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研究生:蔡宜君
研究生(外文):Tsai, Yijyun
論文名稱:在車輛行動網路中以本體論為基礎之個人化情境感知服務架構
論文名稱(外文):Ontology-Based Framework For Personalized Context-Aware Services In VANETs
指導教授:陳永昇陳永昇引用關係
指導教授(外文):Chen, Yeongsheng
口試委員:湯政仁洪茂盛
口試委員(外文):Tang, ChengjenHong, Maocheng
口試日期:2012-07-10
學位類別:碩士
校院名稱:國立臺北教育大學
系所名稱:資訊科學系碩士班
學門:工程學門
學類:電資工程學類
論文種類:學術論文
論文出版年:2012
畢業學年度:100
語文別:英文
論文頁數:53
中文關鍵詞:車輛行動網路情境感知網路本體論語言語意網規則語言SWRL規則引擎
外文關鍵詞:VANETContext AwarenessWeb Ontology Language (OWL)Semantic Web Rule Language (SWRL)SWRL Rule Engine
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近年來,車輛行動網路之應用與服務在工業界以及產學界都備受重視,包括提供行車安全的服務與便利的服務,車輛使用者可以透過車輛行動網路來獲取有關的交通資訊。另外,應用與服務在高度動態的環境中必須具有感知和適性的能力也是近年來的熱門議題之一。然而,如何正確地解譯以及整合這些情境資訊來適時地提供使用者有用的服務,以滿足使用者的實際需求仍然是個挑戰。在本論文中,我們針對車輛行動網路,建置以本體論為基礎之個人化情境感知服務架構。我們針對車輛行動網路的應用情境,建構出以網路本體論語言(Web Ontology Language, OWL)來描述本體論,以及利用語意網規則語言(Semantic Web Rule Language, SWRL)來定義推論規則。透過網路本體語言與語意網規則語言,具有語意的情境資訊可以更容易的被描述、共享及再使用。除此之外,我們利用SWRL規則引擎(Rule Engine)來達到自動推理情境資訊,以便提供適合的服務資訊給車輛使用者。最後我們實做一個雛形系統來實現目標架構,此系統透過情境感知技術和邏輯推理機制,讓車輛使用者可以自動的獲取適合的服務資訊在車輛行動網路中。基於以本體論為基礎的架構,一個智能的情境感知服務系統不僅了解使用者想要做什麼事情,且更進一步的了解使用者何時、何地想要做什麼事情。
Recently, the applications and services for VANET (Vehicular Ad Hoc Network), including the provision of road safety and comfort services as well as traffic information from service providers, have attracted lots of attention both in academic and industry communities. Also, applications and services that are aware of and adapted to their changing contexts in highly dynamic environments has become one of the most promising topics for ubiquitous computing. However, how to properly interpret the context information and integrate them so as to adaptively provide users useful services to meet their practical requirements remains a challenge. In this thesis, we investigate the problem of developing an ontology-based framework for supporting personalized context-aware services in VANETs. In the proposed framework, Web Ontology Language (OWL) is used to formally describe the ontology of vehicular services; and Semantic Web Rule Language (SWRL) is used to describe rule-based inferences for context reasoning. By using OWL and SWRL, the semantic information of contexts can be easily described, shared and reused. In addition, SWRL Rule Engine is used for automatically reasoning adaptive services for vehicular users. An illustrative example with our prototype system shows that through the proposed context-aware technologies and logic reasoning mechanisms, vehicular users can easily and automatically obtain adaptive services in VANETs. Based on proposed ontology-based framework, an intelligent context-aware services system should not only know what its user wants, but also where and when its user wants to use it.
Table of Contents
摘要 i
Abstract ii
Table of Contents iv
List of Tables v
List of Figures vi
Chapter 1 Introduction 1
1.1 Background 1
1.2 Motivation and Challenges 2
1.3 Solutions and Contributions 2
1.4 Thesis Outline 4
Chapter 2 Related Work 5
2.1 Context Awareness 5
2.2 Ontology 7
2.3 Web Ontology Language (OWL) 10
2.4 Semantic Web Ontology Language (SWRL) 12
2.5 Vehicular Ad Hoc Network (VANET) 13
Chapter 3 Proposed Ontology-Based Framework 15
3.1 System Architecture 15
3.2 Context Aggregation 17
3.3 Context Interpretation 19
3.3.1 Ontology 20
3.3.2 User-defined Rules 23
3.3.3 OWL-API 26
3.4 Context Manipulation and Reasoning 27
Chapter 4 Implementation of a Prototype System and Its Applications 30
4.1 Ontology Development Environment and Reasoning Tools 30
4.1.1 Protege 30
4.1.2 SWRLTab 35
4.1.3 SWRL Rule Engine 36
4.2 Construction of Ontology 37
4.3 Establishment of User-defined Rules 40
4.4 An Illustrative Example 42
Chapter 5 Conclusions and Discussion 47
References 50


List of Tables
Table 2.1 Common components of ontology 8
Table 3.1 Descriptions of contexts 18
Table 3.2 User-defined reasoning rules 24
Table 3.3 The Partial code in OWL API 27
Table 4.1 Protege-OWL API 34
Table 4.2 The Partial code in SWRL Rule Engine API 37
Table 4.3 Vehicular services ontology in OWL format (Partial) 39


List of Figures
Figure 3.1 Overview of the CMRM architecture 15
Figure 3.2 Class hierarchy diagram for our ontology 21
Figure 3.3 Ontology and an instance example 22
Figure 3.4 Flowchart of the context manipulation and reasoning 28
Figure 4.1 A graphical interface of Protege-OWL editor OWL Classes 31
Figure 4.2 A graphical interface of Protege-OWL editor Properties 32
Figure 4.3A graphical interface of Protege-OWL editor Individuals 32
Figure 4.4 A graphical interface of Protege-OWL editor Jambalaya 33
Figure 4.5 The SWRL Tab in Protege-OWL 36
Figure 4.6 Construction of ontology for vehicular services in Protege 38
Figure 4.7 Construction of the object property in Protege 38
Figure 4.8 Construction of the datatype property in Protege 39
Figure 4.9 SWRL rules for reminding user of what he/she has to do 41
Figure 4.10 Automatic recommendation of a restaurant with parking lots 44
Figure 4.11 Automatic recommendation of store 45
Figure 4.12 Automatic recommendation of gas station 46
[1]E. Hossain, G. Chow, V. Leung, B. McLeod, J. Misic, V. Wong, and O. Yang, “Vehicular telematics over heterogeneous wireless networks: A survey,” Computer Communications, Vol. 33, No. 7, pp. 775-793, May 2010.
[2]R. Bhakthavathsalam, S. Nayak, and MG. Srikumar, “Expediency of penetration ratio and evaluation of mean throughput for safety and commercial applications in VANETs,” IEEE International Conference on Ultra Modern Telecommunications & Workshops, pp. 1-5, Oct 2009.
[3]J. Jakubiak, and Y. Koucheryavy, “State of the art and research challenges for VANETs,” IEEE Consumer Communications and Networking Conference, pp. 912-916, Jan 2008.
[4]S. Yousefi, M. Fathy, and A. Benslimance, “Performance of beacon safety message dissemination in Vehicular Ad hoc NETworks (VANETs),” Journal of Zhejiang University-Science A, Vol. 8, No. 7, pp. 1990-2004, 2007.
[5]S. Yousefi, M.S. Mousavi, and M. Fathy, “Vehicular ad hoc networks (VANETs): challenges and perspectives,” IEEE International Conference on ITS Telecommunications Proceedings, PP. 761-766, June 2006.
[6]K.S. Michael, W. Chris, and L.M. Deborah, “OWL Web Ontology Language Guide”, http://www.w3.org/TR/owl-guide/ (Retrieved July 2012)
[7]H. lan, F.P. Peter, B. Harold, T. Said, G. Benjamin, and D. Mike, “SWRL:A Semantic Web Rule Language Combining OWL and RuleML”, http://www.w3.org/Submission/SWRL/ (Retrieved July 2012)
[8]The protege Ontology Editor and Knowledge Acquisition System, http://protege.stanford.edu/ (Retrieved July 2012)
[9]SWRLRuleEngineAPI, http://protege.cim3.net/cgi-bin/wiki.pl?SWRLRuleEngineAPI (Retrieved July 2012)
[10]SWRLTab,
http://protege.cim3.net/cgi-bin/wiki.pl?SWRLTab (Retrieved July 2012)
[11]P. Shankar, T. Nadeem, J. Rosca and L. Iftode, “CARS:Context-Aware Rate Selection for Vehicular Networks,” IEEE International Conference on Network Protocols, In Proc. IEEE ICNP, pp. 1-12, Oct. 2008.
[12]M.D. Dikaiakos, A. Florides, T. Nadeem and L. Iftode, “Location-aware Services over Vehicular Ad-Hoc Networks using Car-to-Car Communication,” IEEE Journal on Selected Areas in Conmunications, Vol. 25, pp. 1590-1602, Oct 2007.
[13]W. Woerndl, et al., “Context-Aware Recommender Systems in Mobile Scenarios,” International Journal of Information Technology and Web Engineering, Vol. 4, pp. 67-85, 2009.
[14]R. Eigner, and G. Lutz, “Collision Avoidance in VANETs - An Application for Ontological Context Models,” Sixth Annual IEEE International Conference on Pervasive Computing and Communications, PerCom-2008, pp. 412 – 416, Mar 2008.
[15]B. N. Schilit and M. M. Theimer, “Disseminating Active Map Information to Mobile Hosts,” IEEE Network, Vol. 8, No. 5, pp. 22-32, Sept-Oct 1994.
[16]A. K. Dey, “Understanding and Using Context,” Personal and Ubiquitous Computing, Vol. 5, No. 1, pp. 4-7, 2001.
[17]H. Chen, T. Finin, and A. Joshi, “A context broker for building smart meeting rooms,” Proceedings of the Knowledge Representation and Ontology for Autonomous Systems Symposium, AAAI Spring Symposium, pp. 53-60, 2004.
[18]T. Gu, H. K. Pung and D. Q. Zhang, “A Service-oriented middleware for building context-aware services,” Journal of Network and Computer Applications, Vol. 28, pp. 1-18, July 2004.
[19]L. Stojanovic, A. Maedche, B. Motik, and N. Stojanovic, “User-driven Ontology Evolution Management,” The 13th European Conf. on Knowledge Engineering and Knowledge Management (EKAW-2002), Siguenza, Spain, Oct 2002.
[20]Ontology Components, http://en.wikipedia.org/wiki/Ontology_components (Retrieved July 2012)
[21]X.H. Wang, D.Q. Zhang, T. Gu, and H.K. Pung, "Ontology based context modeling and reasoning using OWL", Proceedings of the Second IEEE Annual Conference on Pervasive Computing and Communications Workshops, pp. 18-22, March 2004.
[22]D.Brickly, and R.V.Guha, “RDF Vocabulary Description Language 1.0:RDF Schema”, http://wwww.w3.org/TR/rdf-schema, 2004. (Retrieved July 2012)
[23]Extensible Markup Language(XML),
http://www.w3.org/XML/ (Retrieved July 2012)
[24]XML Schema,
http://www.w3.org/XML/Schema (Retrieved July 2012)
[25]X. Wang and X. Yu, “A OWL-Based Semantic Web Service Discovery Framework,” Proceedings of the Advanced International Conference on Telecommunications and International Conference on Internet and Web Applications and Services, pp. 19-25, Feb 2006.
[26]J. Z. Pan and I. Horrocks, “RDFS (FA): Connecting RDF(S) and OWL DL,” IEEE transactions on Knowledge and Data Engineering, Vol. 19, No. 2, pp. 192-206, Feb 2007.
[27]J. Zhu, and S. Roy, “Mac for dedicated short range communications in intelligent transport system,” IEEE Communication Magazine, Vol. 41, pp. 60-67, Dec 2003.
[28]ProtegeOWL_API_Programmers_Guide, http://protegewiki.stanford.edu/wiki/ProtegeOWL_API_Advanced_Topics (Retrieved July 2012)
[29]N. Drummond, M. Horridge, H. Knublauch, “Protege-OWL Tutorial”, http://protege.stanford.edu/conference/2005/slides/T2_OWLTutorialI_Drummond_final.pdf (Retrieved July 2012)
[30]SWRLRuleEngineFactory, http://protege.stanford.edu/protege/3.4/docs/api/owl/edu/stanford/smi/protegex/owl/swrl/bridge/SWRLRuleEngineFactory.html (Retrieved July 2012)
[32]B. Matthews, “Semantic web technologies, ” E-learning, Vol. 6, No. 6,
pp. 8, 2005.
[33]A. Maedche, and S. Staab, “Ontology learning for the semantic web, ”
IEEE Intelligent Systems, Vol.16, No.2, pp. 72-79, 2001.
[34]J. Jovanovi, D. Gaevi, C. Brooks, V. Deved, M. Hatala, T. Eap, and G. Richards, “Using semantic web technologies to analyze learning content, ” IEEE Internet Computing, Vol. 11, No. 5, pp. 45-53, Sep/Oct 2007.
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