以本體論為基礎之網路服務組合

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姓名

馬意雯(I-wen Ma) 查詢紙本館藏

畢業系所

資訊工程學系在職專班

論文名稱

以本體論為基礎之網路服務組合
(Ontology base Web Services composition)

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摘要(中)

本研究主要是利用Rule-Based System 對現有存在的WS 進行調適莘取，以提高WS 所提供的價值給使用該系統的使用者。在實際規劃執行流程中，對於如何描述規劃、領域知識、推論出流程中所需任務等問題必須解決，以及在完成取得相關Service 後，調適初步規劃、組合任務成為完整的規劃、描述服務流程等相關議題也須進行處理。我們的研究中是使用AI 技術對planning 進行描述定義、及採用Partial-order planning 演算法進行規劃出流程，利用JESS Inference Engine 機制來實作出Rule-Based 的推論機制。其領域知識則是利用知識工程中的Ontology 技術來描述知識，並使用W3C WebOnt 組識所開發的Web Ontology Language(OWL)來實作出知識庫，以提供在User 進行Planning 動作，有足夠的知識背景可以達到使用者對WS 進行系統流程規劃的目的。而在利用Rule-Based 推論機制及OWL的Ontology 技術成功的將與User 目的必須要執行的Service 任務取出，及進行Planning 完成系統中要執行的規劃流程。在最後的結果，採用Workflow pattern技術作為服務流程結構設計的依據，以確保流程可以正確完整執行。所以系統規劃的過程是一種專業知識的分析與經驗的學習。我們整合 Rule-based system和workflow pattern 的技術，用以規劃網路服務流程。本研究將以規劃整合式旅遊系統為案例，探討該研究方法的可行性，且實作出對於並評估研究成果的效益，則本研究對於網路服務調適取出進行規則式推論，確實在服務流程規劃上有極大的便利。

摘要(英)

The integration of heterogonous and distributed systems with Web services(WS) has become the popular solutions in the enterprise for the deployment of electronic business processes. Since the initial use of the WS composition in value-added and composite services building, much effort has been put into further increasing its efficiency and selectivity, while decreasing the amount of building cost. Unfortunately, such development efforts have shown diminishing return in recent years. This has prompted many groups to seek AI planning technologies for the improvement of WS composition. First, we explored the use of ontology for the production of specific domain knowledge. Then, we use state computing and reformed Partial-Order-Planning (POP) algorithm for beforehand planning the corresponding service flow according to user’s request. For the effective control of execution order, we combine the workflow patterns technology. And for the confirmation that the completed plan will adapt to the user’s situation and be supported with the existing services, we combine the mechanism of dynamic service selection. Finally, we build an adaptive WS planning system. From the promising experiments, we find that the dynamic service selection can ensure the validation of composite services and the reformed POP can increase the capability of composite services and decrease the time cost of service composition. Because the characteristics of our domain knowledge creation is domain-independent, the capability of our WS planning can be extended and applied to various application domains by the including of corresponding domain knowledge base.

關鍵字(中)

★ 網路服務整合
★ 本體論
★ 工作流程模型
★ 適性化規劃
★ 偏序規劃法

關鍵字(英)

★ Web services composition
★ Partial order planning
★ Workflow patterns
★ Adaptive planning
★ Ontology

論文目次

摘要............................................... II
Abstract............................................III
誌謝...............................................IV
目錄................................................V
圖目錄............................................ VII
表目錄.............................................VIII
第一章緒論..........................................1
1.1 研究背景與動機...................................3
1.2 研究問題描述.....................................5
1.3 問題分析及說明...................................7
1.4 研究相關領域.....................................9
1.5 研究方法.........................................11
1.6 研究貢獻.........................................14
第二章文獻探討......................................15
2.1 普遍性的問題描述.................................15
2.1.1 目前研究狀態與挑戰.............................16
2.1.2 各種解決問題的方法.............................18
2.2 列舉與描述所有可能解問題的方法...................18
2.2.1 學術探討.......................................21
2.2.2 描述服務及流程的標準語言.......................24
2.3 相關研究比較.....................................27
第三章研究方法......................................30
3.1 適性化網路服務規劃...............................31
3.1.1 建置知識領域(Domain Knowledge Generation)......32
3.1.2 調適與組合(Adaptation & Composition) ..........38
3.1.3 Web Service Planning ..........................40
3.2 問題空間描述.....................................43
3.3 研究方法程序說明.................................45
第四章系統實作......................................47
4.1 實作環境.........................................47
4.1.1 硬體與軟體平台.................................48
4.1.2 實作語言與工具.................................48
4.2 系統架構.........................................50
4.2.1 建立知識庫.....................................52
4.2.2 網路服務實體載入機制...........................57
4.2.3 規則式系統規劃建立服務流程.....................58
4.2.4 規劃服務流程轉換BPEL4WS........................62
4.3 系統展示.........................................66
4.3.1 使用者介面、執行結果、與螢幕列印...............66
4.4 實作經驗學習.....................................68
第五章研究評估與討論................................69
5.1 評估的準則.......................................69
5.2 系統特性評估.....................................71
5.3 系統流程控制結構評估.............................72
5.4 研究成果比較與討論...............................73
第六章研究結論與未來建議............................74
參考文獻.............................................75

參考文獻

[1] Kouadri Mostefaoui, S., & Hirsbrunner, B. (2003). Towards a Context-Based Service Composition Framework. In Proceedings of The First International Conference on Web Services , Las Vegs, Nevada, USA.
[2] Korkea-aho, M. (2000). Context-Aware Applications Survey. Internetworking Seminar (Tik-110.551), Helsinki University of Technology.
[3] Dey, A. K., & Abowd, G. D. (1999). Towards a better understanding of context and context-awareness. Technical Report GIT-GVU-99-22, Georgia Institute of Technology, College of Computing.
[4] Prekop, P., & Burnett, M. (2003). Activities, context and ubiquitous computing. Special Issue on Ubiquitous Computing Computer Communications, 26(11).
[5] Neill, E. O., & Lewis, D. (2005). A Platform for User-Centred Evaluation of Context-Aware Services. The 5th Information and Telecommunication Technologies Conference, Cork, Ireland, 26-27.
[6] Soldatos, J., Pandis, I., Stamatis, K., Polymenakos, L., & Crowley, J. L. (2004). Agent Based Middleware Infrastructure for Autonomous Context-Aware Computing Services. To be published in the Journal of Computer Communications, Elsevier.
[7] Chaari, T., Laforest, F., & Celentano, A. (2004). Design of Context-Aware Applications Based on Web Services. Università Ca’ Foscari di Venezia. Technical Report CS-2004-5.
[8] Conlan, O., Power, Ruaidhr., Higel, S., O'Sullivan, D., & Barrett, K. Next Generation Context Aware Adaptive Services. ISICT '03: Proceedings of the 1st international symposium on Information and communication technologies, 205-212. Trinity College Dublin.
[9] Chaari, T., Laforest, F., & Celantano, A. (2005). Service-Oriented Context-Aware Application Design. First International Workshop on Managing Context Information in Mobile and Pervasive Environments (MCMP). Ayia, Napa, CYPRUS.
[10] Chen, L., Shadbolt, N.R., Goble, C., Tao, F., Cox, S. J., Puleston, C., et al. (2003). Towards a Knowledge-based Approach to Semantic Service Composition. Semantic Web Conference (ISWC2003) 2870, pp. 319-334, Florida, USA.
[11] Petrick, R., & Bacchus, F. (2002). A knowledge-based approach to planning with incomplete information and sensing. Proc. AIPS’02.
[12] Klein, M., & Dellarocas, C. (2000). A Knowledge-based Approach to Handling Exceptions in Workflow Systems. Computer Supported Cooperative Work (CSCW).
[13] Natalya, F. N., & Deborah, L. M. (2001). Ontology Development 101: A Guide to Creating Your First Ontology. Stanford Knowledge Systems Laboratory Technical Report KSL-01-05 and Stanford Medical Informatics Technical Report.
[14] Maedche, A., & Staab, S. (2001). Ontology learning for the semantic Web. IEEE Intelligent System, Special Issue on the Semantic Web, 16(2), 72-79.
[15] McGuinness, D., & Harmelen. V.F. (2004). OWL Web Ontology Language Overview. W3C Recommendation.
[16] Ding, L., Kolari, P., Ding, Z., Avancha, S., & Finin, T. (2005, October). Using Ontologies in the Semantic Web: A Survey. UMBC eBiquity Publication.
[17] Choi, C., Cho, M., Kang, E., & Kim, P. (2006). Travel Ontology for Recommendation System based on Semantic Web. Advanced Communication Technology, 2006. ICACT 2006. The 8th International Conference. 1, 624- 627.
[18] Xu Bin; Wang Yan; Zhang Po; Li Juanzi (2005). Web services searching based on domain ontology. Service-Oriented System Engineering, IEEE International Workshop, 51- 55.
[19] Knublauch, H. (2003). Case Study: Using Protege to Convert the Travel Ontology to UML and OWL. Evaluation of Ontology-based Tools, Proceedings of the 2nd International Workshop on Evaluation of Ontology-based Tools held at the 2nd International Semantic Web Conference ISWC 2003, Sanibel Island, Florida, USA.
[20] Flugge, M., & Tourtchaninova, D. (2004). Ontology-derived Activity Components for Composing Travel Web Services. The International Workshop on Semantic Web Technologies in Electronic Business (SWEB2004), Berlin.
[21] Storey, V. C., Dey, D. , Ullrich, H., & Sundaresan, S. (1998). A ontology-based expert system for database design. Data & Knowledge Engineering, 28(1), 31-46.
[22] Horrocks, I., Patel-Schneider, P. F., & van Harmelen, F.(2003). From SHIQ and RDF to OWL: the making of a Web Ontology Language. Web Semantics: Science, Service and Agents on the World Wide Web, 1(1), 7-26.
[23] Carman, M., Serafini, L., & Traverso, P. (2003). Web Service Composition as Planning. Workshop on Planning for Web Services, Trento, Italy.
[24] Qiu, L., Shi, Z., & Lin, F. (2006). Context Optimization of AI Planning for Services Composition. IEEE International Conference on e-Business Engineering (ICEBE’06), ShanGhai, China.
[25] Qiu, L., Lin, F., Wan, C., & Shi, Z. (2006). Semantic Web Services Composition Using AI Planning of Description Logics. Proceedings of the 2006 IEEE Asia-Pacific Conference on Services Computing (APSCC’06), GuangZhou, China.
[26] Pistore, M., Barbon, F., Bertoli, P., Shaparan, D., & Traverso, P. (2004). Planning and monitoring web service composition. In Proceedings of the 14th International Conference on Automated Planning and Scheduling, 247-252.
[27] Pistore, M., Marconi, A., Bertoli, P., & Traverso, P. (2005). Automated Composition of Web Service by Planning at the Knowledge Level. IJCAI 2005.
[28] Peer, J. (2005). Web Service Composition as AI Planning - a Survey. University of St., Gallen, Switzerland.
[29] Chan, M., Bishop, J., & Baresi, L. (2007). Survey and Comparison of Planning Techniques for Web Services Composition. University of Pretoria Pretoria, Technical Report, Polelo Research Group Department of Computer Science. South Africa.
[30] Van Der Poel, B., Tan, Y., Krebs, A. M., & Marsic, I. (2002). Prioritized Replication With Dynamic Selection For Mobile Environments. HICCS 36 Conference.
[31] Vukovic, M., & Robinson, P. (2004). Adaptive, planning-based, Web service composition for context awareness. International Conference on Pervasive Computing, 18-23, Vienna, Austria.
[32] Koehler, J., & Srivastava, B. (2003). Web service composition: Current solutions and open problems. Proceedings of the 13th International Conference on Automated Planning & Scheduling, 28-35, Trento, Italy.
[33] Su, X., & Rao, J. (2004). A Survey of Automated Web Service Composition Methods. In Proceedings of First International Workshop on Semantic Web Services and Web Process Composition, San Diego, California, USA.
[34] Berardi, D. (2005). Automatic Service Composition. Models, Techniques and Tools. University DEGLI STUDI Roma “La Sapienza”,2,13-42.
[35] Paolucci, M., Sycara, K., & Kawamura, T. (2003). Delivering Semantic Web Services. In Proc. WWW’03, Budapest, Hungary.
[36] Thakkar, S., Knoblock, C.A. and Ambite, J.L. (2003). A view integration approach to dynamic. composition of web services. Proceeding of 2003 ICAPS Workshop on Planning for Web. Services, Trento, Italy.
[37] Narayanan, S. & Mcllraith, S. A. (2002). Simulation, Verification and Automated Composition of Web Services. In Proc. WWW’02.
[38] Benatallah, B., Dumas, M., Fauvet, M-C., & Rabhi, F.A. (2001). Towards Patterns of Web Services Composition. School of Computer Science University of New South Wales, Sydney NSW 2052, et al. UNSW-CSE-TR-0111.
[39] Arpinar, B., Aleman-Meza, B., & Zhang R., et al. (2004). Ontology-driven Web services composition platform. IEEE International Conference on E-Commerce Technology (CEC'04), San Diego, California.
[40] Yu, H. Q., & Reiff-Marganiec, S. (2006). Semantic Web Services composition via Planning as Model Checking. Department of Computer Science, University of Leicester, UK.
[41] Berardi, D., Calvanese, D., Giacomo, G. D., Hull, R., & Mecella, M. (2005). Towards Automatic Web Service Discovery and Composition in a Context with Semantics, Messages, and Internal Process Flow. Universit`a di Roma “La Sapienza”, A Position Paper.
[42] Luo, N., Yan, J., Liu, M., Yang, S. (2006). Towards Context-Aware Composition of Web Services. Grid and Cooperative Computing, Fifth International Conference, 494-499.
[43] Kim, J., & Gil, Y. (2004). Towards Interactive Composition of Semantic Web Services. In AAAI Spring Symposium on Semantic Web Services, Palo Alto, California, USA.
[44] Skogan, D., Grønmo, R., & Solheim, I. (2004). Web Service Composition in UML. The 8th International IEEE Enterprise Distributed Object Computing Conference (EDOC), Monterey, California.
[45] Grønmo, R., Solheim, I. (2004). Towards Modeling Web Service Composition in UML. The 2nd International Workshop on Web Services: Modeling, Architecture and Infrastructure, Porto, Portugal.
[46] Curbera, F., Nagy, W., & Weerawarana, S. (2001). Web Services: Why and How. Workshop on Object-Oriented Web Services – OOPSLA 2001, Tampa, Florida, USA.
[47] Quzzani, M., & Bouguettaya, A. (2004). Efficient access to Web services. IEEE Internet Computing, 34-44.
[48] Mcllraith, S. A., Son, T. C., & Zeng, Honglei. (2001). Semantic Web Services. IEEE Intelligent Systems. Special Issue on the Semantic Web, 16(2), 46-53.
[49] Sycara, K., Paolucci, M., Soudry, J. & Srinivasan, N. (2004). Dynamic Discovery and Coordination of Agent-Based Semantic Web Services. IEEE Internet Computing, 66-73.
[50] Berners-Lee, T., Hendler, J., & Lassila, O. (2001). The Semantic Web. Scientific American Magazine, Scientific American.
[51] Sivashanmugam, K., Verma, K., Sheth, A., & Miller, J. (2003). Adding Semantics to Web Services Standards. Proceedings of the International Conference on Web Services.
[52] Fensel, D., & Bussler, C. (2002). The Web Service Modeling Framework WSMF. Electronic Commerce Research and Applications, 1(2).
[53] Flügge, M. (2004). Using semantic Web services for ad hoc collaboration in virtual teams. Berliner XML Tage 2004, BibTeX, 187-198.
[54] J¨ungel, M., Kindler, E., and Weber, M. (2000). The Petri Net Markup Language. Petri Net Newsletter, 59, 24-29.
[55] Staab, S., et al. (2003). Web services: Been there, done that?. IEEE Intelligent Systems, Jan-Feb issue. 72-85.
[56] Van Der Aalst, W.M.P. (2003). Patterns and XPDL: A Critical Evaluation of the XML Process Definition Language. QUT Technical report FIT-TR-2003-06, Queensland University of Technology, Brisbane.
[57] WFMC. (2005). Workflow Management Coalition Workflow Standard: Workflow Process Definition Interface –XML Process Definition Language(XPDL) (WFMC-TC-1025). Technical report, Workflow Management Coalition, Lighthous Point, Florida, USA.
[58] Van Der Aalst, W.M.P., & Ter Hofstede, A.H.M. (2002). Workflow Patterns: On the Expressive Power of (Petri-net-based) Workflow Languages. Proc. of the Fourth Workshop on the Practical Use of Coloured Petri Nets and CPN Tools (CPN 2002), 1-20.
[59] Russell, N., ter Hoefstede, van der Aalst, W. M. P., & Mulyar, N. (2006). Workflow Control-Flow Patterns. BPM Center Report BPM-06-22, BPMcenter.org.
[60] Van der Aalst, W.M.P., Ter Hofstede, A.H.M., Kiepuszewski, B., & Barros A.P. (2000). Advanced Workflow Patterns. 7th International Conference on Cooperative Information Systems -CoopIS 2000, Lecture Notes in Computer Science, 1901, 18-29, Berlin.
[61] Russell, N., van der Aalst, W.M.P., ter Hofstede, A.H.M., & Edmond, D. (2005). Workflow Resource Patterns: Identification, Representation and Tool Support. Proceedings of the 17th Conference on Advanced Information Systems Engineering (CAiSE'05), Lecture Notes in Computer Science, 3520, 216-232, Berlin.
[62] Haller, A., & Oren, E. (2006). m3pl: A work-flows ontology extension to extract choreography interfaces. In Proceedings of the ESWC Workshop on Semantics for Business Process Management.
[63] Haller, A., Oren, E., & Kotinurmi, P. (2006). m3po: An Ontology to Relate Choreographies to Workflow Models. Services Computing (SCC '06). IEEE International Conference, 19-27.
[64] Sirin, E., Parsia, B., Wu, D. , Hendler, J. & Nau, D. (2004). HTN Planning for Web Service Composition Using SHOP2. Journal of Web Semantics, 1(4), 337-396.
[65] Yushi, C., Lee, E. W., & Limbu, D. K. (2004). Web Service Composition-An Overview of Standard. Singapore Institute of Manufacturing Technology. See http://www.itsc.org.sg/synthesis/2004/4_WS.pdf
[66] Eriksson, H. (2003). Using JessTab to Integrate Protégé and Jess. IEEE Computer Society, 43-50.
[67] Eriksson, H. (2004). JessTab Manual. Integration of Protégé and Jess. Linköping University. See http://www.ida.liu.se/~her/JessTab/JessTab.pdf.
[68] Alani, H., Kim, S., Millard, D.E., Weal, M.J., Hall, W., Lewis, P.H., & Shadbolt, N.R.(2003). Automatic Ontology-Based Knowledge Extraction from Web Documents. IEEE Intelligent Systems, 18(1), 14-21.
[69] McIlraith, S., & Son., T. C. (2002). Adapting Golog for Composition of Semantic Web Service. In Proceedings of the 5th International on Logical Foralizations of Commonsense Reasoning, 195-202.
[70] Trainotti, M., Pistorem, M., Calabrese, G., Zacco, G., Lucchese, G., Barbon, F., et al. (2005). ASTRO: Supporting Composition and Execution of Web Service. In Proceeding of the ICSOC 2005, 495-501.
[71] Ernest, F.H. (2003). Jess in Action: Java Rule-Based Systems. Manning Publications.
[72] Reiter, R. (2001). Knowledge in Action: Logical Foundations for Specifying and Implement Dynamical Systems. Massachusetts Institute of Technology.
[73] Russell, S., & Norvig, P. (2003). Artificial Intelligence: A Modern Approach. Prentice-Hall, 2 edition.
[74] Erl, Thomas. (2005). Service-Oriented Architecture: Concepts, Technology, and Design. Upper Saddle River: Prentice Hall PTR. ISBN 0-13-185858-0.
[75] Workflow patterns. In Workflow Patterns , form http://www.workflowpatterns.com/
[76] SHOP. In Simple Hierarchical Ordered Planner, from http://www.cs.umd.edu/projects/shop/index.html
[77] WfMC. In WFMC.org Standards – XPDL, form http://www.wfmc.org/standards/xpdl.htm
[78] IBM. In Business Process Execution Language for Web Service version 1.1, from http://www-128.ibm.com/developerworks/library/specification/ws-bpel/
[79] Jess. In Jess, the Rule engine for the Java platform, from http://herzberg.ca.sandia.gov/jess/.
[80] Protégé. In The Protégé Ontology Editor and Knowledge Acquisition System, form http://protege.stanford.edu/.
[81] YAWL. In YAML: Yet Another Workflow Language, from http://yawlfoundation.org/
[82] Enhydra JaWE. In Open Source Java XPDL editor, from http://www.enhydra.org/workflow/jawe/index.html
[83] Active endpoints. In Active BPEL Open Source Engine, BPEL Standard, form http://www.active-endpoints.com/active-bpel-engine-overview.htm

指導教授

楊鎮華(Stephen J.H. Yang)

審核日期

2007-7-5

推文