROS CIRCLE, PO BOX 3014, LOS ALAMITOS, CA 90720-1264 USA |
出版者 | ICEBE 2009: IEEE INTERNATIONAL CONFERENCE ON E-BUSINESS ENGINEERING, PROCEEDINGS |
英文摘要 | E-Business systems, like Web based systems, usually use application server (AS) to support remote communication between heterogeneous systems. AS will certainly introduce great performance impacts to them transparently. This paper provides an impacts separation framework to automatically include these impacts into the application architecture. AS impacts are separated into isolated aspects and stored in a library, according to features of their component models. Application developer only need to build AS-independence architectures (UML models in this paper), and then the framework will integrated every necessary impacts based on current usage scenarios to form AS-aware models with AS details. The AS-aware models can be transformed into a performance models, and be solved to get performance prediction results. A case study has been presented to illustrate that our framework can deal with different usage scenarios easily. |
公开日期 | 2011-03-20 |
资助信息 | IEEE Comp Soc, Tech Comm Elect Commerce, IEEE, Univ Macau, Arizona State Univ, Software Res Lab, Coventry Univ, Comp Sci Dept, Fudan Univ, Software Sch, IBM China Res Lab, Singapore Management Univ, Sch Informat Syst, Hong Kong Univ Sci & Technol, Dept Comp Sci & Engn, Univ Hong Kong, Dept Comp Sci, Xian Jiaotong Univ |
出处 | Proceedings - IEEE International Conference on e-Business Engineering, ICEBE 2009; IEEE Int. Workshops - AiR 2009; SOAIC 2009; SOKMBI 2009; ASOC 2009 |
内容类型 | 学位论文 |
源URL | [http://124.16.136.157/handle/311060/8244] ![]() |
专题 | 软件研究所_软件工程技术研究开发中心 _学位论文 |
推荐引用方式 GB/T 7714 | Huang Xiang,Zhang Wenbo,Zhang Bo,et al. impacts separation framework for performance prediction of e-business systems[D]. 2009. |
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