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On the Migration to and Synthesis of (Micro-)services: The Use of Intelligent Techniques

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Book cover Next-Gen Digital Services. A Retrospective and Roadmap for Service Computing of the Future

Part of the book series: Lecture Notes in Computer Science ((LNTCS,volume 12521))

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Abstract

This chapter investigates the use of Computational Intelligence (CI) to tackle two challenges in the area of services. The first is involved with providing efficient decision support for migrating from monolithic to service-oriented software, while the latter addresses automatic service composition, which is a special form of service migration. Migration to service-oriented architecture (SOA) is influenced by a number of different and intertwined factors. These factors are identified through literature review and expert consultation. Different CI models, such as Fuzzy Influence Diagrams and Fuzzy Cognitive Maps, are employed to organize the factors and study their behavior. Various simulations are conducted that enable decision makers to execute what-if scenarios and take informed decisions as to whether to migrate or not to SOA, as well as to study the decisive factors contributing in favor or against this migration. Service synthesis is a tedious task considering on one hand the plethora of available services and on the other their different, often conflicting characteristics. Automation of this task is therefore a critical issue which deserves attention. In this context, the challenge of automatic service synthesis is addressed through specific methods and techniques based on Evolutionary Computation to achieve such automation to the best possible extent.

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Notes

  1. 1.

    https://www.antlr.org/.

  2. 2.

    https://platypus.readthedocs.io.

References

  1. Balalaie, A., Heydarnoori, A., Jamshidi, P.: Migrating to cloud-native architectures using microservices: an experience report. In: Celesti, A., Leitner, P. (eds.) ESOCC Workshops 2015. CCIS, vol. 567, pp. 201–215. Springer, Cham (2016). https://doi.org/10.1007/978-3-319-33313-7_15

    Chapter  Google Scholar 

  2. Balalaie, A., Heydarnoori, A., Jamshidi, P.: Microservices architecture enables DevOps: migration to a cloud-native architecture. IEEE Softw. 33(3), 42–52 (2016)

    Article  Google Scholar 

  3. Baresi, L., Garriga, M., De Renzis, A.: Microservices identification through interface analysis. In: De Paoli, F., Schulte, S., Broch Johnsen, E. (eds.) ESOCC 2017. LNCS, vol. 10465, pp. 19–33. Springer, Cham (2017). https://doi.org/10.1007/978-3-319-67262-5_2

    Chapter  Google Scholar 

  4. Browning, T.R.: Applying the design structure matrix to system decomposition and integration problems: a review and new directions. IEEE Trans. Eng. Manag. 48(3), 292–306 (2001)

    Article  Google Scholar 

  5. Chen, L.: Continuous delivery: overcoming adoption challenges. J. Syst. Softw. 128, 72–86 (2017)

    Article  Google Scholar 

  6. Christoforou, A., Andreou, A.S.: A framework for static and dynamic analysis of multi-layer fuzzy cognitive maps. Neurocomputing 232, 133–145 (2017)

    Article  Google Scholar 

  7. Christoforou, A., Garriga, M., Andreou, A.S., Baresi, L.: Supporting the decision of migrating to microservices through multi-layer fuzzy cognitive maps. In: Maximilien, M., Vallecillo, A., Wang, J., Oriol, M. (eds.) ICSOC 2017. LNCS, vol. 10601, pp. 471–480. Springer, Cham (2017). https://doi.org/10.1007/978-3-319-69035-3_34

    Chapter  Google Scholar 

  8. Christoforou, A., Odysseos, L., Andreou, A.: Migration of software components to microservices: matching and synthesis. In: Proceedings of the 14th International Conference on Evaluation of Novel Approaches to Software Engineering, pp. 134–146. SCITEPRESS-Science and Technology Publications, Lda (2019)

    Google Scholar 

  9. Deb, K., Pratap, A., Agarwal, S., Meyarivan, T.: A fast and elitist multiobjective genetic algorithm: NSGA-II. IEEE Trans. Evol. Comput. 6(2), 182–197 (2002)

    Article  Google Scholar 

  10. Di Francesco, P., Lago, P., Malavolta, I.: Migrating towards microservice architectures: an industrial survey. In: 2018 IEEE International Conference on Software Architecture (ICSA). IEEE (2018). 29-2909

    Google Scholar 

  11. Engelbrecht, A.P.: Computational Intelligence: An Introduction. Wiley, Hoboken (2007)

    Book  Google Scholar 

  12. Esposito, C., Castiglione, A., Choo, K.K.R.: Challenges in delivering software in the cloud as microservices. IEEE Cloud Comput. 3(5), 10–14 (2016)

    Article  Google Scholar 

  13. Frappier, M., Matwin, S., Mili, A.: Software metrics for predicting maintainability. Software metrics study: technical memorandum 2 (1994)

    Google Scholar 

  14. Fritzsch, J., Bogner, J., Wagner, S., Zimmermann, A.: Microservices migration in industry: intentions, strategies, and challenges. In: 2019 IEEE International Conference on Software Maintenance and Evolution (ICSME), pp. 481–490. IEEE (2019)

    Google Scholar 

  15. Gabrel, V., Manouvrier, M., Murat, C.: Web services composition: complexity and models. Discrete Appl. Math. 196, 100–114 (2015)

    Article  MathSciNet  Google Scholar 

  16. Howard, R.A., Matheson, J.E.: The principles and applications of decision analysis, pp. 719–762. Strategic Decisions Group, Palo Alto (1984)

    Google Scholar 

  17. Hu, W., Jian, N., Qu, Y., Wang, Y.: GMO: a graph matching for ontologies. In: Proceedings of K-CAP Workshop on Integrating Ontologies, pp. 41–48 (2005)

    Google Scholar 

  18. Jatoth, C., Gangadharan, G., Buyya, R.: Computational intelligence based QoS-aware web service composition: a systematic literature review. IEEE Trans. Serv. Comput. 10(3), 475–492 (2015)

    Article  Google Scholar 

  19. Konar, A.: Computational Intelligence: Principles Techniques and Applications. Springer, Heidelberg (2005). https://doi.org/10.1007/b138935

    Book  MATH  Google Scholar 

  20. Kuhn, A., Ducasse, S., Gírba, T.: Semantic clustering: identifying topics in source code. Inf. Softw. Technol. 49(3), 230–243 (2007)

    Article  Google Scholar 

  21. Levcovitz, A., Terra, R., Valente, M.T.: Towards a technique for extracting microservices from monolithic enterprise systems. arXiv preprint arXiv:1605.03175 (2016)

  22. Mateou, N.H., Andreou, A.S.: Tree-structured multi-layer fuzzy cognitive maps for modelling large scale, complex problems. In: International Conference on Computational Intelligence for Modelling, Control and Automation and International Conference on Intelligent Agents, Web Technologies and Internet Commerce (CIMCA-IAWTIC 2006), vol. 2, pp. 131–139. IEEE (2005)

    Google Scholar 

  23. Mateou, N.H., Hadjiprokopis, A., Andreou, A.S.: Fuzzy influence diagrams: an alternative approach to decision making under uncertainty. In: International Conference on Computational Intelligence for Modelling, Control and Automation and International Conference on Intelligent Agents, Web Technologies and Internet Commerce (CIMCA-IAWTIC 2006), vol. 1, pp. 58–64. IEEE (2005)

    Google Scholar 

  24. Mazlami, G., Cito, J., Leitner, P.: Extraction of microservices from monolithic software architectures. In: 2017 IEEE International Conference on Web Services (ICWS), pp. 524–531. IEEE (2017)

    Google Scholar 

  25. Murata, T., Ishibuchi, H.: MOGA: multi-objective genetic algorithms. In: IEEE International Conference on Evolutionary Computation, vol. 1, pp. 289–294 (1995)

    Google Scholar 

  26. Shachter, R.D.: Evaluating influence diagrams. Oper. Res. 34(6), 871–882 (1986)

    Article  MathSciNet  Google Scholar 

  27. Taibi, D., Auer, F., Lenarduzzi, V., Felderer, M.: From monolithic systems to microservices: an assessment framework. arXiv preprint arXiv:1909.08933 (2019)

  28. Taibi, D., Lenarduzzi, V., Pahl, C.: Processes, motivations, and issues for migrating to microservices architectures: an empirical investigation. IEEE Cloud Comput. 4(5), 22–32 (2017)

    Article  Google Scholar 

  29. Van Veldhuizen, D.A., Lamont, G.B.: Multiobjective evolutionary algorithms: analyzing the state-of-the-art. Evol. Comput. 8(2), 125–147 (2000)

    Article  Google Scholar 

  30. Wootton, B.: Microservices: a definition of this new architectural term (2014). http://highscalability.com/blog/2014/4/8/microservices-not-a-free-lunch.html

  31. Zaremski, A.M., Wing, J.M.: Signature matching: a tool for using software libraries. ACM Trans. Softw. Eng. Methodol. (TOSEM) 4(2), 146–170 (1995)

    Article  Google Scholar 

  32. Zaremski, A.M., Wing, J.M.: Specification matching of software components. ACM Trans. Softw. Eng. Methodol. (TOSEM) 6(4), 333–369 (1997)

    Article  Google Scholar 

  33. Zitzler, E., Laumanns, M., Thiele, L.: SPEA2: improving the strength Pareto evolutionary algorithm. TIK-report 103 (2001)

    Google Scholar 

  34. Zitzler, E., Thiele, L.: Multiobjective evolutionary algorithms: a comparative case study and the strength Pareto approach. IEEE Trans. Evol. Comput. 3(4), 257–271 (1999)

    Article  Google Scholar 

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Authors and Affiliations

  1. Cyprus University of Technology, 3036, Limassol, Cyprus

    Andreas S. Andreou & Andreas Christoforou

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  1. Andreas S. Andreou
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Correspondence to Andreas S. Andreou .

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Editors and Affiliations

  1. University of Stuttgart, Stuttgart, Germany

    Marco Aiello

  2. The University of Sydney, Camperdown, NSW, Australia

    Athman Bouguettaya

  3. Eindhoven University of Technology, ’s Hertogenbosch, The Netherlands

    Damian Andrew Tamburri

  4. Tilburg University, ’s Hertogenbosch, The Netherlands

    Willem-Jan van den Heuvel

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Andreou, A.S., Christoforou, A. (2021). On the Migration to and Synthesis of (Micro-)services: The Use of Intelligent Techniques. In: Aiello, M., Bouguettaya, A., Tamburri, D.A., van den Heuvel, WJ. (eds) Next-Gen Digital Services. A Retrospective and Roadmap for Service Computing of the Future. Lecture Notes in Computer Science(), vol 12521. Springer, Cham. https://doi.org/10.1007/978-3-030-73203-5_4

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  • DOI: https://doi.org/10.1007/978-3-030-73203-5_4

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  • Print ISBN: 978-3-030-73202-8

  • Online ISBN: 978-3-030-73203-5

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