Web主动服务若干关键实现技术研究
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摘要
Web和基于Internet的应用系统改变着当今世界,Internet从信息发布平台逐渐演变为一个开放的分布计算环境,越来越多的数据资源、计算资源与应用资源依托Internet和Web成为可被公共获取和访问的网络资源。近年来,随着“服务”成为开放网络环境下资源封装与抽象的核心概念,通过Web服务实现计算资源灵活配置成为技术发展的创新思路,特别是随着主动计算特征出现和服务要求以人为本、并增加用户体验性,Web主动服务己成为面向服务计算的核心内容。
本文以主动式Web服务为基本思想,将用户、服务、业务有机结合,通过实现Web主动服务以促进企业内部以及企业之间的信息集成和交互。本论文的工作主要包括以下几个方面。
(1)提出了Web主动服务模型
根据Web主动服务架构和主动计算特征,提出了Web主动服务“推”-“拉”模型(WASM),在此模型中对服务请求者的意图进行发现与辨识,以期望得到用户的服务需求,服务质量和等级;同时在服务注册库中查询发现服务;通过服务获取技术绑定所需服务的URI以获取匹配的服务。
(2)提出了一种预模式可生长神经网络模型和基于混合策略的服务挖掘算法
根据反映用户意图的内外模式和认知过程中的模板匹配、认知变焦原理,提出了一种预模式可生长神经网络,它具有预模式的选取和随着辨识要求自适应增加网络节点(或)和增加模式网络协同工作,可以高效准确地发现和辨识用户意图,并以模式网络的最优输出作为教师样本来训练其它模式网络,以达到知识共享、提高辨识效率和精度;并根据用户意图在主动服务中的不同作用层次提出基于混合挖掘算法有针对性地进行意图的发现与辨识:用v-SVC的支持向量学习算法对用户的偏好和意图进行学习和辨识,反映用户的状态和所处的角色;用概念层次生成算法对用户服务属性层次化,获得用户的服务焦点;借助于模糊聚类算法来辨识用户所期望的服务质量或等级。
(3)提出了服务命中策略和小世界模型下的Web智能路由算法
考虑在大量冗余、相近的服务信息中和分布式的服务注册库中高效发现所需服务,提出了服务命中策略并通过相近度计算获取相近的可替换服务,解决高效服务命中和服务绑定失效的问题,并根据服务网库的分布独立性,提出基于资源最优的分布式服务网库搜索算法。还依据小世界网络具有特征路径短、聚类度大的特征和服务聚集性,将提供Web服务的对等节点构造成为具有小世界属性的网络,在服务查询和路由过程中可以提高效率和减少通信量。Web服务路由凭借其虚名称和路由感知机制,在SOAP中方便地实现路由路径的指定和装载。借助于基本蚁群算法,提出了在小世界网络模型中基于QoS约束下的智能路由算法。
(4)提出了基于反射中间件的服务失效处理方法
服务失效是影响服务高可用的制约因素,对于Web主动服务就需要对服务进行必要的动态配置和优化。利用反射中间件技术,将其配置在服务器和客户端捕捉到服务失效的状态,来调整和配置服务以适应服务的内外部环节的变化和要求,并利用混合神经网络作为反射中间件的检测机制。
(5)提出了一种基于QoS上下文反馈控制机制的服务组合方法
QoS是Web服务关键因素,从基于QoS的服务发现机制和基于QoS的服务合成机制基础上提出了QoS指标的上下文模型,并依据此模型来利用反馈控制机理,使用遗传算法作为控制器对QoS上下文的各项指标进行调节,并在备选的服务中发现所需最优的服务。
The Communication and interaction have rapidly changed by Web Technology and application system based on Internet. The Internet is now undergoing an evolution from a simple platform for information sharing to an open distributed computing infrastructure. With more and more data resources, computing resources and applications accessible via the Internet and web pages for public usage, resource sharing and application integration across organizational boundaries. In recent years, the concept services in open of network has been proposed as a mean of abstracting and wrapping environment, which makes Web service the natural way for dynamic resource aggregation and flexible application integration. Especially, along with the features of active computing, human centered and enhancing customer experience in services, which make Web active services become a kernel on SOC (Service Oriented Computing).
Implementing Web active services makes possible for information integration and interaction across organizational boundaries and enterprise interior depend upon unite clients, services, and operation together. The main contributions of this dissertation are summarized as fellows:
(1) The WASM (Web Active Services Model) that has“push”and“draw”two ways character is proposed.
Based on framework of active services and features of actives computing, the key technologies and implementation methods in the WASM are presented. Firstly, discovery and recognizing the asker of services to know its requirement, intention, QoS, and level of services; Secondly, Querying and discovering services information in registry of services; finally, binding proper services’URI to get it that meet user needs.
(2) A PENN and Based on hybrids policies algorithm are discussed
The PENN (Patterned Extendable Neural Network) is presented for discovering and recognizing user intention by selecting pro-pattern and adjusting number of latent layer node and/or increases pattern cooperation to meet discovering and recognizing needs. Taking an optimum pattern output as teacher train other patterns for sharing knowledge and improving efficiency and precision. The hybrid algorithm is proposed based on the different activities of user intention in Web initiative services. The preference learning with v -SVC provide effective preference recognition and role selection for user intention. The service focus point will be found with concept hierarchy algorithm, which conceptualizes service attributes. Using fuzzy clustering for user desire level or quality of services is feasible decision.
(3) The policy of services hitting and Based on small World model Web routing algorithm are proposed
How to discover required services in abundant redundant and similar service that record in databases which possibly have distributed features? The policy of services hitting is introduced, which effectively solves problem of services hitting, and process invalidation of services binding through similarity degree computing and sorting. Because of distributing and independency of services net database, a resource optimization search algorithm is proposed. Becaude the small world networks have a short length of characteristic path and evident attention of clustering, the efficiency of communication is improved in Web services querying and routing on the network which has small-world features and is constructed by some peer to peer services that regard as vertex in graph. Web service depends on virtual name and routing aware mechanism in expediently implement routing appoint and load in SOAP. Based on basic ant colony algorithm, the QoS constrained Ant colony Algorithm is presented.
(4) The mechanism to avoid Web services unavailability is proposed
Web services’high usability is restrained by Services unavailability. The reflection technologies are presented to improving Web services self-adaptive and robust ability to modify and optimize to Web services. The reflection layers are deployed in client’s and server’s sides to catch the traps that are some status of Web services unavailability. The reflection layers can adjust the internal structures and states of services, which avoid services unavailability in time and make services adapt to environment changing. The Hierarchy mixture of expert neural network as a detector in reflective middleware is introduced.
(5) The method of Services composition based on QoS mode is proposed
One of key factors is QoS for obtaining services. The QoS context is presented to deal with the different circumstance in compositing services and discovering services. Based on QoS context model, the candidate services are selected and compounded by QoS control system in which the genetic algorithm as controller to ensure to select suitable web services’QoS in the feedback system.
本文以主动式Web服务为基本思想,将用户、服务、业务有机结合,通过实现Web主动服务以促进企业内部以及企业之间的信息集成和交互。本论文的工作主要包括以下几个方面。
(1)提出了Web主动服务模型
根据Web主动服务架构和主动计算特征,提出了Web主动服务“推”-“拉”模型(WASM),在此模型中对服务请求者的意图进行发现与辨识,以期望得到用户的服务需求,服务质量和等级;同时在服务注册库中查询发现服务;通过服务获取技术绑定所需服务的URI以获取匹配的服务。
(2)提出了一种预模式可生长神经网络模型和基于混合策略的服务挖掘算法
根据反映用户意图的内外模式和认知过程中的模板匹配、认知变焦原理,提出了一种预模式可生长神经网络,它具有预模式的选取和随着辨识要求自适应增加网络节点(或)和增加模式网络协同工作,可以高效准确地发现和辨识用户意图,并以模式网络的最优输出作为教师样本来训练其它模式网络,以达到知识共享、提高辨识效率和精度;并根据用户意图在主动服务中的不同作用层次提出基于混合挖掘算法有针对性地进行意图的发现与辨识:用v-SVC的支持向量学习算法对用户的偏好和意图进行学习和辨识,反映用户的状态和所处的角色;用概念层次生成算法对用户服务属性层次化,获得用户的服务焦点;借助于模糊聚类算法来辨识用户所期望的服务质量或等级。
(3)提出了服务命中策略和小世界模型下的Web智能路由算法
考虑在大量冗余、相近的服务信息中和分布式的服务注册库中高效发现所需服务,提出了服务命中策略并通过相近度计算获取相近的可替换服务,解决高效服务命中和服务绑定失效的问题,并根据服务网库的分布独立性,提出基于资源最优的分布式服务网库搜索算法。还依据小世界网络具有特征路径短、聚类度大的特征和服务聚集性,将提供Web服务的对等节点构造成为具有小世界属性的网络,在服务查询和路由过程中可以提高效率和减少通信量。Web服务路由凭借其虚名称和路由感知机制,在SOAP中方便地实现路由路径的指定和装载。借助于基本蚁群算法,提出了在小世界网络模型中基于QoS约束下的智能路由算法。
(4)提出了基于反射中间件的服务失效处理方法
服务失效是影响服务高可用的制约因素,对于Web主动服务就需要对服务进行必要的动态配置和优化。利用反射中间件技术,将其配置在服务器和客户端捕捉到服务失效的状态,来调整和配置服务以适应服务的内外部环节的变化和要求,并利用混合神经网络作为反射中间件的检测机制。
(5)提出了一种基于QoS上下文反馈控制机制的服务组合方法
QoS是Web服务关键因素,从基于QoS的服务发现机制和基于QoS的服务合成机制基础上提出了QoS指标的上下文模型,并依据此模型来利用反馈控制机理,使用遗传算法作为控制器对QoS上下文的各项指标进行调节,并在备选的服务中发现所需最优的服务。
The Communication and interaction have rapidly changed by Web Technology and application system based on Internet. The Internet is now undergoing an evolution from a simple platform for information sharing to an open distributed computing infrastructure. With more and more data resources, computing resources and applications accessible via the Internet and web pages for public usage, resource sharing and application integration across organizational boundaries. In recent years, the concept services in open of network has been proposed as a mean of abstracting and wrapping environment, which makes Web service the natural way for dynamic resource aggregation and flexible application integration. Especially, along with the features of active computing, human centered and enhancing customer experience in services, which make Web active services become a kernel on SOC (Service Oriented Computing).
Implementing Web active services makes possible for information integration and interaction across organizational boundaries and enterprise interior depend upon unite clients, services, and operation together. The main contributions of this dissertation are summarized as fellows:
(1) The WASM (Web Active Services Model) that has“push”and“draw”two ways character is proposed.
Based on framework of active services and features of actives computing, the key technologies and implementation methods in the WASM are presented. Firstly, discovery and recognizing the asker of services to know its requirement, intention, QoS, and level of services; Secondly, Querying and discovering services information in registry of services; finally, binding proper services’URI to get it that meet user needs.
(2) A PENN and Based on hybrids policies algorithm are discussed
The PENN (Patterned Extendable Neural Network) is presented for discovering and recognizing user intention by selecting pro-pattern and adjusting number of latent layer node and/or increases pattern cooperation to meet discovering and recognizing needs. Taking an optimum pattern output as teacher train other patterns for sharing knowledge and improving efficiency and precision. The hybrid algorithm is proposed based on the different activities of user intention in Web initiative services. The preference learning with v -SVC provide effective preference recognition and role selection for user intention. The service focus point will be found with concept hierarchy algorithm, which conceptualizes service attributes. Using fuzzy clustering for user desire level or quality of services is feasible decision.
(3) The policy of services hitting and Based on small World model Web routing algorithm are proposed
How to discover required services in abundant redundant and similar service that record in databases which possibly have distributed features? The policy of services hitting is introduced, which effectively solves problem of services hitting, and process invalidation of services binding through similarity degree computing and sorting. Because of distributing and independency of services net database, a resource optimization search algorithm is proposed. Becaude the small world networks have a short length of characteristic path and evident attention of clustering, the efficiency of communication is improved in Web services querying and routing on the network which has small-world features and is constructed by some peer to peer services that regard as vertex in graph. Web service depends on virtual name and routing aware mechanism in expediently implement routing appoint and load in SOAP. Based on basic ant colony algorithm, the QoS constrained Ant colony Algorithm is presented.
(4) The mechanism to avoid Web services unavailability is proposed
Web services’high usability is restrained by Services unavailability. The reflection technologies are presented to improving Web services self-adaptive and robust ability to modify and optimize to Web services. The reflection layers are deployed in client’s and server’s sides to catch the traps that are some status of Web services unavailability. The reflection layers can adjust the internal structures and states of services, which avoid services unavailability in time and make services adapt to environment changing. The Hierarchy mixture of expert neural network as a detector in reflective middleware is introduced.
(5) The method of Services composition based on QoS mode is proposed
One of key factors is QoS for obtaining services. The QoS context is presented to deal with the different circumstance in compositing services and discovering services. Based on QoS context model, the candidate services are selected and compounded by QoS control system in which the genetic algorithm as controller to ensure to select suitable web services’QoS in the feedback system.
引文
[1] Paul Grefen, Heiko Ludwig, Asit Dan, et al, An analysis of web services support for dynamic business process outsourcing, Information and Software Technology, 2006, 48(11): 1115~1134.
[2] Benatallah B, Casati F, Toumani F. Web services conversation modeling: a cornerstone for e-business automation, IEEE Internet Computing, 2004, 8(1):46~54.
[3] Wendy L. Currie, Mihir A, Value creation in web services: An integrative model, The Journal of Strategic Information Systems, 2006, 15(2): 153~174.
[4] Clark D., Next-generation web services, IEEE Internet Computing, 2002. 6(2):12~14.
[5] Chen Huamin, Mohapatra Prasant, Using service brokers for accessing backend servers for web applications, Journal of Network and Computer Applications, 2005, 28(1): 57~74.
[6] Baldoni Matteo, Baroglio Cristina, Martelli, et al, Reasoning About Interaction Protocols for Web Service Composition, Electronic Notes in Theoretical Computer Science, 2004, 105(10): 21~36.
[7]岳昆,王晓玲,周傲英, Web服务核心支撑技术:研究综述,软件学报, 2004, 15(3): 428~442.
[8] Sabou Marta, Wroe Chris, Goble Carole, et al, Learning domain ontologies for semantic Web service descriptions, Web Semantics: Science, Services and Agents on the World Wide Web, 2005, 3(4): 340~365.
[9] Wang Shuying, Shen Weiming, Hao Qi, An agent-based Web service workflow model for inter-enterprise collaboration, Expert Systems with Applications,2006, 31(41): 787~799.
[10] Swamynathan S., Kannan A., Geetha T.V., Composite event monitoring in XML repositories using generic rule framework for providing reactive e-services, Decision Support Systems, 2006, 42( 1): 79~88.
[11] Jeroen J. van der Ham, Dijkstra Freek, Travostino Franco, et al, Using RDF to describe networks Future Generation Computer Systems, 2006, 22(8): 862~867.
[12] Shuying Wang, Weiming Shen, Qi Hao, An agent-based Web service workflow model for inter-enterprise collaboration, Expert Systems with Applications, 2006, 31(4): 787~799.
[13] Mennie D, Pagurek B. A runtime composition service creation and deployment and its application in internet security, E-commerce and software provision, In: Proc. Of the 25th Annual Int'1 computer software and Application Conf., (COMPSAC 2001), Chicago: IEEE Computer Society Press, 2001, 371~376.
[14] Kuter Ugur, Sirin Evren, Parsia Bijan, et al, Information gathering during planning for Web Service composition, Web Semantics: Science, Services and Agents on the World Wide Web, 2005, 3( 2-3): 183~205.
[15] Tosic Vladimir, Pagurek Bernard, Patel Kruti, et al, Management applications of the Web Service Offerings Language (WSOL), Information Systems, 2005, 30(7): 564~586.
[16] Kleiner E, Roscoe A.W, On the Relationship between Web Services Security and Traditional Protocols, Electronic Notes in Theoretical Computer Science, 2006, 155(12): 583~603..
[17] Limam Noura, Ziembicki Joanna, Ahmed Reaz, et al, OSDA: Open service discovery architecture for efficient cross-domain service provisioning, Computer Communications, 2007, 30(3): 546~563.
[18] Chakraborty D, Perich F, Avancha S,et al, Semantic service discovery for M-Commerce application, In: Proc of the 20th Symposium on Reliable Distribute System, Workshop on Reliable and Secure Application in Mobile Environment.2001.
[19] Chakraborty D, Joshi A, Yesha Y, et al. GSD: A novel Group-based service s discovery protocol for MANETS. In: Proc Of the 4th IEEE conf, on mobile and wireless Communications Networks (MWCN2002).
[20] Paolo D’Onorio De Meo, Danilo Carrabino, Nico Sanna, et al, A high performance grid-web service framework for the identification of‘conserved sequence tags’, Future Generation Computer Systems, 2007, 23(3): 371~381.
[21] Serena Pastore, The service discovery methods issue: A web services UDDI specification framework integrated in a grid environment, Journal of Network and Computer Applications, In Press, Corrected Proof, Available online 30 May 2006.
[22] Shi Zhongzhi, Huang He, Luo Jiewen, et al, Agent-based grid computing, Applied Mathematical Modeling, 2006, 30(7): 629~640.
[23] Foster I, Kessleman C, The Grid: Blueprint for a new computing infrastructure, San Francisco: Morgan Kaufman Publisher, 1999, 167~285.
[24] Weiser M, The computer for the twenty-first century, Scientific American, 1991, 265(3): 94~104.
[25] Dertouzos M, The future of computing, Scientific American, 1999, 282(3): 52~63.
[26]徐光右,史元春,谢伟凯,普适计算,计算机学报, 2003, 26(9): 1042~1050.
[27] Georgios John Fakas, Bill Karakostas, A peer to peer (P2P) architecture for dynamic workflow management, Information and Software Technology, 2004, 46(6): 423~431.
[28] Mohania Mukesh, Building web warehouse for semi-structured data , Data & Knowledge Engineering, 2001, 39(2): 101~103.
[29] Kimball Ralph, Merz Richard,张丽萍译, Web数据仓库构建指南,北京:清华大学出版社, 2005, 14~24.
[30] Sourav S, Bhowmick, Wee Keong Ng,et al, Constraint-driven join processing in a Web Warehouse, Data & Knowledge Engineering, 2003, 45( 1): 33~78.
[31] Sourav S, Bhowmick, Wee Keong Ng, et al, Anatomy of the coupling query in a web warehouse, Information and Software Technology, 2002, 44( 9): 513~539.
[32] Aristides Triantafillakis, Panagiotis Kanellis, Drakoulis Martakos, Data warehouse clustering on the web , European Journal of Operational Research, 2005, 160(2): 353~364.
[33] Federico Michele Facca, Pier Luca Lanzi, Mining interesting knowledge from weblogs: a survey, Data & Knowledge Engineering, 2005, 53(3): 225~241.
[34] Runkler T. A, Bezdek J. C, Web mining with relational clustering, International Journal of Approximate Reasoning, 2003, 32(2-3): 217~236.
[35] Li Hua-Fu, Lee Suh-Yin, Shan Man-Kwan, DSM-PLW: Single-pass mining of path traversal patterns over streaming Web click-sequences, Computer Networks, 2006, 50(10): 1474~1487.
[36]张尧学,方存好,主动服务的概念架构和实现,北京:科学出版, 2005, 29~41.
[37] Kim Kwang In, Jung Keechul, Kim Hang Joon, Face Recognition Using Kernels Principal Component Analysis, IEEE Signal Processing Letters, 2002, 9(2): 40~42.
[38]张有为,人机自然交互,北京:国防工业出版社, 2005, 27~142.
[39] Chen Ing-Ray, DaSilva Luiz A., Midkiff Scott F., Editorial: Mobile and Pervasive Computing, Computer, 2004, 47(4): 404~415.
[40] Chakraborty Dipanjan, Anupam Joshi, Yelena Yesha, et al, Toward Distributed Service Discovery in Pervasive Computing Environments, IEEE Trans. Mob. Computing, 2006, 5(2): 97~112.
[41] Coen M, The future of human computer interaction or how I learned to stop worrying and love my intelligent room, IEEE intelligent systems, 1999, 4(3-4): 8~19.
[42] Brumitt B, Meyers B, Krumm J, et al. Easy Living: technologies for intelligent environments, Handhold ubiquitous computer, Bristol, UK, 2000: 30~36.
[43] Alexander J A, Mozer M C, Template-based procedures for neural network interpretation, Neural Networks, 1999, 12(3): 479~498.
[44] Lu Wei, Lu Hongtao, Chung Fu-Lai, Feature based watermarking using watermark template match Applied Mathematics and Computation, 2006, 177(1): 377~386.
[45] Andrew Lee, Mohammed Ibrahim, Emotional Attributes in Autonomic Computing Systems, DEXA Workshops, 2003: 681~685.
[46] James Newman, Bernard J. Baars, Sung-Bae Cho. A Neural Global Workspace Model forConscious Attention, Neural Networks 1997, 10(7)): 1195~1206.
[47] Lee Yugyung, Chun Soon Ae, James Geller, Web-Based Semantic Pervasive Computing Services, IEEE Intelligent Informatics Bulletin, 2004, 4: 4~15.
[48] Simon Haykin, Neural network a comprehensive foundation, Beijing: China machine press, 2004, 253~278.
[49] Suresh C, Kothari, Heekuck Oh, Neural Networks for Pattern Recognition, Advances in Computers, 1993, 37: 119~166.
[50] Sanaga Srinivasulu, Ashu Jain, A comparative analysis of training methods for artificial neural network rainfall–runoff models, Applied Soft Computing, 2006, 6(3): 295~306.
[51] Kiyotoshi Matsuoka, Masahiro Ohoya, Mitsuru Kawamoto, A neural net for blind separation of non-stationary signals, Neural Networks, 1995, 8(3): 411~419.
[52]周志华,曹存根,神经网络及其应用,北京:清华大学出版社, 2004, 35~246.
[53] Wen Kuang-Wei , Peng Kuo-Fang Peng, Market segmentation via structured click stream analysis, Industrial Management and Data Systems,2002, 102(9): 493~502.
[54] Prodanov Plamen, Drygajlo Andrzej, Bayesian networks based multi-modality fusion for error handling in human–robot dialogues under noisy conditions, Speech Communication, 2005, 45(3): 231~248.
[55] Chen Zheng, Lin Fan, Liu Huan, et al, User Intention Modeling in Web Applications Using Data Mining, World Wide Web, 2002, 5(2): 181~192.
[56]邓乃杨,田英杰.数据挖掘中的新方法-支持向量机,北京:科学出版社, 2004.
[57] Gary William Flake, Steve Lawrence, Efficient SVM Regression Training with SMO, Machine Learning, 2002,46(1-3): 271~290.
[58] S. Ali, K. Smith, Matching SVM Kernel's Suitability to Data Characteristics Using Tree by Fuzzy C-means Clustering, HIS 2003: 553~562.
[59] Graeme S. Chambers, Svetha Venkatesh, et al, Hierarchical Recognition of Intentional Human Gestures for Sports Video Annotation, ICPR,2002, (2): 1082~1085.
[60] Han Jiawei, Fu Yongjian, Dynamic Generation and Refinement of Concept Hierarchies for Knowledge Discovery in Databases, KDD Workshop, 1994: 157~168.
[61] Venkateswarlu N B, Raju P S V S K, Fast ISODATA clustering algorithms, Pattern Recognition, 1992, 25(3): 335~342.
[62]吴敏, Web Service访问控制机制及其整合研究, [博士学位论文],上海,东华大学, 2006.
[63] Valérie Issarny, Daniele Sacchetti, Ferda Tartanoglu, et al, Developing Ambient Intelligence Systems: A Solution based on Web Services, Automation Software Engineer, 2005, 12(1): 101~137.
[64]胡建强,服务发现若干关键问题研究, [博士学位论文],长沙,国防科技大学, 2005.
[65] Burstein M H, Hobbs J R, Lassila O, et al, DAML-S: Web services description for the semantic Web, In: Horrocks, ed. Proc. Of the Int’1 Semantic Web conf. Sardinia, Springer-Verlag, 2002, 348~363.
[66] Christos Makris, Yannis Panagis, Evangelos Sakkopoulos, et al, Efficient and adaptive discovery techniques of Web Services handling large data sets, Journal of Systems and Software, 2006, 79(4): 480~495.
[67] Paul Grefen, Heiko Ludwig, Asit Dan, et al, An analysis of web services support for dynamic business process outsourcing, Information and Software Technology, 2006, 48(11): 1115~1134.
[68] Pautasso Cesare, Alonso Gustavo, Flexible Binding for Reusable Composition of Web Services, Software Composition, 2005, 151~166.
[69] Pullen J Mark, Brunton Ryan, Brutzman Don, et al, Using Web services to integrate heterogeneous simulations in a grid environment, Future Generation Computer Systems, 2005, 21(1): 97~106.
[70]朱清新,离散和连续空间中的最优搜索理论,北京:科学出版社, 2005, 12~37.
[71] Richard M Karp, Judea Pearl, Searching for an Optimal Path in a Tree with Random Costs, Artif. Intell, 1983, 21(1-2): 99~116.
[72] Richard Monson-Haefel,崔洪斌,王爱民译, J2EE Web Services高级编程,北京:清华大学出版社, 2005, 125~201.
[73] D. J. Watts, Strogatz S H, Collective dynamics of‘small world’networks, Nature, 1998, 392: 440~442.
[74] J Kleinberg , The Small World phenomenon: An algorithmic perspective, ACM Symp on Theory of Computing, 2000.
[75] Wang Xiaofan, Chen Guanrong, Complex networks small-world scale-free and beyond, IEEE Circuits and Systems Magaxine, 2003, 3(1): 6~20.
[76] Keith Ballinger,巴林杰等译, .NET Web服务架构,北京:中国电力出版社, 2004,180~190.
[77] Olaf Sporns, Small-world connectivity, motif composition, and complexity of fractal neuronal connections, Biosystems, 2006, 85(1): 55~64.
[78] Carlos Handrey A. Ferraz, Hans J Herrmann, The Kauffman model on small-world topology, Physica A: Statistical Mechanics and its Applications, In Press, Corrected Proof, Available online 17 May 2006.
[79] Anjan Kumar Chandra, Subinay Dasgupta, A small world network of prime numbers, Physica A: Statistical Mechanics and its Applications, 2006, 357(3-4): 436~446.
[80] Jani Lahtinen, János Kertész, Kimmo Kaski, Sandpiles on Watts–Strogatz type small-worlds,Physica A: Statistical and Theoretical Physics, 2005, 349(3-4): 535~547.
[81]段海滨,蚁群算法原理及其应用,北京:科学出版社, 2005, 225~234.
[82] Wang Xingwei, Cao Jiannong, Cheng Hui et al, QoS multicast routing for multimedia group communications using intelligent computational methods, Computer Communications, 2006, 29(12): 2217~2229.
[83] Nejdl Wolfgang, Wolpers Martin, Siberski Wolf, et al, Super-peer-based routing strategies for RDF-based peer-to-peer networks, Web Semantics: Science, Services and Agents on the World Wide Web, 2004, 1(2): 177~186.
[84] Ronaldo A. Ferreira, Suresh Jagannathan, Ananth Grama, Locality in structured peer-to-peer networks, Journal of Parallel and Distributed Computing, 2006, 66(2): 257~273.
[85] Laura F. LandWeber, Lila Kari, The evolution of cellular computing: nature’s solution to a computational problem, Biosystems, 1999, 52(1-3): 3~13.
[86] Emilio G. Roselló, María J. Lado, Arturo J. Méndez, et al, A component framework for reusing a proprietary computer-aided engineering environment, Advances in Engineering Software, 2007, 38(4): 256~266.
[87] Abbas Heydarnoori, Farhad Mavaddat, Farhad Arbab, Towards an Automated Deployment Planner for Composition of Web Services as Software Components, Electronic Notes in Theoretical Computer Science, 2006, 160(8): 239~253.
[88] Agha Gul A., Kim Wooyoung, Actors: A unifying model for parallel and distributed computing, Journal of Systems Architecture, 1999, 45(15): 1263~1277.
[89] Marshall Byron, Chen Hsinchun, Madhusudan Therani, Matching knowledge elements in concept maps using a similarity flooding algorithm, Decision Support Systems, 2006, 42(3): 1290~1306.
[90] Lunney T. F., McCaughey A. J., Component based distributed systems– CORBA and EJB in context, Computer Physics Communications, 2000, 127(2-3): 207~214.
[91] Litiu R, Prakash A, DACIA: A mobile component framework for building adaptive distributed applications, Operating Systems Review, 2001, 35(2): 31~42.
[92]陶先平,吕建,张冠群等,一种移动agent结构化迁移机制的设计和实现,软件学报, 2000, 11(7): 918~923.
[93] Smith B. C., Procedural reflection in programming language, Cambridge Mass, MIT 1982.
[94]张云勇,张智江,刘锦德等.中间件技术原理与应用,北京:清华大学出版社,2004, 98~218.
[95]徐新卫,王有远,曹永忠,丁秋林,基于反射技术的Web服务失效处理,计算机工程与应用, 2007, 47(12): 6~9.
[96]杜炤,王小鸽,陈渝,反射中间件综述,计算机研究与发展,2005,42(12): 2041~2047.
[97] Maes P., Concepts and experiments in computational reflection, ACM SIGPLAN Notices, 1987, 22(10), 147~155.
[98] Coulson G., What is reflective middleware, http://boole.computer/org/dsonline/middleware/RMarticle1.htm, 2001.
[99]杨思忠,骆志刚,刘锦德,RECOM:一个反射中间件,计算机科学, 200l,28(7),112~117.
[100] Shimony Solomon Eyal, Domshlak Carmel, Complexity of probabilistic reasoning in directed-path singly-connected Bayes networks, Artifical Intelligence, 2003, 151(1-2): 213~225.
[101] Rossi Fabrice, Villa Nathalie, Support vector machine for functional data classification, Neural computing, 2006, 69(7-9): 78~102.
[102] Ang C. L., Luo M, Gay R. K. L, Knowledge-based approach to the generation of IDEF0 models, Computer Integrated Manufacturing Systems, 1995, 8(4): 279~290.
[103] Pablo A Estévez, Hélène Paugam-Moisy, Didier Puzenat et al, A scalable parallel algorithm for training a hierarchical mixture of neural experts, Parallel Computing, 2002, 28(6): 861~891.
[104] Moghrabi C., M. S. Eid, Modeling users through an expert system and a neural network [J] . Computers & Industrial Engineering, 1998, 35(3-4): 583~586.
[105]阎平凡,张长水,人工神经网络与模拟进化计算,北京:清华大学出版社, 2000, 268~279.
[106] Hu Tianming, Sung Sam Yuan, A hybrid EM approach to spatial clustering, Computational Statistics & Data Analysis, 2006, 50(5): 1188-1205.
[107] Simon Haykin,叶世伟等译,神经网络原理,北京:机械工业出版设, 2004, 253~278.
[108] Zhong Mingjun, Tang Huanwen, Chen Hongjun et al, An EM algorithm for learning sparse and over complete representations, Neural computing, 2004, 57(3): 469~476.
[109] Ng Shu-Kay, McLachlan Geoffrey J, Andy H. Lee, An incremental EM-based learning approach for on-line prediction of hospital resource utilization, Artificial Intelligence in Medicine, 2006,36(3): 257~267.
[110] Masahiro Kuroda, Michio Sakakihara, Accelerating the convergence of the EM algorithm using the vectorεalgorithm, Computational Statistics & Data Analysis, 2006, 51(3): 1549-1561.
[111] Zeng Liangzhao, Boualem Benatallah, marlon, et al, QoS-Aware Middleware for Web Services Composition, IEEE transactions on software engineering. 2004, 30(5): 311~327.
[112] Charif Yasmine, Sabouret Nicolas, An Overview of Semantic Web Services Composition Approaches, Electronic Notes in Theoretical Computer Science, 2006, 146(1): 33~42.
[113] Agarwal Vikas, Chafle Girish, Dasgupta Koustuv et al, Synthy: A system for end to endcomposition of web services, Web Semantics: Science, Services and Agents on the World Wide Web, 2005, 3(4): 311~339.
[114] Web Services Description Working Group.Web Services Description Language (WSDL) Version 1.2.March 2003.http//www.w3corg/TR/wsdl12/2003.
[115] BPEL4WS:Business Process Execution Language for Web Services version 1.1 May 2003.http://www-106.ibm.corn/developerworks/webservices/library/ws-bpel/2003.
[116] Kumar Akhil, Wainer Jacques, Meta workflows as a control and coordination mechanism for exception handling in workflow systems, Decision Support Systems, 2005, 40(1): 89~105.
[117] DAML Joint Committee, DAML Services (DAML-S) May 2003, http://www.dam1.org/services/2003.
[118] Sattanathan S., Narendra N.C., Maamar Z, Ontologies for Specifying and Reconciling Contexts of Web Services, Electronic Notes in Theoretical Computer Science, 2006, 146(1): 43~57.
[119] Younas Muhammad, Awan Irfan, Duce David, An efficient composition of Web services with active network support, Expert Systems with Applications, 2006, 31(4): 859~869.
[120]刘必欣,动态Web服务组合关键技术研究,[博士学位论文],北京,国防科学技术大学,2005。
[121]汤景凡,,动态Web服务组合的关键技术研究,[博士学位论文],浙江,浙江大学,2005。
[122] Zhang Chengwen, Su Sen, Chen Junliang, DiGA: Population diversity handling genetic algorithm for QoS-aware web services selection, Computer Communications, 2007, 30(5): 1082~1090.
[123] Zeng Liangzhao, Benatallah Boualem, marlon, et al, QoS-Aware Middleware for Web Services Composition, IEEE transactions on software engineering, 2004, 30(5): 311~327.
[124] Menasce D. A., QoS issues in web services, Internet Computering, 2002, 6(6): 72~75.
[125] RAN S. P., A model for web services discovery with QoS, ACM SIGCOM Exchanges, 2003, 4(1): 1~10.
[126]杨胜文,史美林,一种支持QoS约束的Web服务发现模型,计算机学报,2005, 28(4): 489~594。
[127]徐明伟,胡春明,刘旭东等,一种基于Web Service的分级QoS的研究与实现,计算机研究与发展,2005,42(4):669~675。
[128] Paurobally Shamimabi, Jennings Nicholas R.,Protocol engineering for web services conversations, Engineering Applications of Artificial Intelligence, 2005, 18(2): 237~254.
[129] Xie Xianchao, Geng Zhi,Zhao Qiang,Decomposition of structural learning about directed acyclic graphs,Artificial Intelligence, 2006, 170(4-5): 422～439.
[130] Sen Anup K., Bagchi Amitava, Zhang Weixiong, Average-case analysis of best-first search in two representative directed acyclic graphs, Artificial Intelligence, 2004, 155(1-2): 183~206.
[131]石静,丁长明,赵泽宇等,Web服务合成研究综述,计算机科学,2004,31(6): 54~58。
[132] Wang Ling, Zhang Liang, Da-Zhong Zheng, An effective hybrid genetic algorithm for flow shop scheduling with limited buffers, Computers & Operations Research, 2006, 33(10): 2960~2971.
[133] Altiparmak Fulya, Gen Mitsuo, Lin Lin, et al, A genetic algorithm approach for multi-objective optimization of supply chain networks, Computers & Industrial Engineering, 2006, 51(1): 196~215.
[134]徐新卫,丁秋林,基于QoS上下文的Web服务组合,华南理工大学,2007, 38(1): 106~111.
[135] Artail Hassan, Kahale Elie, MAWS: A platform-independent framework for mobile agents using Web services, Journal of Parallel and Distributed Computing, 2006, 66(3): 428~443.
[136] Matjaz B. Juric, Ivan Rozman, Bostjan Brumen, et al, Comparison of performance of Web services, WS-Security, RMI, and RMI–SSL, Journal of Systems and Software, 2006, 79(5): 689~700.
[137] Christos Doulkeridis, Nikos Loutas, Michalis Vazirgiannis, A System Architecture for Context-Aware Service Discovery, Electronic Notes in Theoretical Computer Science, 2006, 146(1): 101~116.
[138] Richard Monson-Haefel,崔洪斌,王爱民译,J2EE Web Services高级编程,北京:清华大学出版社,2005,363~459.
[139] Deepak Alur, John Crupi, Dan Malks, Core J2EE patterns,北京:科学出版社, 2004, 172~186.
[140] Shamimabi Paurobally, Nicholas R. Jennings, Protocol engineering for web services conversations, Engineering Applications of Artificial Intelligence, 2005, 18(2): 37~254.
[141] Konstantin Beznosov, Donald J. Flinn, Shirley Kawamoto, et al, and Bret Hartman introduction to Web services and their security, Information Security Technical Report, 2005, 10(1): 2~14.
[142] Lai Ray,周斌等译,J2EE平台Web Services,北京:电子工业出版社,2005,293~298.
[143] Thriskos P., Zintzaras E., Germenis A., DHLAS: A web-based information system for statistical genetic analysis of HLA population data, Computer Methods and Programs in Biomedicine, 2007, 85(3): 267~272.
[144] Lan Hongbo, Ding Yucheng, Hong Jun, et al, A web-based manufacturing service system for rapid product development, Computers in Industry, 2004, 54(1): 51~67.
[145] Merrilees Bill, Fenech Tino, from catalog to Web: B2B multi-channel marketing strategy,Industrial Marketing Management, 2007, 36(1): 44~49.
[146] Gupta Samir, Cadeaux Jack, Woodside Arch, Mapping network champion behavior in B2B electronic venturing, Industrial Marketing Management, 2005, 34(5): 495~503.
[147] Trastour David, Bartolini Claudio, Preist Chris, Semantic Web support for the business-to-business e-commerce pre-contractual lifecycle, Computer Networks, 2003, 42(5): 661~673.
[2] Benatallah B, Casati F, Toumani F. Web services conversation modeling: a cornerstone for e-business automation, IEEE Internet Computing, 2004, 8(1):46~54.
[3] Wendy L. Currie, Mihir A, Value creation in web services: An integrative model, The Journal of Strategic Information Systems, 2006, 15(2): 153~174.
[4] Clark D., Next-generation web services, IEEE Internet Computing, 2002. 6(2):12~14.
[5] Chen Huamin, Mohapatra Prasant, Using service brokers for accessing backend servers for web applications, Journal of Network and Computer Applications, 2005, 28(1): 57~74.
[6] Baldoni Matteo, Baroglio Cristina, Martelli, et al, Reasoning About Interaction Protocols for Web Service Composition, Electronic Notes in Theoretical Computer Science, 2004, 105(10): 21~36.
[7]岳昆,王晓玲,周傲英, Web服务核心支撑技术:研究综述,软件学报, 2004, 15(3): 428~442.
[8] Sabou Marta, Wroe Chris, Goble Carole, et al, Learning domain ontologies for semantic Web service descriptions, Web Semantics: Science, Services and Agents on the World Wide Web, 2005, 3(4): 340~365.
[9] Wang Shuying, Shen Weiming, Hao Qi, An agent-based Web service workflow model for inter-enterprise collaboration, Expert Systems with Applications,2006, 31(41): 787~799.
[10] Swamynathan S., Kannan A., Geetha T.V., Composite event monitoring in XML repositories using generic rule framework for providing reactive e-services, Decision Support Systems, 2006, 42( 1): 79~88.
[11] Jeroen J. van der Ham, Dijkstra Freek, Travostino Franco, et al, Using RDF to describe networks Future Generation Computer Systems, 2006, 22(8): 862~867.
[12] Shuying Wang, Weiming Shen, Qi Hao, An agent-based Web service workflow model for inter-enterprise collaboration, Expert Systems with Applications, 2006, 31(4): 787~799.
[13] Mennie D, Pagurek B. A runtime composition service creation and deployment and its application in internet security, E-commerce and software provision, In: Proc. Of the 25th Annual Int'1 computer software and Application Conf., (COMPSAC 2001), Chicago: IEEE Computer Society Press, 2001, 371~376.
[14] Kuter Ugur, Sirin Evren, Parsia Bijan, et al, Information gathering during planning for Web Service composition, Web Semantics: Science, Services and Agents on the World Wide Web, 2005, 3( 2-3): 183~205.
[15] Tosic Vladimir, Pagurek Bernard, Patel Kruti, et al, Management applications of the Web Service Offerings Language (WSOL), Information Systems, 2005, 30(7): 564~586.
[16] Kleiner E, Roscoe A.W, On the Relationship between Web Services Security and Traditional Protocols, Electronic Notes in Theoretical Computer Science, 2006, 155(12): 583~603..
[17] Limam Noura, Ziembicki Joanna, Ahmed Reaz, et al, OSDA: Open service discovery architecture for efficient cross-domain service provisioning, Computer Communications, 2007, 30(3): 546~563.
[18] Chakraborty D, Perich F, Avancha S,et al, Semantic service discovery for M-Commerce application, In: Proc of the 20th Symposium on Reliable Distribute System, Workshop on Reliable and Secure Application in Mobile Environment.2001.
[19] Chakraborty D, Joshi A, Yesha Y, et al. GSD: A novel Group-based service s discovery protocol for MANETS. In: Proc Of the 4th IEEE conf, on mobile and wireless Communications Networks (MWCN2002).
[20] Paolo D’Onorio De Meo, Danilo Carrabino, Nico Sanna, et al, A high performance grid-web service framework for the identification of‘conserved sequence tags’, Future Generation Computer Systems, 2007, 23(3): 371~381.
[21] Serena Pastore, The service discovery methods issue: A web services UDDI specification framework integrated in a grid environment, Journal of Network and Computer Applications, In Press, Corrected Proof, Available online 30 May 2006.
[22] Shi Zhongzhi, Huang He, Luo Jiewen, et al, Agent-based grid computing, Applied Mathematical Modeling, 2006, 30(7): 629~640.
[23] Foster I, Kessleman C, The Grid: Blueprint for a new computing infrastructure, San Francisco: Morgan Kaufman Publisher, 1999, 167~285.
[24] Weiser M, The computer for the twenty-first century, Scientific American, 1991, 265(3): 94~104.
[25] Dertouzos M, The future of computing, Scientific American, 1999, 282(3): 52~63.
[26]徐光右,史元春,谢伟凯,普适计算,计算机学报, 2003, 26(9): 1042~1050.
[27] Georgios John Fakas, Bill Karakostas, A peer to peer (P2P) architecture for dynamic workflow management, Information and Software Technology, 2004, 46(6): 423~431.
[28] Mohania Mukesh, Building web warehouse for semi-structured data , Data & Knowledge Engineering, 2001, 39(2): 101~103.
[29] Kimball Ralph, Merz Richard,张丽萍译, Web数据仓库构建指南,北京:清华大学出版社, 2005, 14~24.
[30] Sourav S, Bhowmick, Wee Keong Ng,et al, Constraint-driven join processing in a Web Warehouse, Data & Knowledge Engineering, 2003, 45( 1): 33~78.
[31] Sourav S, Bhowmick, Wee Keong Ng, et al, Anatomy of the coupling query in a web warehouse, Information and Software Technology, 2002, 44( 9): 513~539.
[32] Aristides Triantafillakis, Panagiotis Kanellis, Drakoulis Martakos, Data warehouse clustering on the web , European Journal of Operational Research, 2005, 160(2): 353~364.
[33] Federico Michele Facca, Pier Luca Lanzi, Mining interesting knowledge from weblogs: a survey, Data & Knowledge Engineering, 2005, 53(3): 225~241.
[34] Runkler T. A, Bezdek J. C, Web mining with relational clustering, International Journal of Approximate Reasoning, 2003, 32(2-3): 217~236.
[35] Li Hua-Fu, Lee Suh-Yin, Shan Man-Kwan, DSM-PLW: Single-pass mining of path traversal patterns over streaming Web click-sequences, Computer Networks, 2006, 50(10): 1474~1487.
[36]张尧学,方存好,主动服务的概念架构和实现,北京:科学出版, 2005, 29~41.
[37] Kim Kwang In, Jung Keechul, Kim Hang Joon, Face Recognition Using Kernels Principal Component Analysis, IEEE Signal Processing Letters, 2002, 9(2): 40~42.
[38]张有为,人机自然交互,北京:国防工业出版社, 2005, 27~142.
[39] Chen Ing-Ray, DaSilva Luiz A., Midkiff Scott F., Editorial: Mobile and Pervasive Computing, Computer, 2004, 47(4): 404~415.
[40] Chakraborty Dipanjan, Anupam Joshi, Yelena Yesha, et al, Toward Distributed Service Discovery in Pervasive Computing Environments, IEEE Trans. Mob. Computing, 2006, 5(2): 97~112.
[41] Coen M, The future of human computer interaction or how I learned to stop worrying and love my intelligent room, IEEE intelligent systems, 1999, 4(3-4): 8~19.
[42] Brumitt B, Meyers B, Krumm J, et al. Easy Living: technologies for intelligent environments, Handhold ubiquitous computer, Bristol, UK, 2000: 30~36.
[43] Alexander J A, Mozer M C, Template-based procedures for neural network interpretation, Neural Networks, 1999, 12(3): 479~498.
[44] Lu Wei, Lu Hongtao, Chung Fu-Lai, Feature based watermarking using watermark template match Applied Mathematics and Computation, 2006, 177(1): 377~386.
[45] Andrew Lee, Mohammed Ibrahim, Emotional Attributes in Autonomic Computing Systems, DEXA Workshops, 2003: 681~685.
[46] James Newman, Bernard J. Baars, Sung-Bae Cho. A Neural Global Workspace Model forConscious Attention, Neural Networks 1997, 10(7)): 1195~1206.
[47] Lee Yugyung, Chun Soon Ae, James Geller, Web-Based Semantic Pervasive Computing Services, IEEE Intelligent Informatics Bulletin, 2004, 4: 4~15.
[48] Simon Haykin, Neural network a comprehensive foundation, Beijing: China machine press, 2004, 253~278.
[49] Suresh C, Kothari, Heekuck Oh, Neural Networks for Pattern Recognition, Advances in Computers, 1993, 37: 119~166.
[50] Sanaga Srinivasulu, Ashu Jain, A comparative analysis of training methods for artificial neural network rainfall–runoff models, Applied Soft Computing, 2006, 6(3): 295~306.
[51] Kiyotoshi Matsuoka, Masahiro Ohoya, Mitsuru Kawamoto, A neural net for blind separation of non-stationary signals, Neural Networks, 1995, 8(3): 411~419.
[52]周志华,曹存根,神经网络及其应用,北京:清华大学出版社, 2004, 35~246.
[53] Wen Kuang-Wei , Peng Kuo-Fang Peng, Market segmentation via structured click stream analysis, Industrial Management and Data Systems,2002, 102(9): 493~502.
[54] Prodanov Plamen, Drygajlo Andrzej, Bayesian networks based multi-modality fusion for error handling in human–robot dialogues under noisy conditions, Speech Communication, 2005, 45(3): 231~248.
[55] Chen Zheng, Lin Fan, Liu Huan, et al, User Intention Modeling in Web Applications Using Data Mining, World Wide Web, 2002, 5(2): 181~192.
[56]邓乃杨,田英杰.数据挖掘中的新方法-支持向量机,北京:科学出版社, 2004.
[57] Gary William Flake, Steve Lawrence, Efficient SVM Regression Training with SMO, Machine Learning, 2002,46(1-3): 271~290.
[58] S. Ali, K. Smith, Matching SVM Kernel's Suitability to Data Characteristics Using Tree by Fuzzy C-means Clustering, HIS 2003: 553~562.
[59] Graeme S. Chambers, Svetha Venkatesh, et al, Hierarchical Recognition of Intentional Human Gestures for Sports Video Annotation, ICPR,2002, (2): 1082~1085.
[60] Han Jiawei, Fu Yongjian, Dynamic Generation and Refinement of Concept Hierarchies for Knowledge Discovery in Databases, KDD Workshop, 1994: 157~168.
[61] Venkateswarlu N B, Raju P S V S K, Fast ISODATA clustering algorithms, Pattern Recognition, 1992, 25(3): 335~342.
[62]吴敏, Web Service访问控制机制及其整合研究, [博士学位论文],上海,东华大学, 2006.
[63] Valérie Issarny, Daniele Sacchetti, Ferda Tartanoglu, et al, Developing Ambient Intelligence Systems: A Solution based on Web Services, Automation Software Engineer, 2005, 12(1): 101~137.
[64]胡建强,服务发现若干关键问题研究, [博士学位论文],长沙,国防科技大学, 2005.
[65] Burstein M H, Hobbs J R, Lassila O, et al, DAML-S: Web services description for the semantic Web, In: Horrocks, ed. Proc. Of the Int’1 Semantic Web conf. Sardinia, Springer-Verlag, 2002, 348~363.
[66] Christos Makris, Yannis Panagis, Evangelos Sakkopoulos, et al, Efficient and adaptive discovery techniques of Web Services handling large data sets, Journal of Systems and Software, 2006, 79(4): 480~495.
[67] Paul Grefen, Heiko Ludwig, Asit Dan, et al, An analysis of web services support for dynamic business process outsourcing, Information and Software Technology, 2006, 48(11): 1115~1134.
[68] Pautasso Cesare, Alonso Gustavo, Flexible Binding for Reusable Composition of Web Services, Software Composition, 2005, 151~166.
[69] Pullen J Mark, Brunton Ryan, Brutzman Don, et al, Using Web services to integrate heterogeneous simulations in a grid environment, Future Generation Computer Systems, 2005, 21(1): 97~106.
[70]朱清新,离散和连续空间中的最优搜索理论,北京:科学出版社, 2005, 12~37.
[71] Richard M Karp, Judea Pearl, Searching for an Optimal Path in a Tree with Random Costs, Artif. Intell, 1983, 21(1-2): 99~116.
[72] Richard Monson-Haefel,崔洪斌,王爱民译, J2EE Web Services高级编程,北京:清华大学出版社, 2005, 125~201.
[73] D. J. Watts, Strogatz S H, Collective dynamics of‘small world’networks, Nature, 1998, 392: 440~442.
[74] J Kleinberg , The Small World phenomenon: An algorithmic perspective, ACM Symp on Theory of Computing, 2000.
[75] Wang Xiaofan, Chen Guanrong, Complex networks small-world scale-free and beyond, IEEE Circuits and Systems Magaxine, 2003, 3(1): 6~20.
[76] Keith Ballinger,巴林杰等译, .NET Web服务架构,北京:中国电力出版社, 2004,180~190.
[77] Olaf Sporns, Small-world connectivity, motif composition, and complexity of fractal neuronal connections, Biosystems, 2006, 85(1): 55~64.
[78] Carlos Handrey A. Ferraz, Hans J Herrmann, The Kauffman model on small-world topology, Physica A: Statistical Mechanics and its Applications, In Press, Corrected Proof, Available online 17 May 2006.
[79] Anjan Kumar Chandra, Subinay Dasgupta, A small world network of prime numbers, Physica A: Statistical Mechanics and its Applications, 2006, 357(3-4): 436~446.
[80] Jani Lahtinen, János Kertész, Kimmo Kaski, Sandpiles on Watts–Strogatz type small-worlds,Physica A: Statistical and Theoretical Physics, 2005, 349(3-4): 535~547.
[81]段海滨,蚁群算法原理及其应用,北京:科学出版社, 2005, 225~234.
[82] Wang Xingwei, Cao Jiannong, Cheng Hui et al, QoS multicast routing for multimedia group communications using intelligent computational methods, Computer Communications, 2006, 29(12): 2217~2229.
[83] Nejdl Wolfgang, Wolpers Martin, Siberski Wolf, et al, Super-peer-based routing strategies for RDF-based peer-to-peer networks, Web Semantics: Science, Services and Agents on the World Wide Web, 2004, 1(2): 177~186.
[84] Ronaldo A. Ferreira, Suresh Jagannathan, Ananth Grama, Locality in structured peer-to-peer networks, Journal of Parallel and Distributed Computing, 2006, 66(2): 257~273.
[85] Laura F. LandWeber, Lila Kari, The evolution of cellular computing: nature’s solution to a computational problem, Biosystems, 1999, 52(1-3): 3~13.
[86] Emilio G. Roselló, María J. Lado, Arturo J. Méndez, et al, A component framework for reusing a proprietary computer-aided engineering environment, Advances in Engineering Software, 2007, 38(4): 256~266.
[87] Abbas Heydarnoori, Farhad Mavaddat, Farhad Arbab, Towards an Automated Deployment Planner for Composition of Web Services as Software Components, Electronic Notes in Theoretical Computer Science, 2006, 160(8): 239~253.
[88] Agha Gul A., Kim Wooyoung, Actors: A unifying model for parallel and distributed computing, Journal of Systems Architecture, 1999, 45(15): 1263~1277.
[89] Marshall Byron, Chen Hsinchun, Madhusudan Therani, Matching knowledge elements in concept maps using a similarity flooding algorithm, Decision Support Systems, 2006, 42(3): 1290~1306.
[90] Lunney T. F., McCaughey A. J., Component based distributed systems– CORBA and EJB in context, Computer Physics Communications, 2000, 127(2-3): 207~214.
[91] Litiu R, Prakash A, DACIA: A mobile component framework for building adaptive distributed applications, Operating Systems Review, 2001, 35(2): 31~42.
[92]陶先平,吕建,张冠群等,一种移动agent结构化迁移机制的设计和实现,软件学报, 2000, 11(7): 918~923.
[93] Smith B. C., Procedural reflection in programming language, Cambridge Mass, MIT 1982.
[94]张云勇,张智江,刘锦德等.中间件技术原理与应用,北京:清华大学出版社,2004, 98~218.
[95]徐新卫,王有远,曹永忠,丁秋林,基于反射技术的Web服务失效处理,计算机工程与应用, 2007, 47(12): 6~9.
[96]杜炤,王小鸽,陈渝,反射中间件综述,计算机研究与发展,2005,42(12): 2041~2047.
[97] Maes P., Concepts and experiments in computational reflection, ACM SIGPLAN Notices, 1987, 22(10), 147~155.
[98] Coulson G., What is reflective middleware, http://boole.computer/org/dsonline/middleware/RMarticle1.htm, 2001.
[99]杨思忠,骆志刚,刘锦德,RECOM:一个反射中间件,计算机科学, 200l,28(7),112~117.
[100] Shimony Solomon Eyal, Domshlak Carmel, Complexity of probabilistic reasoning in directed-path singly-connected Bayes networks, Artifical Intelligence, 2003, 151(1-2): 213~225.
[101] Rossi Fabrice, Villa Nathalie, Support vector machine for functional data classification, Neural computing, 2006, 69(7-9): 78~102.
[102] Ang C. L., Luo M, Gay R. K. L, Knowledge-based approach to the generation of IDEF0 models, Computer Integrated Manufacturing Systems, 1995, 8(4): 279~290.
[103] Pablo A Estévez, Hélène Paugam-Moisy, Didier Puzenat et al, A scalable parallel algorithm for training a hierarchical mixture of neural experts, Parallel Computing, 2002, 28(6): 861~891.
[104] Moghrabi C., M. S. Eid, Modeling users through an expert system and a neural network [J] . Computers & Industrial Engineering, 1998, 35(3-4): 583~586.
[105]阎平凡,张长水,人工神经网络与模拟进化计算,北京:清华大学出版社, 2000, 268~279.
[106] Hu Tianming, Sung Sam Yuan, A hybrid EM approach to spatial clustering, Computational Statistics & Data Analysis, 2006, 50(5): 1188-1205.
[107] Simon Haykin,叶世伟等译,神经网络原理,北京:机械工业出版设, 2004, 253~278.
[108] Zhong Mingjun, Tang Huanwen, Chen Hongjun et al, An EM algorithm for learning sparse and over complete representations, Neural computing, 2004, 57(3): 469~476.
[109] Ng Shu-Kay, McLachlan Geoffrey J, Andy H. Lee, An incremental EM-based learning approach for on-line prediction of hospital resource utilization, Artificial Intelligence in Medicine, 2006,36(3): 257~267.
[110] Masahiro Kuroda, Michio Sakakihara, Accelerating the convergence of the EM algorithm using the vectorεalgorithm, Computational Statistics & Data Analysis, 2006, 51(3): 1549-1561.
[111] Zeng Liangzhao, Boualem Benatallah, marlon, et al, QoS-Aware Middleware for Web Services Composition, IEEE transactions on software engineering. 2004, 30(5): 311~327.
[112] Charif Yasmine, Sabouret Nicolas, An Overview of Semantic Web Services Composition Approaches, Electronic Notes in Theoretical Computer Science, 2006, 146(1): 33~42.
[113] Agarwal Vikas, Chafle Girish, Dasgupta Koustuv et al, Synthy: A system for end to endcomposition of web services, Web Semantics: Science, Services and Agents on the World Wide Web, 2005, 3(4): 311~339.
[114] Web Services Description Working Group.Web Services Description Language (WSDL) Version 1.2.March 2003.http//www.w3corg/TR/wsdl12/2003.
[115] BPEL4WS:Business Process Execution Language for Web Services version 1.1 May 2003.http://www-106.ibm.corn/developerworks/webservices/library/ws-bpel/2003.
[116] Kumar Akhil, Wainer Jacques, Meta workflows as a control and coordination mechanism for exception handling in workflow systems, Decision Support Systems, 2005, 40(1): 89~105.
[117] DAML Joint Committee, DAML Services (DAML-S) May 2003, http://www.dam1.org/services/2003.
[118] Sattanathan S., Narendra N.C., Maamar Z, Ontologies for Specifying and Reconciling Contexts of Web Services, Electronic Notes in Theoretical Computer Science, 2006, 146(1): 43~57.
[119] Younas Muhammad, Awan Irfan, Duce David, An efficient composition of Web services with active network support, Expert Systems with Applications, 2006, 31(4): 859~869.
[120]刘必欣,动态Web服务组合关键技术研究,[博士学位论文],北京,国防科学技术大学,2005。
[121]汤景凡,,动态Web服务组合的关键技术研究,[博士学位论文],浙江,浙江大学,2005。
[122] Zhang Chengwen, Su Sen, Chen Junliang, DiGA: Population diversity handling genetic algorithm for QoS-aware web services selection, Computer Communications, 2007, 30(5): 1082~1090.
[123] Zeng Liangzhao, Benatallah Boualem, marlon, et al, QoS-Aware Middleware for Web Services Composition, IEEE transactions on software engineering, 2004, 30(5): 311~327.
[124] Menasce D. A., QoS issues in web services, Internet Computering, 2002, 6(6): 72~75.
[125] RAN S. P., A model for web services discovery with QoS, ACM SIGCOM Exchanges, 2003, 4(1): 1~10.
[126]杨胜文,史美林,一种支持QoS约束的Web服务发现模型,计算机学报,2005, 28(4): 489~594。
[127]徐明伟,胡春明,刘旭东等,一种基于Web Service的分级QoS的研究与实现,计算机研究与发展,2005,42(4):669~675。
[128] Paurobally Shamimabi, Jennings Nicholas R.,Protocol engineering for web services conversations, Engineering Applications of Artificial Intelligence, 2005, 18(2): 237~254.
[129] Xie Xianchao, Geng Zhi,Zhao Qiang,Decomposition of structural learning about directed acyclic graphs,Artificial Intelligence, 2006, 170(4-5): 422～439.
[130] Sen Anup K., Bagchi Amitava, Zhang Weixiong, Average-case analysis of best-first search in two representative directed acyclic graphs, Artificial Intelligence, 2004, 155(1-2): 183~206.
[131]石静,丁长明,赵泽宇等,Web服务合成研究综述,计算机科学,2004,31(6): 54~58。
[132] Wang Ling, Zhang Liang, Da-Zhong Zheng, An effective hybrid genetic algorithm for flow shop scheduling with limited buffers, Computers & Operations Research, 2006, 33(10): 2960~2971.
[133] Altiparmak Fulya, Gen Mitsuo, Lin Lin, et al, A genetic algorithm approach for multi-objective optimization of supply chain networks, Computers & Industrial Engineering, 2006, 51(1): 196~215.
[134]徐新卫,丁秋林,基于QoS上下文的Web服务组合,华南理工大学,2007, 38(1): 106~111.
[135] Artail Hassan, Kahale Elie, MAWS: A platform-independent framework for mobile agents using Web services, Journal of Parallel and Distributed Computing, 2006, 66(3): 428~443.
[136] Matjaz B. Juric, Ivan Rozman, Bostjan Brumen, et al, Comparison of performance of Web services, WS-Security, RMI, and RMI–SSL, Journal of Systems and Software, 2006, 79(5): 689~700.
[137] Christos Doulkeridis, Nikos Loutas, Michalis Vazirgiannis, A System Architecture for Context-Aware Service Discovery, Electronic Notes in Theoretical Computer Science, 2006, 146(1): 101~116.
[138] Richard Monson-Haefel,崔洪斌,王爱民译,J2EE Web Services高级编程,北京:清华大学出版社,2005,363~459.
[139] Deepak Alur, John Crupi, Dan Malks, Core J2EE patterns,北京:科学出版社, 2004, 172~186.
[140] Shamimabi Paurobally, Nicholas R. Jennings, Protocol engineering for web services conversations, Engineering Applications of Artificial Intelligence, 2005, 18(2): 37~254.
[141] Konstantin Beznosov, Donald J. Flinn, Shirley Kawamoto, et al, and Bret Hartman introduction to Web services and their security, Information Security Technical Report, 2005, 10(1): 2~14.
[142] Lai Ray,周斌等译,J2EE平台Web Services,北京:电子工业出版社,2005,293~298.
[143] Thriskos P., Zintzaras E., Germenis A., DHLAS: A web-based information system for statistical genetic analysis of HLA population data, Computer Methods and Programs in Biomedicine, 2007, 85(3): 267~272.
[144] Lan Hongbo, Ding Yucheng, Hong Jun, et al, A web-based manufacturing service system for rapid product development, Computers in Industry, 2004, 54(1): 51~67.
[145] Merrilees Bill, Fenech Tino, from catalog to Web: B2B multi-channel marketing strategy,Industrial Marketing Management, 2007, 36(1): 44~49.
[146] Gupta Samir, Cadeaux Jack, Woodside Arch, Mapping network champion behavior in B2B electronic venturing, Industrial Marketing Management, 2005, 34(5): 495~503.
[147] Trastour David, Bartolini Claudio, Preist Chris, Semantic Web support for the business-to-business e-commerce pre-contractual lifecycle, Computer Networks, 2003, 42(5): 661~673.
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