基于RFID的上下文感知若干关键技术研究
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摘要
随着信息技术、计算技术的发展,计算模式正发生着深刻的变革,已经逐渐从传统分布式移动计算发展到普适计算模式。普适计算的本质特征是融合物理空间和信息空间,为人提供透明的、无处不在的服务。本文研究的是普适计算环境的一个重要分支领域——上下文感知计算。上下文感知计算对于实现普适计算是至关重要的。
在普适计算的背景下,本文首先分析和研究了现有上下文感知计算的理论和相关关键技术,包括上下文建模方法,上下文推理研究现状,上下文存储以及上下文感知系统框架研究现状,总结了这些研究和技术的成果与不足之处。
然后,本文提出了基于RFID的本体上下文模型,模型采用层次化的建模方式,上下文本体按领域进行划分,对各种不同类型的上下文采用统一的格式管理,实例证明该模型能够快速地构建上下文感知系统最基本需求的领域本体。
在此基础上,提出了RFID上下文感知服务模型框架,该框架包括底层通信环境、上下文感知中间件层、上下文服务层,详细阐述了框架中各模块的功能以及相互间的联系。然后用两个应用实例对本体上下文模型和服务模型进行进一步阐述和验证。
最后在研究分析了现有无线环境下的缓存置换算法后,提出了种适合于普适计算环境的上下文缓存置换算法——RCRA。算法根据上下文未来被访问的概率、上下文历史访问频率、上下文新鲜度等加权来判断上下文的价值,当有新的上下文需要加入缓冲池或缓冲池己满有必要对上下文缓冲池进行清理时,以上下文价值为依据决定是否将上下文剔除出缓存池。通过实验将RCRA和LRU对比从三个方面证明RCRA的命中率得到了很大提高。
With the rapid development of the information and computing technology, the computing mode is also undergoing profound reform. The computing model has gradually developed from the traditional distributed mobile computing to pervasive computing model. The essential characteristic of pervasive computing is the integration of physical space and information space, which provides transparent and ubiquitous services for people. In this thesis, we mainly concern on context-aware computing? an important branch of pervasive computing. Context-aware computing is crucial to the realization of pervasive computing.
In the background of pervasive computing, this thesis firstly summarizes and analyzes the research satus of context-aware computing including context modeling methods, context reasoning, context storing and context-aware system framework.
Then this thesis proposes an ontology context model based on RFID. The model uses hierarchical modeling method. Context ontologies are categorized by field and managed using unified format. The experimental results show that the model can rapidly build domain ontology for the context-aware system.
On that basis, this thesis gives a RFID based context-aware service framework. It includes underlying communication environment layer, context-aware middleware layer and service layer. The function of each module in the framework and the relationships between modules are elaborated. Then two examples are given to illustrate the context model and service model further.
Based on the analysis and research of the existing caching replacement algorithms under wireless environment, this thesis proposes a context caching replacement algorithm RCRA which is suitable for pervasive computing environment. In the algorithm, the value of the context is determined by its access probability, history access frequency and freshness. When new context is to be added into the cache or the cache is full, the algorithm removes context from the cache based on the value of the context. Finally, experiments are carried out to compare RCRA with LRU. The result shows that the RCRA improves the hit rate of the cache.
在普适计算的背景下,本文首先分析和研究了现有上下文感知计算的理论和相关关键技术,包括上下文建模方法,上下文推理研究现状,上下文存储以及上下文感知系统框架研究现状,总结了这些研究和技术的成果与不足之处。
然后,本文提出了基于RFID的本体上下文模型,模型采用层次化的建模方式,上下文本体按领域进行划分,对各种不同类型的上下文采用统一的格式管理,实例证明该模型能够快速地构建上下文感知系统最基本需求的领域本体。
在此基础上,提出了RFID上下文感知服务模型框架,该框架包括底层通信环境、上下文感知中间件层、上下文服务层,详细阐述了框架中各模块的功能以及相互间的联系。然后用两个应用实例对本体上下文模型和服务模型进行进一步阐述和验证。
最后在研究分析了现有无线环境下的缓存置换算法后,提出了种适合于普适计算环境的上下文缓存置换算法——RCRA。算法根据上下文未来被访问的概率、上下文历史访问频率、上下文新鲜度等加权来判断上下文的价值,当有新的上下文需要加入缓冲池或缓冲池己满有必要对上下文缓冲池进行清理时,以上下文价值为依据决定是否将上下文剔除出缓存池。通过实验将RCRA和LRU对比从三个方面证明RCRA的命中率得到了很大提高。
With the rapid development of the information and computing technology, the computing mode is also undergoing profound reform. The computing model has gradually developed from the traditional distributed mobile computing to pervasive computing model. The essential characteristic of pervasive computing is the integration of physical space and information space, which provides transparent and ubiquitous services for people. In this thesis, we mainly concern on context-aware computing? an important branch of pervasive computing. Context-aware computing is crucial to the realization of pervasive computing.
In the background of pervasive computing, this thesis firstly summarizes and analyzes the research satus of context-aware computing including context modeling methods, context reasoning, context storing and context-aware system framework.
Then this thesis proposes an ontology context model based on RFID. The model uses hierarchical modeling method. Context ontologies are categorized by field and managed using unified format. The experimental results show that the model can rapidly build domain ontology for the context-aware system.
On that basis, this thesis gives a RFID based context-aware service framework. It includes underlying communication environment layer, context-aware middleware layer and service layer. The function of each module in the framework and the relationships between modules are elaborated. Then two examples are given to illustrate the context model and service model further.
Based on the analysis and research of the existing caching replacement algorithms under wireless environment, this thesis proposes a context caching replacement algorithm RCRA which is suitable for pervasive computing environment. In the algorithm, the value of the context is determined by its access probability, history access frequency and freshness. When new context is to be added into the cache or the cache is full, the algorithm removes context from the cache based on the value of the context. Finally, experiments are carried out to compare RCRA with LRU. The result shows that the RCRA improves the hit rate of the cache.
引文
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[3]徐光裕,陶霖密,史元春,张翔.普适计算模式下的人机交互,计算机学报,2007,30(7)：1041-1053
[4]李蕊,李仁发.上下文感知计算及系统框架综述.计算机研究与发展,2007,44(2)：269-276
[5]Schilit B, Adams N, Want R. Context-aware computing applications. In: Proceedings of the Workshop on Mobile Computing Systems and Applications (WMCSA'94), Santa Cruz,CA,DEC,1994:85-90
[6]Brown P J, Bovey J D, Chen X. Context-Aware Applications:from the Laboratory to the Marketplace. IEEE Personal Communications,1997,4(5):58-64
[7]Anind K D, Gregory D A, Daniel S. A conceptual framework and a toolkit for supporting the rapid prototyping of context-aware applications. Human-Computer Interaction,2001,16(2-4):97-166
[8]Dey A K, Saltier D, Abowd G D. A conceptual Framework and a Toolkit for Supporting the Rapid Prototyping of Context-Aware Applications. Human-Computer Interaction (HCI),2001,16(2-4):97-166
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[10]Joyce H, Stephen S I. Using context-aware computing to reduce the perceived burden of interruptions from mobile devices. Proceedings of the SIGCHI conference on Human factors in computing systems, New York, USA,2005
[11]Hung K P, Tao G, Wen W X, et al. Context-aware middleware for pervasive elderly homecare. IEEE JOURNAL ON SELECTED AREAS IN COMMUNICATIONS,2009,27(4):510-524
[12]Matthias B, Schahram D, Florian R. A survey on context-aware systems. International Journal of Ad Hoc and Ubiquitous Computing.2007,2(4):263-277
[12]Hong J Y, Suh E H, Kim S J. Context-aware systems:A literature review and classification. Expert Systems with Applications,2009,36(4):8509-8522
[13]Hwe-Mo K, Kyong-Ho L. Device-independent web browsing based on CC/PP and annotation. Interaction with Computers,2006,18(2):283-303
[14]Henricksen K. Developing context-aware pervasive computing applications: Models and approach. Journal of Pervasive and Mobile Computing,2005,2(1): 37-64
[15]Jong-yi H, Eui-ho S, Sung-Jin K. Context-aware systems:A literature review and classification. Expert Systems with Applications,2009,36(4):8509-8522
[16]Gu T, Pung H K, Zhang D Q. A Service-Oriented Middleware for Building Context-Aware Services. Journal of Network and Computer Applications,2005, 28(1):1-18
[17]Lee J Y, Seo D W, Rhee G. Visualization and interaction of pervasive services using context-aware augmented reality. Expert Systems with Applications,2008, 35(4):1873-1882
[18]Lee Y, Kwon O. A index-based privacy preserving service trigger in context-aware computing environments. Expert Systems with Applications,2010, 37(7):5192-5200
[19]Hong J, Suh E H, Kim J, et al. Context-aware system for proactive personalized service based on context history. Expert Systems with Applications,2009, 36(4):7448-7457
[20]Garbinato B, Holzer A, Vessaz F. Context-aware broadcasting approaches in mobile ad hoc networks. Computer Networks,2010,54(7):1210-1228
[21]Christos D, Nikos L, Michalis V. Context-aware media independent information server for optimized seamless handover procedures. Electronic Notes in Theoretical Computer Science,2006,146(1):101-116,
[22]Sharat K, Jukka R. A context based storage system for mobile computing applications. Mobile Computing and Communications Review,2005,9(1):64-68
[23]蒋发群,李锦涛,苏晓丽等.基于上下文感知的普适服务框架.计算机工程,2008,34(13)：16-18
[24]Graham K, Franklin R, Chris W, et al. Compsite Capability/Preference Profiles(CC/PP):Structure and Vocabularis 1.0 W3C Recommendation 15. http://www.w3.org/TR/CCPP-struct-vocab/. January 2004
[25]Matsuyama K, Kraus M, Kitagawa K, Saito N. A path-based RDF query language for CC/PP and UAProf. Pervasive Computing and Communications Workshops,2004
[26]Achilleas A, Kun Y, Nektarios G. Context modelling and a context-aware framework for pervasive service creation:A model-driven approach. Pervasive and Mobile Computing,2010,6(2):281-296
[27]Kao T.H, Yuan S.M. Designing an XML-based context-aware transformation framework for mobile execution environments using CC/PP and XSLT. Computer Standards & Interfaces,2004,26(5):377-399
[28]Dan B, Miller L. FOAF Vocabulary Specification 0.91. Namespace Document 2 November 2007. http://www.xmlns.com/foaf/spec/20071002.html. November 20007
[29]Zhou B, Wu C. Social Networking Interoperability through Extended FOAF Vocabulary and Service. Information Sciences and Interaction Sciences (ICIS), June 2010,50-55
[30]Jamie B, Alisdair M, James I. FOAF:improving detected social network accuracy. In proceeding of the 12th ACM international conference adjunct papers on Ubiquitous computing, New York, USA,2010
[31]中华人民共和国科学技术部等十五部委.中国射频识别(RFID)技术政策白皮书,2006,6
[32]Yeh T C, Wang Y J, Kuo T C, et al. Securing RFID systems conforming to EPC Class 1 Generation 2 standard. Expert Systems with Applications,2010, 37(12):7678-7683
[33]Enabling Ubiquitous Sensing with RFID.Computer,2004,37(4):84-86
[34]Lorraine S L, Kirk D F, Jeffery S S. Radio frequency indentification(RFID) implementation in the service sector:A customer-facing diffusion model. International Journal of Production Economics,2008,112(2):587-600
[35]Jaekwan P, Bonghee H, Chaehoon B. A query index for continuous queries on RFID streaming data. Science in China Series F:Information Sciences,2008, 51(12):2047-2061
[36]Lonsdale D, David W E, Ding Y H, et al. Reusing ontologies and language components for ontology generation. Data & Knowledge Engineering,2010, 69(4):318-330
[37]Garshol L M. The Linear Topic Map Notation, Definition and introduction, version 1.3. http//www.ontopia.net/download/ltm.html.2006,6,17
[38]Fensel D, V.Harmelen F, Horrocks I, et al. OIL:an ontology infrastructure for the Semantic Web. Intelligent Systems, IEEE.2001,16(2):38-45
[39]M.Robert M. Inside the LOOM description classifier. ACM Special issue on implemented knowledge representation and reasoning systems,1991,2(3):88-92
[40]OWL 2 Web Ontology Language Document Overview. http://www.w3.org/TR/owl2-overview/. W3C Recommendation, October 2009
[41]Sean B, Frank V H, Jim H, et al. OWL Web Ontology Language Reference. http://www.w3.org/TR/owl-features/. W3C Recommendation 10, February 2004
[42]Martin D, Burstein M, Hobbs J, et al. OWL-S:Semantic Markup for Web Services, http://www.ai.sri.com/daml/services/owl-s/1.2/overview/
[43]Horrocks I, Boley H, Tabet S, et al. SWRL:A Semantic Web Rule Language Combining OWL and RuleML. http://www.daml.org/2004/11/fol/rules-all.Draft Version 0.7 of 2 November 2004
[44]Antoniou G, Harmelen F V. Web Ontology Language:OWL. Information Systems, 2009,1:91-110
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