《A user centric service-oriented modeling approach》，Ding-Yuan Cheng, Kuo-Ming Chao, Chi-Chun Lo, Chen-Fang Tsai World Wide Web (2011)， Springe Abstract With rapid development of service-oriented architecture and cloud computing, web services have been widely employed on the Internet. Quality of Service (QoS) is a very important criterion for service consumers to measure and select services. The selection of web services with respect to non-functional QoS criteria can be considered as a Multiple Criteria Decision Making (MCDM) problem when multiple consumers need to share a number of services. This paper describes a new user centric service-oriented modeling approach which is featured by integrating fuzzy Technique for Order Preference by Similarity to an Ideal Solution (TOPSIS) and Service Component Architecture (SCA) to facilitate web service selection and composition and to effectively satisfy a group of service consumers’ subjective requirements and preferences in the dynamic environment. The main contribution of this method is able to translate a group of users’ fuzzy requirements to services as well as model different levels of hardware and software as services to meet the requirements. We also design a simulated environment that includes 8*8 LED matrix on a circuit board that corresponds to an office with different appliances to demonstrate the dynamic service selection and binding. The simulation is used to assess the computational efficiency of the fuzzy TOPSIS method and the effectiveness of the proposed system. Keyword： SCA . fuzzy TOPSIS . service selection . multiple criteria decision making (MCDM) 文献类型： 仿真模型 研究目标： 研究方法： 以Group Decision Making为核 以fuzzy TOPSIS为工具 以Service Component Architecture (SCA)为纽带 以Smart home LED为仿真环境 注： 逼近理想解排序法 TOPSIS （Technique for Order Preference by Similarity to an Ideal Solution ）法是 C.L.Hwang 和 K.Yoon 于1981年首次提出，TOPSIS法根据有限个评价对象与理想化目标的接近程度进行排序的方法，是在现有的对象中进行相对优劣的评价。理想化目标（Ideal Solution）有两个，一个是肯定的理想目标（positive ideal solution）或称最优目标，一个是否定的理想目标（negative ideal solution）或称最劣目标，评价最好的对象应该是与最优目标的距离最近，而与最劣目标最远，距离计算可采用明考斯基距离，常用的欧几里德几何距离是明考斯基距离的特殊情况。 比基尼： 难点 重点 疑点 个人点评： 个人认为本文并没有太多新意，但是其写作方式巧妙：和学硬件的讲软件，同学软件的谈硬件。 值得借鉴，总结架构： Smart home + Group Decision Making (Fuzzy TOPSIS) + SCA + LED 如我 Smart home + Group Decision Making (Rough ...)+ SOA + ARM 文章不足之处： 作者其它文献脉络 相关重要文献 A user centric service-oriented modeling approach .pdf beamer_user_centric_service-oriented_modeling_approach.pdf
标签: TOPSIS
