Dynamic Patterns for Cloud Application Life-Cycle Management

  • Geir HornEmail author
  • Leire Orue-Echevarria Arrieta
  • Beniamino Di Martino
  • Paweł Skrzypek
  • Dimosthenis Kyriazis
Conference paper
Part of the Lecture Notes in Networks and Systems book series (LNNS, volume 96)


Cloud applications are by nature dynamic and must react to variations in use, and evolve to adopt new Cloud services, and exploit new capabilities offered by Edge and Fog devices, or within data centers offering Graphics Processing Units (GPUs) or dedicated processors for Artificial Intelligence (AI). Our proposal is to alleviate this complexity by using patterns at all stages of the Cloud application life-cycle: deployment, automatic service discovery, monitoring, and adaptive application evolution. The main idea of this paper is that it is possible to reduce the complexity of composing, deploying, and evolving Cross-Cloud applications using dynamic patterns.


  1. 1.
    Rossini, A., Kritikos, K., Nikolov, N., Domaschka, J., Griesinger, F., Seybold, D., Romero, D., Orzechowski, M., Kapitsaki, G., Achilleos, A.: The cloud application modelling and execution language (CAMEL). OPen Access Repositorium der Universität Ulm, p. 39 (2017).
  2. 2.
    Bergmayr, A., Rossini, A., Ferry, N., Horn, G., Orue-Echevarria, L., Solberg, A., Wimmer, M.: The evolution of CloudML and its applications. In: Paige, R., Cabot, J., Brambilla, M., Hill, J.H. (eds.) Proceedings of the 3rd International Workshop on Model-Driven Engineering on and for the Cloud 18th International Conference on Model Driven Engineering Languages and Systems (MoDELS 2015), vol. 1563, pp. 13–18. CEUR Workshop Proceedings, Ottawa (2015).
  3. 3.
    Androcec, D., Vrcek, N., Seva, J.: Cloud computing ontologies: a systematic review. In: The Third International Conference on Models and Ontology-based Design of Protocols, Architectures and Services, MOPAS 2012, pp. 9–14 (2012)Google Scholar
  4. 4.
    Di Martino, B., Cretella, G., Esposito, A.: Cloud Portability and Interoperability - Issues and Current Trends. Springer, Berlin (2015). Scholar
  5. 5.
    Beniamino, D.M., Antonio, E., Giuseppina, C.: Semantic representation of cloud patterns and services with automated reasoning to support cloud application portability. IEEE Trans. Cloud Comput. 5(4), 765–779 (2017). Scholar
  6. 6.
    Richardson, C.: Microservices Patterns: With Examples in Java, 1st edn. Manning Publications, Shelter Island, New York (2018)Google Scholar
  7. 7.
    Namiot, D., Sneps-Sneppe, M.: On micro-services architecture. 2(9), 24–27 (2014).
  8. 8.
    Taibi, D., Lenarduzzi, V., Pahl, C.: Architectural patterns for microservices: a systematic mapping study. In: CLOSER 2018, pp. 221–232 (2018).
  9. 9.
    Deng, Y., Head, M., Kochut, A., Munson, J., Sailer, A., Shaikh, H.: Introducing semantics to cloud services catalogs. In: 2011 IEEE International Conference on Services Computing (SCC), pp. 24–31 (2011)Google Scholar
  10. 10.
    Gamma, E., Helm, R., Johnson, R., Vlissides, J., Booch, G.: Design Patterns: Elements of Reusable Object-Oriented Software, 1st edn. Addison-Wesley Professional, Reading (1994)Google Scholar
  11. 11.
    European Union: Regulation (EU) 2018/1807 of the European Parliament and of the Council of 14 November 2018 on a framework for the free flow of non-personal data in the European Union (text with EEA relevance) (2018).
  12. 12.
    Amato, F., Moscato, F.: Pattern-based orchestration and automatic verification of composite cloud services. 56 (2016).
  13. 13.
    Amato, F., Moscato, F.: Exploiting cloud and workflow patterns for the analysis of composite cloud services. Future Gener. Comput. Syst. 67, 255–265 (2017)CrossRefGoogle Scholar
  14. 14.
    Horn, G., Skrzypek, P.: MELODIC: utility based cross cloud deployment optimisation. In: 32nd International Conference on Advanced Information Networking and Applications (AINA) Workshops, pp. 360–367. IEEE Computer Society, Krakow (2018).
  15. 15.
    Horn, G., Skrzypek, P., Materka, K., Przeździek, T.: Cost benefits of multi-cloud deployment of dynamic computational intelligence applications. In: Barolli, L., Takizawa, M., Xhafa, F., Enokido, T. (eds.) Proceedings of the Workshops of the 33rd International Conference on Advanced Information Networking and Applications (WAINA-2019). Advances in Intelligent Systems and Computing, vol. 927, pp. 1041–1054. Springer, Matsue (2019). Scholar
  16. 16.
    Blair, G., Bencomo, N., France, R.B.: Models@run.time. Computer 42(10), 22–27 (2009). Scholar
  17. 17.
    IBM: An architectural blueprint for autonomic computing. White Paper Third Edition, IBM, 17 Skyline Drive, Hawthorne, NY 10532, USA (2005).
  18. 18.
    Dietrich, J., Elgar, C.: A formal description of design patterns using OWL. In: 2005 Australian Software Engineering Conference, pp. 243–250. IEEE Computer Society, Brisbane (2005).
  19. 19.
    Kacprzyk, J., Pedrycz, W. (eds.): Springer Handbook of Computational Intelligence. Springer Handbooks. Springer, Heidelberg (2015)zbMATHGoogle Scholar
  20. 20.
    Kephart, J.O., Chess, D.M.: The vision of autonomic computing. Computer 36(1), 41–50 (2003). Scholar
  21. 21.
    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). Scholar
  22. 22.
    Geihs, K., Barone, P., Eliassen, F., Floch, J., Fricke, R., Gjørven, E., Hallsteinsen, S., Horn, G., Khan, M.U., Mamelli, A., Papadopoulos, G.A., Paspallis, N., Reichle, R., Stav, E.: A comprehensive solution for application-level adaptation. Softw.: Pract. Exp. 39(4), 385–422 (2009). Scholar
  23. 23.
    Maciaszek, L.A., Skalniak, T.: Confluent factors, complexity and resultant architectures in modern software engineering: a case of service cloud applications. In: 5th International Symposium on Business Modeling and Software Design, BMSD 2015, pp. 37–45. SciTePress (2015)Google Scholar
  24. 24.
    Arostegi, M., Torre-Bastida, A., Bilbao, M.N., Del Ser, J.: A heuristic approach to the multicriteria design of IaaS cloud infrastructures for big data applications. Expert Syst. 35(5), e12259 (2018). Scholar
  25. 25.
    Ferry, N., Chauvel, F., Song, H., Rossini, A., Lushpenko, M., Solberg, A.: CloudMF: model-driven management of multi-cloud applications. ACM Trans. Internet Technol. (TOIT) 18(2), 16:1–16:24 (2018). Scholar
  26. 26.
    Avgeriou, P., Zdun, U.: Architectural patterns revisited - a pattern language. In: Longshaw, A., Zdun, U. (eds.) Proceedings of the 10th European Conference on Pattern Languages of Programs (EuroPLoP 2005), vol. D3, pp. 1–39. UVK - Universitaetsverlag Konstanz, Irsee (2005)Google Scholar
  27. 27.
    Jabbari, R., bin Ali, N., Petersen, K., Tanveer, B.: What is DevOps? A systematic mapping study on definitions and practices. In: Proceedings of the Scientific Workshop Proceedings of XP2016, XP 2016 Workshops, pp. 12:1–12:11. ACM, Edinburgh (2016).
  28. 28.
    Hallsteinsen, S., Geihs, K., Paspallis, N., Eliassen, F., Horn, G., Lorenzo, J., Mamelli, A., Papadopoulos, G.A.: A development framework and methodology for self-adapting applications in ubiquitous computing environments. J. Syst. Softw. 85(12), 2840–2859 (2012). Scholar
  29. 29.
    Takahashi, T., Kadobayashi, Y., Fujiwara, H.: Ontological approach toward cybersecurity in cloud computing. In: Proceedings of the 3rd International Conference on Security of Information and Networks, pp. 100–109. ACM (2010)Google Scholar
  30. 30.
    Cunningham, W., Beck, K.: Constructing abstractions for object-oriented applications. Technical report CR-87-25, Tektronix, Inc, Computer Research Laboratory (1987)Google Scholar
  31. 31.
    Yamato, Y.: Optimum application deployment technology for heterogeneous IaaS cloud. Inform. Process. Soc. Jpn. 25, 56–58 (2017)Google Scholar

Copyright information

© Springer Nature Switzerland AG 2020

Authors and Affiliations

  • Geir Horn
    • 1
    Email author
  • Leire Orue-Echevarria Arrieta
    • 2
  • Beniamino Di Martino
    • 3
  • Paweł Skrzypek
    • 4
  • Dimosthenis Kyriazis
    • 5
  1. 1.University of OsloOsloNorway
  2. 2.Fundacion TECNALIA Research and InnovationDerioSpain
  3. 3.University of Campania “Luigi Vanvitelli”CasertaItaly
  4. 4.7Bulls.comWarsawPoland
  5. 5.University of PiraeusPiraeusGreece

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