Enterprise Service Computing From Concept to Deployment_14 pptx

402 Maamar Copyright © 2007, Idea Group Inc. Copying or distributing in print or electronic forms without written permis- sion of Idea Group Inc. is prohibited. currently under execution vs. the maximum number of Web services under execution and (b) the next period of unavailability. After a positive check of the W-context, the identication of a resource is now launched. In ConPWS, we assume the existence of a mechanism supporting the identication of resources. A resource mainly needs to accommodate two things: (a) the beginning time of a Web-service execution, and (b) the time that the execution of a Web service lasts since the outcome of this execution depends on the delivery time as per user indication. To this purpose, a resource checks its R-context with regard to (a) the next periods of time that will feature the execution of Web services, and (b) the next period of maintenance. After a positive check, the resource noties the Web service about its availability to sup- port this service execution. Before the personalized Web service noties the user about the handling of his or her time and location preferences, an extra personalization process is triggered. This consists of adjusting the Web services that are linked, through the causal relationship, to the personalized Web service. The description given in the previous paragraphs also applies to the extra Web services, which assess their current status through their respective W-contexts and search for the resources on which they will oper- ate. To keep Figure 7 clean, the interactions that the new personalized Web services undertake to search for the resources are not represented. Once all the Web services are personalized, a nal notication is sent out to the user about the deployment of the Web service that he or she has requested. Policies in ConPWS Because of user preferences and resource availabilities, a Web service is adjusted so that it accommodates these preferences and deals with these availabilities. To ensure that the adjustment of a Web service is efcient, ConPWS integrates three types of policies (owners of Web services are normally responsible for developing the policies). The rst type, called consistency, checks the status of a Web service after it has been personalized. The second type, called feasibility, guarantees that a personalized Web service nds a resource on which it can operate according to the constraints of time and location. Finally, the third type, called inspection, ensures that the deployment of a personalized Web service complies with the adjusted specication. A consistency policy guarantees that a Web service still does what it is supposed to do after personalization. Personalization may alter the initial specication of a Web service when it comes, for instance, to the list of regular events that trigger the service. Indeed, time- and location-related parameters are new events that need to be added to the list of regular events. Moreover, because of the QoS (quality of service) -related parameters of a Web service (e.g., response time and throughput; Two Research Projects on Web Services and Context 403 Copyright © 2007, Idea Group Inc. Copying or distributing in print or electronic forms without written permission of Idea Group Inc. is prohibited. Menascé, 2002), it is important to verify that these QoS parameters did not change and are still satised despite the personalization. For illustration, because a user wishes to start the execution of a service at 2 p.m., which corresponds to the peak- time period of receiving requests, the response-time QoS cannot be satised. A feasibility policy guarantees that an appropriate resource is always identied for the execution of a personalized Web service. Because Web services have different requirements (e.g., period of requests, period of deliveries) and resources have dif- ferent constraints (e.g., period of availabilities, maximum capacity), an agreement has to be reached between what Web services need in terms of resources and what resources offer in terms of capabilities. Furthermore, the feasibility policy checks that the new operations of the personalized Web service are properly handled by the available resources. For example, if a new operation that is the result of a personal- ization requires a wireless connection, this connection has to be made available. An inspection policy is a means by which various aspects are considered such as what to track (time, location, etc.), who asked to track (user, the service itself, or both), when to track (continuously, intermittently), when and how to update the arguments of contexts, and how to react if a discrepancy is noticed between what was requested and what has effectively happened. The inspection policy is mainly tightened to the W-context of a Web service. If there is a discrepancy between what was requested and what has effectively happened, the reasons have to be determined, assessed, and reported. One of the reasons could be the lack of appropriate resources on which the personalized service has to be executed. Summary In this part of the chapter, we reviewed ConPWS for personalizing Web services using preferences and policies. Personalization occurs when there is a need for ac- commodating preferences during the performance and outcome delivery of these Web services. Preferences are user related and are of different types varying from when the execution of a Web service should start to where the outcome of this execution should be delivered. Besides user preferences, ConPWS deals with the computing resources on which the Web services are carried out since resource availabilities impact their personalization. As part of the implementation strategy in the ConPWS project, the Web services policy language (WSPL) could be used for implementing the policies related to Web services. 404 Maamar Copyright © 2007, Idea Group Inc. Copying or distributing in print or electronic forms without written permis- sion of Idea Group Inc. is prohibited. How Context Fits into Web Services Roman and Campbell (2002) observe that a user-centric context promotes appli- cations that move with users, adapt to the changes in the available resources, and provide conguration mechanisms based on user preferences. Parallel to the user- centric context, ConCWS and ConPWS bind to a service-centric context in order to promote applications that permit service adaptability, track service execution, and support on-the-y service composition. A user-centric context is associated with the U-context, whereas a service-centric context is associated with the W-context and C-context. Because Web services are the core components of a composition process, the W-context is organized in ConCWS and ConPWS along three perspec- tives (Figure 8): participation, execution, and location and time. • The participation perspective is about overseeing the multiple composition scenarios in which a Web service concurrently takes part. This guarantees that the Web service is properly specied and is ready for execution in each composition scenario. • The execution perspective is about looking for the computing resources on which a Web service operates, and monitoring the capabilities of these resources so that the Web service’s requirements are constantly satised. • The preference perspective is about ensuring that user preferences regarding execution time (e.g., at 2 p.m.) and execution location (e.g., user passing by meeting room) are integrated into the specication of a composite service. Figure 8 also illustrates the connections between the participation, execution, and preference perspectives. First, deployment connects the participation and execution perspectives, and highlights the Web service that is executed once it agrees to par- Figure 8. Perspective-based organization of W-context Participation Preference Execution D e p l o ym e nt T r a c ki n g C us t o m i z a t i o n Two Research Projects on Web Services and Context 405 Copyright © 2007, Idea Group Inc. Copying or distributing in print or electronic forms without written permission of Idea Group Inc. is prohibited. ticipate in a composition. Second, tracking connects the execution and preference perspectives, and highlights the signicance of monitoring the execution of a Web service so that user preferences are properly handled. Finally, customization con- nects the preference and participation perspectives, and highlights the possibility of adjusting a Web service so that it can accommodate various user preferences. The integration of context into Web-services composition ensures that the require- ments of and constraints on these Web services are taken into account. While current composition approaches rely on different selection criteria (e.g., execution cost and reliability), context supports Web services in their decision-making process when it comes to whether to accept or reject participating in a composition. Moreover, context is suitable for tracing the execution of Web services during exception handling. It would be possible to know at any time what happened and what is happening with a Web service. Predicting what will happen to a Web service would also be feasible in case the past contexts (i.e., what happened to a service) are stored. Web services can take advantage of the information that past contexts cater so that they can adapt their behavior for better actions and interactions with peers and users. Conclusion In this chapter, we reviewed two research projects denoted by ConCWS and ConPWS. Both are concerned with the integration of context into Web-services composition and personalization. We promoted the use of context because of the requirements of exibility, autonomy, and stability that Web-services self-management situa- tions have to satisfy. Additional requirements, namely, connectivity, nonfunctional quality-of-service properties, correctness, and scalability, also exist as reported in Milanovic and Malek (2004). The research eld of context-aware Web services opens up the opportunity for further investigation since several obstacles still hin- der the deployment of such Web services, including the fact that current standards for Web services do not enhance them with any context-awareness mechanisms, existing specication approaches for Web-services composition typically facilitate orchestration only while neglecting contexts and their impact on this orchestra- tion, and guidelines supporting the operations of Web-services personalization and tracking are lacking. Acknowledgments The author acknowledges the contributions of S. K. Mostéfaoui, H. Yahyaoui, Q. Mahmoud, and W. J. van den Heuvel to the projects presented in this chapter. 406 Maamar Copyright © 2007, Idea Group Inc. Copying or distributing in print or electronic forms without written permis- sion of Idea Group Inc. is prohibited. References Ardissono, L., Goy, A., & Petrone, G. (2003). Enabling conversations with Web services. In Proceedings of the Second International Joint Conference on Autonomous Agents & Multi-Agent Systems (AAMAS 2003), Melbourne, Australia. Benatallah, B., Dumas, M., Sheng, Q. Z., & Ngu, A. (2002). Declarative composi- tion and peer-to-peer provisioning of dynamic Web services. In Proceedings of the 18 th International Conference on Data Engineering (ICDE 2002), San Jose, CA. Benatallah, B., Sheng, Q. Z., & Dumas, M. (2003). The self-serve environment for Web services composition. IEEE Internet Computing, 7(1), 40-48. Bonett, M. (2001). Personalization of Web services: Opportunities and challenges. ARIADNE, 28. 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In Proceedings of the Ninth Open European Summer School and IFIP Workshop on Next Generation Networks (EUNICE 2003), Balatonfured, Hungary. 408 About the Authors Copyright © 2007, Idea Group Inc. Copying or distributing in print or electronic forms without written permis- sion of Idea Group Inc. is prohibited. About the Authors Robin G. Qiu is an assistant professor of information science at The Pennsylvania State University, USA, and is a university-endowed professor at Nanjing Univer- sity of Aeronautics and Astronautics, China. His research interests include services operations and informatics, component business modeling and computing, business transformation and services innovations, automatic information retrieval (auto-IR), and the control and management of manufacturing systems. He has had about 90 publications including over 30 journal publications and 2 book chapters. He cur- rently serves as the editor in chief of International Journal of Services Operations and Informatics, as an associate editor of IEEE Transactions on Systems, Man and Cybernetics, as an associate editor of IEEE Transactions on Industrial Informatics, and on the editorial board of International Journal of Data Mining and Bioinformatics. He was the founding and general chair of the 2005 IEEE International Conference on Service Operations and Logistics, and Informatics. He is a general co-chair of the 2006 IEEE International Conference on Service Operations and Logistics, and Informatics and the general chair of the 2007 International Conference on Flex- ible Automation and Intelligent Manufacturing. He also founded Services Science Global to promote the research on services science, management, and engineering worldwide. He holds a PhD in industrial engineering and a PhD (minor) in computer science and engineering from The Pennsylvania State University. * * * * * About the Authors 409 Copyright © 2007, Idea Group Inc. Copying or distributing in print or electronic forms without written permission of Idea Group Inc. is prohibited. Lianjun An is a researcher at IBM’s T.J. Watson Research Center and is currently studying the stability of supply chains through system-dynamics modeling and simulation, and designing a business-performance monitoring and management system. He received a PhD in applied mathematics from Duke University in 1991. He worked on the analysis of granular ow and plastic deformation, and the scien- tic simulation of oil reservoirs on parallel computers at McMaster University and the State University of New York at Stony Brook (1992-1997). He subsequently joined IBM and has worked on the Network Conguration Management System and Websphere Commerce Suite and Grid Computing Projects since 1998. João Paulo Andrade Almeida is a PhD candidate in the Faculty of Electrical Engineering, Mathematics and Computer Science of the University of Twente. He currently works as a researcher at the Telematica Instituut, The Netherlands. His research interests are model-driven architecture, the design of distributed applications, and service-oriented architectures. Jan vom Brocke is an assistant professor at the Department for Information Systems at the University of Muenster and a member of the European Research Center for Information Systems (ERCIS) in Germany. He graduated with a master’s in informa- tion systems in 1998 and obtained his PhD at the Faculty of Business Administration and Economics of Muenster in 2003. He has research and teaching experience at the Universities of Muenster and Saarbrücken in Germany, the University of Bucharest in Romania, the University of Tartu in Estonia, and the University College Dublin in Ireland. At present, Jan vom Brocke is supervising two competence centers at ERCIS and running research projects funded by industry foundations, the German Federal Ministry of Education and Research, and the European Commission. Barret R. Bryant is a professor and associate chair of computer and information sciences at the University of Alabama at Birmingham (UAB). He joined UAB after completing his PhD in computer science at Northwestern University. His primary research areas are the theory and implementation of programming languages, for- mal specication and modeling, and component-based software engineering. He has authored or coauthored over 100 technical papers in these areas. Bryant is a member of ACM, IEEE (senior member), and the Alabama Academy of Science. He is an ACM distinguished lecturer and chair of the ACM Special Interest Group on Applied Computing (SIGAPP). Rajkumar Buyya is a senior lecturer, Storage Technology Coporation (StoreTek, USA) fellow of grid computing, and the director of the Grid Computing and Dis- 410 About the Authors Copyright © 2007, Idea Group Inc. Copying or distributing in print or electronic forms without written permis- sion of Idea Group Inc. is prohibited. Fei Cao received his doctoral degree from the University of Alabama at Birmingham, USA. His research interests include model-driven software development, aspect- oriented programming, component-based software development, service-oriented computing, and generative programming. His work as a graduate assistant has been supported by the Naval Ofce of Research. He has been a research scientist in Avaya research labs working on a multimodal dialog system, and is now working in the Windows enterprise and server division at Microsoft. Carl K. Chang is a professor and chair of the Department of Computer Science at Iowa State University, USA. Under his leadership, the department has grown in the past 3 years to almost 30 tenured and tenure-track faculty and over 100 PhD students. He received a PhD in computer science from Northwestern University. He worked for GTE Automatic Electric and Bell Laboratories before joining the University of Illinois at Chicago in 1984, where he directed the International Center for Software Engineering. He served as the inaugurating director for the Institute for Recongurable Smart Components (IRSC) at Auburn University from 2001to 2002 before moving to Iowa State University in July 2002 to become department chair in computer science. His research interests include requirements engineering, software architecture, and Net-centric computing, and he has published extensively in these areas. Having served as general chair and program chair for many international conferences, in 2005 he served as the general chair of the rapidly emerging IEEE International Conference on Web Services (ICWS) and IEEE Services Computing Conference (SCC). In 2006, he will lead the development of the rst Congress on Software Technology and Engineering Practice (CoSTEP) for IEEE. He will also lead the IEEE International Computer Software and Applications Conference as chair of its standing committee to break a new page at its 30th anniversary in October 2006. Chang was the 2004 president of the IEEE computer society, which is the largest professional association in computing with 100,000 members worldwide from over 150 countries. Previously, he served as the editor in chief for IEEE Software (1991-1994). He received the Society’s Meritorious Service Award, Outstanding Contribution Award, the Golden Core recognition, and the IEEE Third Millennium Medal. Chang is a fellow of IEEE and of AAAS. S. C. Cheung was born in 1962. Before joining the Hong Kong University of Science and Technology, Hong Kong, he worked for the Distributed Software Engineering Group at the Imperial College in a major European ESPRIT II project on distributed recongurable systems. His effort led to the development of REX, which was adopted by various European rms like Siemens and Stollman to build in-house distributed software systems. More recently, he has been working on vari- ous research and industrial projects on object-oriented technologies and services About the Authors 411 Copyright © 2007, Idea Group Inc. Copying or distributing in print or electronic forms without written permission of Idea Group Inc. is prohibited. computing. Dr. Cheung is an associate editor of IEEE Transactions on Software Engineering. He actively participates in the organization and program committees of many leading international conferences on software engineering and distributed computing, including ICSE, FSE, ASE, ISSTA, ICDCS, ER, and SCC. He is in- terested in technology transfer and has provided technical consultancy to various organizations, including banks, public organizations, and engineering companies on the use of object-oriented and component-based technologies. Dickson K. W. Chiu is the founder of Dickson Computer Systems, Hong Kong. Besides being an experienced consultant, he also teaches part time at universities. He was born in Hong Kong and received the BSc (honors) degree in computer studies from the University of Hong Kong in 1987. He received the MSc (1994) and the PhD (2000) degrees in computer science from the Hong Kong University of Science and Technology, where he worked as a visiting assistant lecturer after graduation. He also started his own computer company while studying part time. From 2001 to 2003, he was an assistant professor at the Department of Computer Science at the Chinese University of Hong Kong. His research interests include information-systems engineering and service computers with a cross-disciplinary approach, involving Internet technologies, software engineering, agents, work ows, information-sys- tem management, security, and databases. His research results have been published in over 70 technical papers in international journals and conference proceedings, such as IEEE Transactions, Information Systems, and Decision Support Systems. He served in program committees of several international conferences, such as the IEEE International Conference on Web Services; IEEE International Conference on e-Technology, e-Commerce and e-Services; and International Conference on Web-Age Information Management. He received a best-paper award at the 37th Hawaii International Conference on System Sciences in 2004. Dr. Chiu is a senior member of the IEEE as well as a member of the ACM and the Hong Kong Com- puter Society. Jen-Yao Chung received MS and PhD degrees in computer science from the University of Illinois at Urbana-Champaign. Currently, he is the senior manager for Engineering & Technology Services Innovation, where he was responsible for identifying and creating emergent solutions. He was chief technology ofcer for IBM Global Electronics Industry. Before that, he was senior manager of the elec- tronic-commerce and supply-chain department, and program director for the IBM Institute for Advanced Commerce Technology ofce. Dr. Chung is the cofounder and cochair of the IEEE Technical Committee on e-Commerce (TCEC). He has served as general chair and program chair for many international conferences; most recently he served as the steering-committee chair for the IEEE International Conference on e-Commerce Technology (CEC05) and general chair for the IEEE International [...]... paradigm 133 service- portfolio management 60 service- portfolio measurement (SPM) 61–63 service- support agent cluster 122 service- task categories 116 service components 285–317 service composition 164,  290 service computing 322,  324 service concept 134–135 service credit assessment 77 service decomposition 142 service definition 141 service discovery 249 service follow-up 118 service interaction 191 service. .. model 189 service order processing 78 service orientation 162 service oriented 1,  3 service phase 117 service portfolio 68 service portfolio measurement (SPM) 58 services -enterprise engineering 6 services-led economy 7 services-led total solution 10 services-oriented architecture (SOA) 286 services design and engineering 10 services innovation 11 services interactions 192 services marketing 9 services... Web-based computing tools 322 Web-based platform 332,  350 Web -service component 285 Web -service composition 176 Web-services 316 Web-services-centered computing 291 Web-services-oriented ADL 291 Web-services-oriented system 286,  291,  318 Web-services-specific interface-definition language 292 Web-services composite system 189 Web-services composition 177–293,  393 Web-services concept 286 Web-services... service -enterprise- engineering 2–8 service- level agreement (SLA) 19–27 service- oriented analysis 179 service- oriented application model 170 service- oriented architecture (SOA) 16,  59,  133– 136,  157,  244,  261,  279– 281,  287 service- oriented business 1–8 service- oriented component-network 15 service- oriented computing (SOC) 62,  133,  169 service- oriented enterprise 14 service- oriented IT 15–21 service- oriented... e-retailer pricing 10 e-services 10 eBusiness 242 ebXML 242 eFlow 289 EIS triggers 118 Electre 332 electronic data interchange (EDI) 243 enterprise application integration (EAI) 19 enterprise application 133 enterprise computing 59 enterprise information system (EIS) 112 enterprise resource planning (ERP) 360 enterprise service computing 2,  18– 19,  134–139,  176,  323–329,  351 enterprise services 168 execution... conversation 191 Web-services interaction 177,  184,  189 Web-services model 286 Web-services net (WS-Net) 286,  287 Web applications 285 Web service choreography interface (WSCI) 291 Web service description language (WSDL) 21,  286 Web services 16–22,  242,  285– 303,  316,  327–331,  388–390 Web services conversation language (WSCL) 205 Web services flow language (WSFL) 291 Web services policy language... automation 276 sales and operations planning 367 SC-management system 325 scenario-based service composition 289 SCM 363 SC visibility 371 security 249–250 selling management 369 semantic consistency 183,  189 semantic triangle 251 sensor network 269 service 1,  134,  135 service- business modeling 8 service- component architecture (SCA) 164 service- composition process 289 service- delivery model 11 service -enterprise- engineering... cost-estimation model 232 cost structure 361 critical commodities 60 critical differentiators 60 cross-functional system 163 cross-organizational collaboration 362 CSM-process 370 customer -service management 369 customer -to- business (C2B) 93 customer relationship management (CRM) 118,  358,  363–368,  377 customer satisfaction 10 customer Web portal 118 D DARPA 269 dashboard or project-portfolio management 276... A abstract process graph 28 access-control engine 280 access point (AP) 264 actors 97 adaptability 72 adaptation advice repository (AAR) 52 adaptive enterprise service computing 14 adopting e-business 375 advanced planning and scheduling (APS) 363 agent deployment 393 agility 356 AJAX 162 ambient device 273 Anoto 274 Anoto Pen 274 APICS 367 application area 261 application component 135 application... Brunswick since 2004 She got her PhD from Tsinghua University, China, in 1999 She worked as a postdoc at the University of Toronto and University of Paris 13 for 2 years, and worked as a software consultant in the United States for 1 year before she joined IIT Her research interests include Web services, service- oriented architectures, and model-based reasoning for Web services She holds general interests . 133 enterprise computing 59 enterprise information system (EIS) 112 enterprise resource planning (ERP) 360 enterprise service computing 2, 18– 19, 134–139, 176, 323–329, 351 enterprise services 168 execution. (AP) 264 actors 97 adaptability 72 adaptation advice repository (AAR) 52 adaptive enterprise service computing 14 adopting e-business 375 advanced planning and scheduling (APS) 363 agent deployment. 189 asynchronous transfer mode (ATM) 269 auction 10 auction service 143 145 autonomous service 163 autonomy 236 B basic core component (BCC) 251 BDI conceptual model 112 belief-revision function (BRF)