4 research outputs found

    Microservice Transition and its Granularity Problem: A Systematic Mapping Study

    Get PDF
    Microservices have gained wide recognition and acceptance in software industries as an emerging architectural style for autonomic, scalable, and more reliable computing. The transition to microservices has been highly motivated by the need for better alignment of technical design decisions with improving value potentials of architectures. Despite microservices' popularity, research still lacks disciplined understanding of transition and consensus on the principles and activities underlying "micro-ing" architectures. In this paper, we report on a systematic mapping study that consolidates various views, approaches and activities that commonly assist in the transition to microservices. The study aims to provide a better understanding of the transition; it also contributes a working definition of the transition and technical activities underlying it. We term the transition and technical activities leading to microservice architectures as microservitization. We then shed light on a fundamental problem of microservitization: microservice granularity and reasoning about its adaptation as first-class entities. This study reviews state-of-the-art and -practice related to reasoning about microservice granularity; it reviews modelling approaches, aspects considered, guidelines and processes used to reason about microservice granularity. This study identifies opportunities for future research and development related to reasoning about microservice granularity.Comment: 36 pages including references, 6 figures, and 3 table

    A flexible service selection for executing virtual services

    Full text link
    [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),

    Privacy-preserved security-conscious framework to enhance web service composition

    Get PDF
    The emergence of loosely coupled and platform-independent Service-Oriented Computing (SOC) has encouraged the development of large computing infrastructures like the Internet, thus enabling organizations to share information and offer valueadded services tailored to a wide range of user needs. Web Service Composition (WSC) has a pivotal role in realizing the vision of implementing just about any complex business processes. Although service composition assures cost-effective means of integrating applications over the Internet, it remains a significant challenge from various perspectives. Security and privacy are among the barriers preventing a more extensive application of WSC. First, users possess limited prior knowledge of security concepts. Second, WSC is hindered by having to identify the security required to protect critical user information. Therefore, the security available to users is usually not in accordance with their requirements. Moreover, the correlation between user input and orchestration architecture model is neglected in WSC with respect to selecting a high performance composition execution process. The proposed framework provides not only the opportunity to securely select services for use in the composition process but also handles service users’ privacy requirements. All possible user input states are modelled with respect to the extracted user privacy preferences and security requirements. The proposed approach supports the mathematical modelling of centralized and decentralized orchestration regarding service provider privacy and security policies. The output is then utilized to compare and screen the candidate composition routes and to select the most secure composition route based on user requests. The D-optimal design is employed to select the best subset of all possible experiments and optimize the security conscious of privacy-preserving service composition. A Choreography Index Table (CIT) is constructed for selecting a suitable orchestration model for each user input and to recommend the selected model to the choreographed level. Results are promising that indicate the proposed framework can enhance the choreographed level of the Web service composition process in making adequate decisions to respond to user requests in terms of higher security and privacy. Moreover, the results reflect a significant value compared to conventional WSC, and WSC optimality was increased by an average of 50% using the proposed CIT
    corecore