330,021 research outputs found

    QoS-Aware Middleware for Web Services Composition

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    The paradigmatic shift from a Web of manual interactions to a Web of programmatic interactions driven by Web services is creating unprecedented opportunities for the formation of online Business-to-Business (B2B) collaborations. In particular, the creation of value-added services by composition of existing ones is gaining a significant momentum. Since many available Web services provide overlapping or identical functionality, albeit with different Quality of Service (QoS), a choice needs to be made to determine which services are to participate in a given composite service. This paper presents a middleware platform which addresses the issue of selecting Web services for the purpose of their composition in a way that maximizes user satisfaction expressed as utility functions over QoS attributes, while satisfying the constraints set by the user and by the structure of the composite service. Two selection approaches are described and compared: one based on local (task-level) selection of services and the other based on global allocation of tasks to services using integer programming

    A flexible service selection for executing virtual services

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    [EN] With the adoption of a service-oriented paradigm on the Web, many software services are likely to fulfil similar functional needs for end-users. We propose to aggregate functionally equivalent software services within one single virtual service, that is, to associate a functionality, a graphical user interface (GUI), and a set of selection rules. When an end user invokes such a virtual service through its GUI to answer his/her functional need, the software service that best responds to the end-user s selection policy is selected and executed and the result is then rendered to the end-user through the GUI of the virtual service. A key innovation in this paper is the flexibility of our proposed service selection policy. First, each selection policy can refer to heterogeneous parameters (e.g., service price, end-user location, and QoS). Second, additional parameters can be added to an existing or new policy with little investment. Third, the end users themselves define a selection policy to apply during the selection process, thanks to the GUI element added as part of the virtual service design. This approach was validated though the design, implementation, and testing of an end-to-end architecture, including the implementation of several virtual services and utilizing several software services available today on the Web.This work was partially supported in part by SERVERY (Service Platform for Innovative Communication Environment), a CELTIC project that aims to create a Service Marketplace that bridges the Internet and Telco worlds by merging the flexibility and openness of the former with the trustworthiness and reliability of the latter, enabling effective and profitable cooperation among actors.Laga, N.; Bertin, E.; Crespi, N.; Bedini, I.; Molina Moreno, B.; Zhao, Z. (2013). A flexible service selection for executing virtual services. World Wide Web. 16(3):219-245. doi:10.1007/s11280-012-0184-2S219245163Aggarwal, R., Verma, K., Miller, J., and Milnor, W.: Constraint Driven Web Service Composition in METEOR-S. In Proceedings of the 2004 IEEE international Conference on Services Computing (September 2004). IEEE Computer Society, Washington, DC, 23–30.Apple Inc. Apple app store.: Available at: www.apple.com/iphone/appstore/ , accessed on May 22nd, 2012.Atzeni, P., Catarci, T., Pernici, B.: Multi-Channel adaptive information Systems. World Wide Web 10(4), 345–347 (2007)Baresi, L., Bianchini, D., Antonellis, V.D., Fugini, M.G., Pernici, B., Plebani, P.: Context-aware Composition of e-Service. In Technologies for E-Services: Third International Workshop, vol. 2819, 28–41, TES 2003, Berlin, German, 2003.Ben Hassine, A., Matsubara, S., Ishida, T.: In Proceedings of the 5th international conference on The Semantic Web (ISWC’06), Isabel Cruz, Stefan Decker, Dean Allemang, Chris Preist, and Daniel Schwabe (Eds.). Springer-Verlag, Berlin, Heidelberg, 130–143 (2006).Blum, N., Dutkowski, S., Magedanz, T.: InSeRt - An Intent-based Service Request API for Service Exposure in Next Generation Networks. In Proceedings of 32nd Annual IEEE Software Engineering Workshop. Porto Sani Resort, Kassandra, Greece, 2008 pp21–30.Boussard, M., Fodor, S., Crespi, N., Iribarren, V., Le Rouzic, J.P., Bedini, I., Marton, G., Moro Fernandez, D., Lorenzo Duenas, O., Molina, B.: SERVERY: the Web-Telco marketplace. ICT-Mobile Summit 2009, Santander (2009)Cabrera, Ó., Oriol, M., Franch, X., Marco, J., LĂłpez, L., Fragoso, O., Santaolaya, R.: WeSSQoS: A Configurable SOA System for Quality-aware Web Service Selection. CoRR 2011, abs/1110.5574.Casati, F., Ilnicki, S., Jin, L., Krishnamoorthy, V., Shan, M.: Adaptive and Dynamic Service Composition in eFlow. Lecture Notes in Computer Science, Volume 1789/2000, 13–31, 2000.CibrĂĄn, M. A., Verheecke, B., Vanderperren, W., SuvĂ©e, D., and Jonckers, V.: “Aspect-oriented Programming for Dynamic Web Service Selection, Integration and Management.” In Proc. World Wide Web 2007, pp. 211–242.Crespi, N., Boussard, M. Fodor, S.: Converging Web 2.0 with telecommunications. eStrategies Projects, Vol. 10, 108–109. British Publishers, ISSN 1758–2369, June 2009.Dey, A.K., Salber, D., Abowd, G.D.: A conceptual framework and a toolkit for supporting the rapid prototyping of context-aware applications. Hum. Comput. Interact. 16, 1–67 (2001)Ding, Q., Li, X., and Zhou, X.: Reputation Based Service Selection in Grid Environment. In Proceedings of the 2008 international Conference on Computer Science and Software Engineering - Volume 03 (December. 2008). CSSE. IEEE Computer Society, Washington, DC, 58–61.Fielding, R.T.: Architectural Styles and the Design of Network-based Software Architectures. Thesis dissertation, 2000.Franch, X., GrĂŒnbacher, P., Oriol, M., Burgstaller, B., Dhungana, D., LĂłpez, L., Marco, J., Pimentel, J.: Goal-driven Adaptation of Service-Based Systems from Runtime Monitoring Data. REFS 2011.Frolund, S., Koisten, J.: QML: A Language for Quality of Service Specification. HP Labs technical reports. Available at http://www.hpl.hp.com/techreports/98/HPL-98-10.html , accessed on May 22nd, 2012.Google. Android market.: Available at: www.android.com/market/ , accessed on May 22nd, 2012.Google. Intents and Intent Filters.: Available at http://developer.android.com/guide/topics/intents/intents-filters.html , accessed on May 22nd, 2012.Gu, X., Nahrstedt, K., Yuan, W., Wichadakul, D., Xu, D.: An Xml-Based Quality of Service Enabling Language for the Web. Technical Report. UMI Order Number: UIUCDCS-R-2001-2212., University of Illinois at Urbana-Champaign.Laga, N., Bertin, E., and Crespi, N.: Building a User Friendly Service Dashboard: Automatic and Non-intrusive Chaining between Widgets. In Proceedings of the 2009 Congress on Services - I (July 06–10, 2009). SERVICES. IEEE Computer Society, Washington, DC, 484–491.Laga, N., Bertin, E., and Crespi, N.: Business Process Personalization Through Web Widgets. In Proceedings of the 2010 IEEE international Conference on Web Services (July 05–10, 2010). ICWS. IEEE Computer Society, Washington, DC, 551–558.Liu, Y., Ngu, A. H., and Zeng, L. Z.: QoS computation and policing in dynamic web service selection. In Proceedings of the 13th international World Wide Web Conference on Alternate Track Papers &Amp; Posters (New York, NY, USA, May 19–21, 2004). WWW Alt. ’04. ACM, New York, NY, 66–73.Malik, Z., Bouguettaya, A.: Rater credibility assessment in Web services interactions. World Wide Web 12(1), 3–25 (2009)Martin, D. et al.: OWL-S: Semantic Markup for Web Services. W3C member submission, available at http://www.w3.org/Submission/2004/SUBM-OWL-S-20041122/ , accessed on May 22nd, 2012.Nestler, T., Namoun, A., Schill, A.: End-user development of service-based interactive web applications at the presentation layer. EICS 2011: 197–206.Newcomer, E.: Understanding Web Services: XML, Wsdl, Soap, and UDDI. Addison, Wesley, Boston, Mass., May 2002.O’Reilly, T.: What Is Web 2.0, Design Patterns and Business Models for the Next Generation of Software.Piessens, F., Jacobs, B., Truyen, E., Joosen, W.: Support for Metadata-driven Selection of Run-time Services in .NET is Promising but Immature. vol. 3, no. 2, Special issue: .NET: The Programmer’s Perspective: ECOOP Workshop, 27–35. 2003.Rasch, K;, Li, F., Sehic, S., Ayani R., and Dustdar, S.: “Context-driven personalized service discovery in pervasive environments,” in Proc World Wide Web, 2011, pp. 295–319.Reichl, P.: From ‘Quality-of-Service’ and ‘Quality-of-Design’ to ‘Quality-of-Experience’: A holistic view on future interactive telecommunication ser-vices. In 15th International Conference on Software, Telecommunications and Computer Networks, 2007. Soft-COM 2007. Sept. 2007. vol., no.,1–6, 27–29.Rolland, C., Kaabi, R.S., Kraiem, N.: On ISOA: Intentional Services Oriented Architecture. In Advanced Information Systems Engineering, volume 4495/2007, 158–172, June 2007.Sanchez, A., Carro, B., Wesner, S.: Telco services for end customers: European Perspective. In Communications Magazine. IEEE 46(2), 14–18 (2008)Santhanam, G. R., Basu, S., and Honavar, V.: On Utilizing Qualitative Preferences in Web Service Composition: A CP-net Based Approach. In Proceedings of IEEE Congress on Services, Services - Part I, vol., no.,538–544, 2008.Spanoudakis, G., Mahbub, K., Zisman, A.: A Platform for Context Aware Runtime Web Service Discovery. In Proc IEEE ICWS, 2007, pp233-240.Tsesmetzis, D., Roussaki, I., Sykas, E.: Modeling and Simulation of QoS-aware Web Service Selection for Provider Profit Maximization. Simulation 83(1), 93–106 (2007)Wang, P., Chao, K., Lo, C., Farmer, R., and Kuo, P.: A Reputation-Based Service Selection Scheme. In Proceedings of the 2009 IEEE international Conference on E-Business Engineering (October 21–23, 2009). ICEBE. IEEE Computer Society, Washington, DC, 501–506.Wang, H., Yang, D., Zhao, Y., and Gao, Y.: Multiagent System for Reputation--based Web Services Selection. In Proceedings of the Sixth international Conference on Quality Software (October 27–28, 2006). QSIC. IEEE Computer Society, Washington, DC, 429–434.Wholesale Applications Community.: WAC Informational Whitepaper. Available at http://www.wholesaleappcommunity.com/About-Wac/BACKGROUND%20TO%20WAC/whitepaper.pdf , accessed on May 22nd, 2012.Windows Marketplace.: Available at http://marketplace.windowsphone.com/default.aspx , accessed on May 22nd, 2012.Xu, Z., Martin, P., Powley, W., Zulkernine, F.: Reputation-Enhanced QoS-based Web Services Discovery. Web Services, 2007. In proceedings of IEEE International Conference on Web Services, ICWS 2007. 249, 256, 9–13 July 2007.Yu, Q., Bouguettaya,A.: “Multi-attribute optimization in service selection”. In Proc World Wide Web,2012, pp. 1–31.Yu, T., Zhang, Y., Lin, K. Efficient algorithms for Web services selection with end-to-end QoS constraints. ACM Transaction Web 1, 1. Article 6, 26 pages. (May 2007),

    A Requirement-centric Approach to Web Service Modeling, Discovery, and Selection

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    Service-Oriented Computing (SOC) has gained considerable popularity for implementing Service-Based Applications (SBAs) in a flexible\ud and effective manner. The basic idea of SOC is to understand users'\ud requirements for SBAs first, and then discover and select relevant\ud services (i.e., that fit closely functional requirements) and offer\ud a high Quality of Service (QoS). Understanding users’ requirements\ud is already achieved by existing requirement engineering approaches\ud (e.g., TROPOS, KAOS, and MAP) which model SBAs in a requirement-driven\ud manner. However, discovering and selecting relevant and high QoS\ud services are still challenging tasks that require time and effort\ud due to the increasing number of available Web services. In this paper,\ud we propose a requirement-centric approach which allows: (i) modeling\ud users’ requirements for SBAs with the MAP formalism and specifying\ud required services using an Intentional Service Model (ISM); (ii)\ud discovering services by querying the Web service search engine Service-Finder\ud and using keywords extracted from the specifications provided by\ud the ISM; and(iii) selecting automatically relevant and high QoS services\ud by applying Formal Concept Analysis (FCA). We validate our approach\ud by performing experiments on an e-books application. The experimental\ud results show that our approach allows the selection of relevant and\ud high QoS services with a high accuracy (the average precision is\ud 89.41%) and efficiency (the average recall is 95.43%)

    Verifying predictive services'quality with Mercury

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    Due to the success of service technology, there are lots of services nowadays that make predictions about the future in domains such as weather forecast, stock market and bookmakers. The value delivered by these predictive services relies on the quality of their predictions. This paper presents Mercury, a tool that measures predictive service quality in the domain of weather forecast, and automates the context-dependent selection of the most accurate predictive service to satisfy a customer query. To do so, candidate predictive services are monitored so that their predictions can be eventually compared with real observations obtained from some trusted source. Mercury is a proof-of-concept to show that the selection of predictive services can be driven by the quality of their predictions. Its service-oriented architecture (SOA) aims to support the easy adaptation to other prediction domains and makes feasible its integration in self-adaptive SOA systems, as well as its direct use by end-users as a classical web application. Thoughout the paper, we show how Mercury was built.Preprin

    Aspect-Oriented Programming for Dynamic Web Service Monitoring and Selection

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    Abstract. In Service-Oriented Application Development, applications are composed by selecting and integrating third-party web services. To avoid hardwiring concrete services in client applications we introduced in previous work the Web Services Management Layer (WSML) and suggested a redirection mechanism based on Aspect Oriented Programming (AOP). Even though this mechanism enables hot swapping between semantically equivalent services based on their availability, this is not enough to create applications that are driven by business requirements. In this paper we introduce a more advanced selection mechanism that allows dynamic switching between services based on business driven requirements that can change over time. Choosing a service may be done based on cost, presence on approved partners list, as well as binding support, quality of service classifications, historical performance and proximity. We introduce a modular monitoring mechanism that is able to observe these criteria and trigger a more advanced service selection procedure. We show how the AOP language JAsCo with its dynamically pluggable aspects is well suited to achieve this. 1

    On the Free Bridge Across the Digital Divide: Assessing the Quality of Facebook’s Free Basics Service

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    Free Basics is an initiative backed by Facebook to provide users in developing countries free mobile Internet access to selected services. Despite its wide-spread deployment and its potential impact on bridging the digital divide, to date, few studies have rigorously measured the quality of the free Internet service offered by Free Basics. In this short paper, we characterize the quality of the Free Basics service offered in Pakistan and South Africa along three dimensions: (i) the selection of accessible Web services, (ii) the functionality of those services, and (iii) the network performance for those services. While preliminary, our findings show that data-driven studies are essential for having more informed public debates on the pros and cons of the current design of the Free Basics service
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