| 研究生: |
吳穗池 Wu, Suei-Chih |
|---|---|
| 論文名稱: |
建立考量群體需求之網路服務選擇方法 Developing a Method of Web Service Selection Considering Group Preference |
| 指導教授: |
王惠嘉
Wang, Hei-Chia |
| 學位類別: |
碩士 Master |
| 系所名稱: |
管理學院 - 資訊管理研究所 Institute of Information Management |
| 論文出版年: | 2011 |
| 畢業學年度: | 99 |
| 語文別: | 中文 |
| 論文頁數: | 72 |
| 中文關鍵詞: | 網路服務 、服務品質 、群體決策 、逼近理想解排序法 |
| 外文關鍵詞: | Web service, QoS, group decision, TOPSIS |
| 相關次數: | 點閱:83 下載:0 |
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為了因應企業快速整合的需求,World Wide Web Consortium(W3C)與Organization for the Advancement of Structured Information Standards(OASIS)等組織提出了服務導向架構的相關標準,在此標準的架構中,網路服務具有跨平台、彈性及重複使用的特性,正好為企業在開發系統時得以整合不同軟體服務提供者的方式來建置系統。然而當功能需求越來越複雜時,僅靠單一服務已不能滿足所有功能需求,因此將網路服務進行組合成為一個可行方案,在組合時可能由於網路上有越來越多相同功能之網路服務可供選擇,網路服務的選取除了要滿足功能需求外還需考量QoS的表現及限制,並要能確保整個服務組合能達到多數使用者需求的全域最佳化配置,這些都將增加服務選擇的困難度。過去已有許多網路服務選擇的相關研究,致力於使用QoS作為選擇標準、網路服務組合的選擇及群體進行網路服務選擇,但這些研究多假設決策者不了解網路服務組合流程,或沒有針對各流程重視程度去選擇網路服務,而過去亦沒有從方案產生到最後進行群體選擇之網路服務選擇相關研究。為了解決這些問題,本研究提出一群體決策網路服務選擇流程(Group Decision Web Service Selection , GDWSS),首先考量各決策者對任務重視程度與全域最佳化產生多個選擇方案,再以群體決策中之TOPSIS方法為基礎,提出能讓決策者以較少的評估工作且考量群體偏好之網路服務選擇方法,以期能多利用可用之網路服務並可降低整體決策者對系統期望之落差。我們亦對所提出的方法利用模擬資料來進行實驗,實驗結果顯示在方案產生的過程中,較被重視之任務流程可選擇較符決策者偏好之網路服務;在群體選擇的過程中,相較於傳統方法,決策者較偏好以QoS數值取代決策者評估值的WSS-TOPSIS方法,且其所得到的方案排序結果具有顯著的共識度。
W3C and OASIS proposed a service oriented architecture standard to meet the demand for rapid business system integration. Under the framework of the standard, the Web services, which have the characteristics of crossing- platform, flexibility, and reusability, are suitable for the enterprise systems to exchange data and can be regarded as components made by different service providers to build systems. These features of web service can be adapted for web service composition to meet complicated functional requirements which cannot be met by a single web service alone. There were many web service selection researches over the past years, committed to using QoS as the selection criteria for the selection of web service composition and selection of web service for groups. But many of these researches assume that decision makers do not understand the web service composition process. They didn't select web service by the importance of the task process. There was also no research about generating web service selection alternatives from decision makers' preference for group selection. To solve these problems, we propose a selection process named Group Decision Web Service Selection, GDWSS. First, we consider the importance of each task of decision maker and the global optimization for generating alternatives, and then select the final solution by WSS-TOPSIS which was adopted from the idea of TOPSIS method. GDWSS allows decision-makers to set preference with less workload. We conducted experiments using simulated data. Experimental results show that 1) the task process with more importance can select web service more close to decision maker's preference; 2) the ranking results show high consensus.
Ardagna, D., & Pernici, B. (2005). Global and Local QoS Constraints Guarantee in Web Service Selection. Paper presented at the IEEE International Conference on Web Services (ICWS'05), Orlando, Florida.
Ardagna, D., & Pernici, B. (2007). Adaptive service composition in flexible processes. IEEE Transactions on Software Engineering, 33(6), 369-384.
Canfora, G., Penta, M. D., Esposito, R., & Villani, M. L. (2005). An Approach for QoS-aware Service Composition based on Genetic Algorithms. Paper presented at the Proc. of Genetic and Evolutionary Computation Conference, Washington, D.C.
Chen, Y.-L. & Cheng, L.-C. (2010). An approach to group ranking decisions in a dynamic environment. Decision Support Systems, 48(4), 622-634.
Hilari, M. O. (2009). Quality of Service (QoS) in SOA Systems. A Systematic Review. Universitat Politècnica de Catalunya.
Hillier, F. S. & Lieberman, G. J. (1967). Introduction to Operations Research (Eighth ed.): The McGraw-Hill Companies, Inc.
Huang, A. F. M., Lan, C. W., & Yang, S. J. H. (2009). An optimal QoS-based Web service selection scheme. Information Sciences, 179(19), 3309-3322.
Jagdev, H., Vasiliu, L., Browne, J., & Zaremba, M. (2008). A semantic web service environment for B2B and B2C auction applications within extended and virtual enterprises. Computers in Industry, 59(8), 786-797.
Kahraman, C., Engin, O., Kabak, O., & Kaya, I. (2009). Information systems outsourcing decisions using a group decision-making approach. Engineering Applications of Artificial Intelligence, 22(6), 832-841.
Karakoc, E. & Senkul, P. (2009). Composing semantic Web services under constraints. Expert Systems with Applications, 36(8), 11021-11029.
Lo, C.-C., Chen, D.-Y., Tsai, C.-F., & Chao, K.-M. (2010). Service selection based on fuzzy TOPSIS method. Paper presented at the 2010 IEEE 24th International Conference on Advanced Information Networking and Applications Workshops, Perth, Australia.
Longchang, Z., Hua, Z., & Fangchun, Y. (2010). Multi-Attribute Group Decision Making-Based Decentralized Web Service Selection. Paper presented at the 2010 International Conference on Service Sciences, Hangzhou, Zhejiang, China.
Maximilien, E. M. & Singh, M. P. (2004). A framework and ontology for dynamic Web services selection. IEEE Internet Computing, 8(5), 84-93.
Meng, S. & Arbab, F. (2009). QoS-Driven Service Selection and Composition Using Quantitative Constraint Automata. Fundamenta Informaticae, 95(1), 103-128.
Nakov, S. (2008). SOA Trends for 2008. Retrieved August 19, 2010, from http://www.nakov.com/blog/wp-content/uploads/2009/05/nakov-soa-trends-2008.ppt
Neubauer, T. & Stummer, C. (2010). Interactive selection of Web services under multiple objectives. Information Technology & Management, 11(1), 25-41.
Ran, S. (2003). A model for web services discovery with QoS. SIGecom Exchanges, 4(1), 1-10.
Top 10 SOA Trends for 2010. (2010). Retrieved August 19, 2010, from http://www.biztechmarch.com/SOA/top-10-soa-trends-for-2010.htm
W3C. (2001). Web Services Description Language (WSDL) 1.1. Retrieved August, 11, 2010, from http://www.w3.org/TR/wsdl/
W3C. (2004). Web Services Architecture. Retrieved August 16, 2010, from http://www.w3.org/TR/ws-arch/
W3C. (2007). Web Services Policy 1.5 - Framework. Retrieved November 4, 2010, from http://www.w3.org/TR/ws-policy/
Xiong, P. C., Fan, Y. S., & Zhou, M. C. (2008). QoS-aware Web service configuration. IEEE Transactions on Systems Man and Cybernetics Part A: Systems and Humans, 38(4), 888-895.
Yoon, K. P. & Hwang, C.-L. (1995). Multiple attribute decision making: An introduction (Sage University Paper series on Quantitative Applications in the Social Sciences, 07-104). Thousand Oaks: CA: Sage.
Zeng, L. Z., Benatallah, B., Ngu, A. H. H., Dumas, M., Kalagnanam, J., & Chang, H. (2004). QoS-aware middleware for Web Services Composition. IEEE Transactions on Software Engineering, 30(5), 311-327.
王小璠. (2005). 多準則決策分析. 台中市: 滄海書局.
梁定澎. (2006). 決策支援系統與企業智慧. 台北市: 智勝文化.
校內:2016-07-14公開