Abstract
With the introduction of services, software systems have become more flexible as new services can easily be composed from existing ones. Service composition frameworks offer corresponding functionality and hide the complexity of the underlying technologies from their users. However, possibilities for anticipating quality properties of composed services before their actual operation are limited so far. While existing approaches for model-based software quality prediction can be used by service composers for determining realizable Quality of Service (QoS) levels, integration of such techniques into composition frameworks is still missing. As a result, high effort and expert knowledge is required to build the system models required for prediction. In this paper, we present a novel service composition process that includes QoS prediction for composed services as an integral part. Furthermore, we describe how composition frameworks can be extended to support this process. With our approach, systematic consideration of service quality during the composition process is naturally achieved, without the need for detailed knowledge about the underlying prediction models. To evaluate our work and validate its applicability in different domains, we have integrated QoS prediction support according to our process in two composition frameworks – a large-scale SLA management framework and a service mashup platform.
Keywords
- Service Composition
- Service Selection
- Quality Prediction
- Object Management Group
- Composition Framework
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.
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References
Kingstone, S.: Understanding total cost of ownership of a hosted vs. premises-based crm solution. Yankee Group Report June 2004 (2004)
SLA@SOI: Project website (June 2011), http://sla-at-soi.eu/
COCKTAIL: Project website (June 2011), http://www.cocktail-projekt.de/
Balsamo, S., Marco, A.D., Inverardi, P., Simeoni, M.: Model-based performance prediction in software development: A survey. IEEE Transactions on Software Engineering 30, 295–310 (2004)
Reussner, R., Becker, S., Burger, E., Happe, J., Hauck, M., Koziolek, A., Koziolek, H., Krogmann, K., Kuperberg, M.: The Palladio Component Model. Technical report, Karlsruhe (2011)
Zeng, L., Benatallah, B., Ngu, A.H.H., Dumas, M., Kalagnanam, J., Chang, H.: Qos-aware middleware for web services composition. IEEE Trans. Softw. Eng. 30, 311–327 (2004)
Strunk, A.: Qos-aware service composition: A survey. In: European Conference on Web Services (2010)
Margolis, B., Sharpe, J.: SOA for the business developer: concepts, BPEL, and SCA. MC Press (2007)
Soi, S., Baez, M.: Domain-Specific Mashups: From All to All You Need. In: Daniel, F., Facca, F.M. (eds.) ICWE 2010. LNCS, vol. 6385, pp. 384–395. Springer, Heidelberg (2010)
IBM: Mashup center (June 2011), http://greenhouse.lotus.com/
Yahoo!: Yahoo! pipes (June 2011), http://pipes.yahoo.com/pipes
DreamFace: Mashup editor (June 2011), http://dreamface-interactive.com
Canfora, G., Di Penta, M., Esposito, R., Villani, M.L.: An approach for qos-aware service composition based on genetic algorithms. In: Proceedings of GECCO 2005 (2005)
Smith, C.U.: Performance Engineering of Software Systems. Addison-Wesley Longman Publishing Co., Inc., Boston (1990)
Koziolek, H.: Performance Evaluation of Component-based Software Systems: A Survey. Performance Evaluation 67(8), 634–658 (2010)
Goseva-Popstojanova, K., Trivedi, K.S.: Architecture-based approach to reliability assessment of software systems. Performance Evaluation 45 (May 2001)
Becker, S.: Coupled Model Transformations for QoS Enabled Component-Based Software Design. PhD thesis, University of Oldenburg, Germany (March 2008)
Object Management Group (OMG): UML Profile for Schedulability, Performance and Time (January 2005)
Object Management Group (OMG): UML Profile for Modeling Quality of Service and Fault Tolerance Characteristics and Mechanisms (May 2005)
Object Management Group (OMG): UML Profile for Modeling and Analysis of Real-Time and Embedded systems (MARTE) (May 2006)
Grassi, V., Mirandola, R., Sabetta, A.: From Design to Analysis Models: A Kernel Language for Performance and Reliability Analysis of Component-based Systems. In: WOSP 2005. ACM Press (2005)
Sharma, V.S., Jalote, P., Trivedi, K.S.: A performance engineering tool for tiered software systems. In: Proceedings of the 30th Annual International Computer Software and Applications Conference, vol. 1. IEEE Computer Society (2006)
Kounev, S.: Performance modeling and evaluation of distributed component-based systems using queueing petri nets. IEEE Trans. Softw. Eng. 32, 486–502 (2006)
Reussner, R.H., Schmidt, H.W., Poernomo, I.H.: Reliability prediction for component-based software architectures. Journal of Systems and Software 66(3) (2003)
Roshandel, R., Medvidovic, N., Golubchik, L.: A Bayesian Model for Predicting Reliability of Software Systems at the Architectural Level. In: Overhage, S., Ren, X.-M., Reussner, R., Stafford, J.A. (eds.) QoSA 2007. LNCS, vol. 4880, pp. 108–126. Springer, Heidelberg (2008)
Klein, A., Ishikawa, F., Honiden, S.: Efficient heuristic approach with improved time complexity for qos-aware service composition. In: The 9th International Conference on Web Services, ICWS 2011 (2011)
García, J.M., Ruiz, D., Ruiz-Cortés, A., Martín-Díaz, O., Resinas, M.: An Hybrid, QoS-Aware Discovery of Semantic Web Services Using Constraint Programming. In: Krämer, B.J., Lin, K.-J., Narasimhan, P. (eds.) ICSOC 2007. LNCS, vol. 4749, pp. 69–80. Springer, Heidelberg (2007)
Gallotti, S., Ghezzi, C., Mirandola, R., Tamburrelli, G.: Quality Prediction of Service Compositions through Probabilistic Model Checking. In: Becker, S., Plasil, F., Reussner, R. (eds.) QoSA 2008. LNCS, vol. 5281, pp. 119–134. Springer, Heidelberg (2008)
Durdik, Z., Drawehn, J., Herbert, M.: Towards automated service quality prediction for development of enterprise mashups. In: 5th International Workshop on Web APIs and Service Mashups @ ECOWS 2011, Lugano, Switzerland (September 2011) (to appear)
Huber, N., Becker, S., Rathfelder, C., Schweflinghaus, J., Reussner, R.: Performance Modeling in Industry: A Case Study on Storage Virtualization. In: International Conference on Software Engineering (ISCE), Software Engineering in Practice Track, pp. 1–10. ACM (2010)
Rathfelder, C., Kounev, S., Evans, D.: Capacity Planning for Event-based Systems using Automated Performance Predictions. In: 26th IEEE/ACM International Conference on Automated Software Engineering (2011) (to appear)
Brosig, F., Kounev, S., Krogmann, K.: Automated Extraction of Palladio Component Models from Running Enterprise Java Applications. In: Proceedings of the 1st International Workshop on Run-time Models for Self-managing Systems and Applications. ACM (2009)
Martens, A., Becker, S., Koziolek, H., Reussner, R.: An Empirical Investigation of the Applicability of a Component-Based Performance Prediction Method. In: Thomas, N., Juiz, C. (eds.) EPEW 2008. LNCS, vol. 5261, pp. 17–31. Springer, Heidelberg (2008)
Comuzzi, M., Kotsokalis, C., Rathfelder, C., Theilmann, W., Winkler, U., Zacco, G.: A Framework for Multi-level SLA Management. In: Dan, A., Gittler, F., Toumani, F. (eds.) ICSOC/ServiceWave 2009. LNCS, vol. 6275, pp. 187–196. Springer, Heidelberg (2010)
Kotsokalis, C., Yahyapour, R., Gonzalez, M.A.R.: Sami: The sla management instance. In: Proceedings of ICIW 2010 (September 2010)
Palladio: Project website (June 2011), http://www.palladio-simulator.com/
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Klatt, B., Brosch, F., Durdik, Z., Rathfelder, C. (2012). Quality Prediction in Service Composition Frameworks. In: Pallis, G., et al. Service-Oriented Computing - ICSOC 2011 Workshops. ICSOC 2011. Lecture Notes in Computer Science, vol 7221. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-31875-7_14
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DOI: https://doi.org/10.1007/978-3-642-31875-7_14
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