Optimal Distribution of Applications in the Cloud

  • Vasilios Andrikopoulos
  • Santiago Gómez Sáez
  • Frank Leymann
  • Johannes Wettinger
Part of the Lecture Notes in Computer Science book series (LNCS, volume 8484)


The emergence of the cloud computing paradigm introduces a number of challenges and opportunities to application and system developers. The multiplication and proliferation of available offerings by cloud service providers, for example, makes the selection of an appropriate solution complex and inefficient. On the other hand, this availability of offerings creates additional possibilities in the way that applications can be engineered or re-engineered to take advantage of e.g. the elastic nature, or the pay per use model of cloud computing. This work proposes a formal framework which allows to explore the possibility space of optimally distributing application components across cloud offerings in an efficient and flexible manner. The proposed approach introduces a set of innovative in their use concepts and demonstrates how this framework can be used in practice by means of a running scenario.


application topology distribution optimization cloud computing operational expenses 


Unable to display preview. Download preview PDF.

Unable to display preview. Download preview PDF.


  1. 1.
    Andrikopoulos, V., Binz, T., Leymann, F., Strauch, S.: How to Adapt Applications for the Cloud Environment. Computing 95(6), 493–535 (2013)CrossRefGoogle Scholar
  2. 2.
    Andrikopoulos, V., Song, Z., Leymann, F.: Supporting the migration of applications to the cloud through a decision support system. In: Proceedings of the 6th IEEE International Conference on Cloud Computing (CLOUD 2013), pp. 565–572. IEEE Computer Society (2013)Google Scholar
  3. 3.
    Antonescu, A.F., Robinson, P., Braun, T.: Dynamic topology orchestration for distributed cloud-based applications. In: Second Symposium on Network Cloud Computing and Applications (NCCA), pp. 116–123 (2012)Google Scholar
  4. 4.
    Armbrust, M., et al.: Above the Clouds: A Berkeley View of Cloud Computing. Tech. Rep. UCB/EECS-2009-28, EECS Department, University of California, Berkeley (2009)Google Scholar
  5. 5.
    Bardohl, R., Ehrig, H., De Lara, J., Runge, O., Taentzer, G., Weinhold, I.: Node type inheritance concept for typed graph transformation. Tech. Rep. 2003-19, TU Berlin (2003),
  6. 6.
    Binz, T., Breitenbücher, U., Kopp, O., Leymann, F.: TOSCA: Portable Automated Deployment and Management of Cloud Applications. In: Advanced Web Services, pp. 527–549. Springer (2014)Google Scholar
  7. 7.
    Brandtzæg, E., Mohagheghi, P., Mosser, S.: Towards a domain-specific language to deploy applications in the clouds. In: The Third International Conference on Cloud Computing, GRIDs, and Virtualization, Cloud Computing 2012, pp. 213–218. IARIA (2012)Google Scholar
  8. 8.
    Frey, S., Hasselbring, W.: The cloudmig approach: Model-based migration of software systems to cloud-optimized applications. International Journal on Advances in Software 4(3 and 4), 342–353 (2011)Google Scholar
  9. 9.
    Gray, J.: Distributed Computing Economics. Queue 6(3), 63–68 (2008)CrossRefGoogle Scholar
  10. 10.
    Khajeh-Hosseini, A., Greenwood, D., Smith, J.W., Sommerville, I.: The cloud adoption toolkit: supporting cloud adoption decisions in the enterprise. Software: Practice and Experience 42(4), 447–465 (2012)Google Scholar
  11. 11.
    Koziolek, A., Koziolek, H., Reussner, R.: Peropteryx: automated application of tactics in multi-objective software architecture optimization. In: Proceedings of the joint ACM SIGSOFT QoSA and ISARCS, pp. 33–42. ACM (2011)Google Scholar
  12. 12.
    de Lara, J., Bardohl, R., Ehrig, H., Ehrig, K., Prange, U., Taentzer, G.: Attributed graph transformation with node type inheritance. Theoretical Computer Science 376(3), 139–163 (2007)CrossRefzbMATHMathSciNetGoogle Scholar
  13. 13.
    Leymann, F., Fehling, C., Mietzner, R., Nowak, A., Dustdar, S.: Moving applications to the cloud: An approach based on application model enrichment. International Journal of Cooperative Information Systems 20(03), 307–356 (2011)CrossRefGoogle Scholar
  14. 14.
    Malek, S., Medvidovic, N., Mikic-Rakic, M.: An extensible framework for improving a distributed software system’s deployment architecture. IEEE Transactions on Software Engineering 38(1), 73–100 (2012)CrossRefGoogle Scholar
  15. 15.
    Martens, A., Koziolek, H., Becker, S., Reussner, R.: Automatically improve software architecture models for performance, reliability, and cost using evolutionary algorithms. In: Proceedings of the First Joint WOSP/SIPEW International Conference on Performance Engineering, pp. 105–116. ACM (2010)Google Scholar
  16. 16.
    Menzel, M., Ranjan, R.: Cloudgenius: decision support for web server cloud migration. In: Proceedings of the 21st International Conference on World Wide Web, WWW 2012, pp. 979–988. ACM, New York (2012)CrossRefGoogle Scholar
  17. 17.
    Miglierina, M., Gibilisco, G., Ardagna, D., Di Nitto, E.: Model based control for multi-cloud applications. In: 5th International Workshop on Modeling in Software Engineering (MiSE), pp. 37–43 (2013)Google Scholar
  18. 18.
    Mirkovic, J., Faber, T., Hsieh, P., Malaiyandisamy, G., Malaviya, R.: DADL: Distributed Application Description Language. Tech. Rep. ISI-TR-664, USC/ISI (2010),
  19. 19.
    Nguyen, D.K., Lelli, F., Papazoglou, M.P., Van Den Heuvel, W.J.: Blueprinting approach in support of cloud computing. Future Internet 4(1), 322–346 (2012)CrossRefGoogle Scholar
  20. 20.
    Papazoglou, M.P., van den Heuvel, W.: Blueprinting the cloud. Internet Computing 15(6), 74–79 (2011)CrossRefGoogle Scholar
  21. 21.
    Sharma, U., Shenoy, P., Sahu, S., Shaikh, A.: Kingfisher: Cost-aware elasticity in the cloud. In: Proceedings of INFOCOM 2011, pp. 206–210. IEEE (2011)Google Scholar
  22. 22.
    Suleiman, B., Sakr, S., Jeffery, R., Liu, A.: On understanding the economics and elasticity challenges of deploying business applications on public cloud infrastructure. Journal of Internet Services and Applications, 1–21 (2011)Google Scholar
  23. 23.
    Walker, E.: The real cost of a cpu hour. Computer 42(4), 35–41 (2009)CrossRefGoogle Scholar
  24. 24.
    Xiu, M., Andrikopoulos, V.: The Nefolog & MiDSuS Systems for Cloud Migration Support. Technical Report 2013/08, Universität Stuttgart, Fakultät Informatik, Elektrotechnik und Informationstechnik, Germany (November 2013),

Copyright information

© Springer International Publishing Switzerland 2014

Authors and Affiliations

  • Vasilios Andrikopoulos
    • 1
  • Santiago Gómez Sáez
    • 1
  • Frank Leymann
    • 1
  • Johannes Wettinger
    • 1
  1. 1.IAASUniversity of StuttgartStuttgartGermany

Personalised recommendations