Testing and Comparing the Performance of Cloud Service Providers Using a Service Broker Architecture

  • Divyaa Manimaran Elango
  • Frank Fowley
  • Claus Pahl
Conference paper
Part of the Communications in Computer and Information Science book series (CCIS, volume 824)

Abstract

Service brokers are tools that allow different individual service providers to be integrated. An API can be a mechanism to provide a joint interface. Broker can actually also be use for more than integration. We use a cloud service broker that implements a multi-cloud abstraction API in order to carry out performance comparisons between different cloud services. The broker tool here is a multi-cloud storage API that integrates a number of provided storage services. The library supporting the API is organised into three services, which are a file, a blob and a table service. Using this broker architecture, we developed a performance test scenario to compare the different providers, i.e., to compare a range of storage operations by different providers.

Notes

Acknowledgements

This work was partly supported by IC4 (Irish Centre for Cloud Computing and Commerce), funded by EI and the IDA.

References

  1. 1.
    Ried, S.: Cloud Broker - A New Business Model Paradigm. Forrester (2011)Google Scholar
  2. 2.
    Elango, D.M., Fowley, F., Pahl, C.: An ontology-based architecture for an adaptable cloud storage broker. In: Advances in Service-Oriented and Cloud Computing. Springer CCIS (2018, to appear)Google Scholar
  3. 3.
    Benslimane, D., Dustdar, S., Sheth, A.: Services mashups - the new generation of web applications. Internet Comput. 12(5), 13–15 (2008)CrossRefGoogle Scholar
  4. 4.
    Bernstein, D., Ludvigson, E., Sankar, K., Diamond, S., Morrow, M.: Blueprint for the inter-cloud: protocols and formats for cloud computing interoperability. In: International Conference on Internet and Web Applications and Services (2009)Google Scholar
  5. 5.
    Buyya, R., Ranjan, R., Calheiros, R.N.: InterCloud: utility-oriented federation of cloud computing environments for scaling of application services. In: Hsu, C.-H., Yang, L.T., Park, J.H., Yeo, S.-S. (eds.) ICA3PP 2010. LNCS, vol. 6081, pp. 13–31. Springer, Heidelberg (2010).  https://doi.org/10.1007/978-3-642-13119-6_2CrossRefGoogle Scholar
  6. 6.
    Cloud Standards (2017). http://cloud-standards.org/
  7. 7.
  8. 8.
    Fehling, C., Mietzner, R.: Composite as a service: cloud application structures, provisioning, and management. Inf. Technol. 53(4), 188–194 (2011)Google Scholar
  9. 9.
    Pahl, C., Jamshidi, P., Weyns, D.: Cloud architecture continuity: change models and change rules for sustainable cloud software architectures. J. Softw. Evol. Process 29(2) (2017)Google Scholar
  10. 10.
    Pahl, C., Jamshidi, P., Zimmermann, O.: Architectural principles for cloud software. In: ACM Transactions on Internet Technology. (2018, to appear)Google Scholar
  11. 11.
    Fowley, F., Pahl, C., Zhang, L.: A comparison framework and review of service brokerage solutions for cloud architectures. In: 1st International Workshop on Cloud Service Brokerage (2013)Google Scholar
  12. 12.
    Fowley, F., Pahl, C., Jamshidi, P., Fang, D., Liu, X.: A classification and comparison framework for cloud service brokerage architectures. IEEE Trans. Cloud Comput. (2017).  https://doi.org/10.1109/TCC.2016.2537333. http://ieeexplore.ieee.org/document/7423741/
  13. 13.
    Garcia-Gomez, S., et al.: Challenges for the comprehensive management of cloud services in a PaaS framework. Scalable Comput. Pract. Experience 13(3), 201–213 (2012)Google Scholar
  14. 14.
    Elango, D.M., Fowley, F., Pahl, C.: Pattern-driven architecting of an adaptable ontology-driven cloud storage broker. In: University of Oslo, Department of Informatics, Research report 471, pp. 33–47 (2017)Google Scholar
  15. 15.
    Gartner: Cloud Services Brokerage. Gartner Research (2013). http://www.gartner.com/it-glossary/cloud-servicesbrokerage-csb
  16. 16.
    Grozev, N., Buyya, R.: InterCloud architectures and application brokering: taxonomy and survey. Softw. Pract. Experience 44(3), 369–390 (2012)CrossRefGoogle Scholar
  17. 17.
    Pahl, C., Jamshidi, P.: Microservices: a systematic mapping study. In: Proceedings CLOSER Conference, pp. 137–146 (2016)Google Scholar
  18. 18.
    Taibi, D., Lenarduzzi, V., Pahl, C.: Processes, motivations and issues for migrating to microservices architectures: an empirical investigation. IEEE Cloud Comput. (2018). Accepted for publicationGoogle Scholar
  19. 19.
    Hofer, C.N., Karagiannis, G.: Cloud computing services: taxonomy and comparison. J. Internet Serv. Appl. 2(2), 81–94 (2011)CrossRefGoogle Scholar
  20. 20.
    IEEE Cloud Standards (2015). http://cloudcomputing.ieee.org/standards
  21. 21.
    Jamshidi, P., Ahmad, A., Pahl, C.: Cloud migration research: a systematic review. IEEE Trans. Cloud Comput. 1(2), 142–157 (2013)CrossRefGoogle Scholar
  22. 22.
    jclouds: jclouds Java and Clojure Cloud API (2015). http://www.jclouds.org/
  23. 23.
    Ferrer, A.J., et al.: OPTIMIS: a holistic approach to cloud service provisioning. Future Gener. Comput. Syst. 28(1), 66–77 (2012)CrossRefGoogle Scholar
  24. 24.
    Gacitua-Decar, V., Pahl, C.: Structural process pattern matching based on graph morphism detection. Int. J. Softw. Eng. Knowl. Eng. 27(2), 153–189 (2017)CrossRefGoogle Scholar
  25. 25.
    Pahl, C.: Layered ontological modelling for web service-oriented model-driven architecture. In: Hartman, A., Kreische, D. (eds.) ECMDA-FA 2005. LNCS, vol. 3748, pp. 88–102. Springer, Heidelberg (2005).  https://doi.org/10.1007/11581741_8CrossRefGoogle Scholar
  26. 26.
    Pahl, C., Giesecke, S., Hasselbring, W.: Ontology-based modelling of architectural styles. Inf. Softw. Technol. 51(12), 1739–1749 (2009)CrossRefGoogle Scholar
  27. 27.
    Pahl, C., Xiong, H.: Migration to PaaS clouds - migration process and architectural concerns. In: IEEE 7th International Symposium on the Maintenance and Evolution of Service-Oriented and Cloud-Based Systems MESOCA (2013)Google Scholar
  28. 28.
    Konstantinou, A.V., Eilam, T., Kalantar, M., Totok, A.A., Arnold, W., Sniblel, E.: An architecture for virtual solution composition and deployment in infrastructure clouds. In: International Workshop on Virtualization Technologies in Distributed Computing (2009)Google Scholar
  29. 29.
    Jamshidi, P., Sharifloo, A., Pahl, C., Arabnejad, H., Metzger, A., Estrada, G.: Fuzzy self-learning controllers for elasticity management in dynamic cloud architectures. In: 12th International ACM SIGSOFT Conference on Quality of Software Architectures QoSA (2016)Google Scholar
  30. 30.
    Arabnejad, H., Jamshidi, P., Estrada, G., El Ioini, N., Pahl, C.: An auto-scaling cloud controller using fuzzy Q-learning - implementation in openstack. In: Aiello, M., Johnsen, E.B., Dustdar, S., Georgievski, I. (eds.) ESOCC 2016. LNCS, vol. 9846, pp. 152–167. Springer, Cham (2016).  https://doi.org/10.1007/978-3-319-44482-6_10CrossRefGoogle Scholar
  31. 31.
    Mietzner, R., Leymann, F., Papazoglou, M.: Defining composite configurable SaaS application packages using SCA. In: International Conference on Internet and Web Applications and Services, Variability Descriptors and Multi-tenancy Patterns (2008)Google Scholar
  32. 32.
    Pahl, C., Xiong, H., Walshe, R.: A comparison of on-premise to cloud migration approaches. In: Lau, K.-K., Lamersdorf, W., Pimentel, E. (eds.) ESOCC 2013. LNCS, vol. 8135, pp. 212–226. Springer, Heidelberg (2013).  https://doi.org/10.1007/978-3-642-40651-5_18CrossRefGoogle Scholar
  33. 33.
    Petcu, D., et al.: Portable cloud applications - from theory to practice. Future Gen. Comput. Syst. 29(6), 1417–1430 (2013)CrossRefGoogle Scholar
  34. 34.
    Javed, M., Abgaz, Y.M., Pahl, C.: Ontology change management and identification of change patterns. J. Data Semant. 2(2–3), 119–143 (2013)CrossRefGoogle Scholar
  35. 35.
    Amazon Simple Storage Service (S3) Cloud Storage AWS. https://aws.amazon.com/s3/
  36. 36.
  37. 37.
    Azure Storage - Secure cloud storage. https://azure.microsoft.com/en-us/services/storage/
  38. 38.
    Google Drive - Cloud Storage & File Backup. https://www.google.com/drive/
  39. 39.
    Jamshidi, P., Pahl, C., Mendonca, N.C.: Pattern-based multi-cloud architecture migration. Softw. Pract. Experience 47(9), 1159–1184 (2017)CrossRefGoogle Scholar
  40. 40.
    Pahl, C., Brogi, A., Soldani, J., Jamshidi, P.: Cloud container technologies: a state-of-the-art review. IEEE Trans. Cloud Comput. (2017).  https://doi.org/10.1109/TCC.2017.2702586. http://ieeexplore.ieee.org/document/7922500/
  41. 41.
    Aderaldo, C.M., Mendonca, N.C., Pahl, C., Jamshidi, P.: Benchmark requirements for microservices architecture research. In: 1st International Workshop on Establishing the Community-Wide Infrastructure for Architecture-Based Software Engineering. IEEE (2017)Google Scholar
  42. 42.
    Heinrich, R., van Hoorn, A., Knoche, H., Li, F., Lwakatare, L.E., Pahl, C., Schulte, S., Wettinger, J.: Performance engineering for microservices: research challenges and directions. In: Proceedings of the 8th ACM/SPEC on International Conference on Performance Engineering Companion (2017)Google Scholar

Copyright information

© Springer International Publishing AG, part of Springer Nature 2018

Authors and Affiliations

  • Divyaa Manimaran Elango
    • 1
  • Frank Fowley
    • 1
  • Claus Pahl
    • 2
  1. 1.IC4Dublin City UniversityDublinIreland
  2. 2.SwSEFree University of Bozen-BolzanoBolzanoItaly

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