A Brokerage Architecture: Cloud Service Selection

  • Hela Malouche
  • Youssef Ben Halima
  • Henda Ben Ghezala
Conference paper
Part of the Lecture Notes in Computer Science book series (LNCS, volume 10380)

Abstract

Due to the various benefits of cloud computing such as flexibility and ease of management, several organizations decided to adopt its services. However, with the large number of available cloud services, the selection of services which meets the specific requirements of the user becomes a complex task. This paper proposes a cloud brokerage architecture which allows selecting cloud services based on functional and non-functional requirements identified by the user. Before selecting the best cloud service which satisfies the user, it is important to know the significance of each parameter that characterizes the cloud service. For this reason, we will use the objective ranking of attributes approach based on rough set theory. In this paper, the selection of cloud service by the broker is done using a developed version of the CM-factory algorithm which takes into account the organization cross-cutting concerns.

Keywords

Cloud computing Brokerage architecture Service selection CM-factory algorithm Rough set theory 

References

  1. 1.
    Fowley, F., Pahl, C., Zhang, L.: A comparison framework and review of service brokerage solutions for cloud architectures. service-oriented computing, ICSOC 2013 Workshops 8377, pp. 137-149 (2014)Google Scholar
  2. 2.
    ElHoussaini, C., Hafiddi, H., Nassar, M., Kriouile, A.: CM-factory for enabling enterprise migration to cloud. Int. J. Cloud Comput. 4(3), 211–233 (2015) Google Scholar
  3. 3.
    Liu, Y., Esseghir, M., Boulahia, L.M.: Evaluation of parameters importance in cloud service selection using rough sets. Appl. Math. 7, 527–541 (2016)CrossRefGoogle Scholar
  4. 4.
    Yu, T., Lin, K.J.: The design of QoS broker algorithms for QoS-capable web services. Int. J. Web Serv. Res. (IJWSR) 1(4), 33–50 (2004)CrossRefGoogle Scholar
  5. 5.
    Clark, K., Warnier, M., Brazier, F.M.T.: An intelligent cloud resource allocation service. In: Proceedings of the International Conference on Cloud Computing and Services Science (CLOSER2012), pp. 37–45 (2012)Google Scholar
  6. 6.
    Lamparter, S., Ankolekar, A., Studer, R., Grimm, S.: Preference-based selection of highly configurable web services. In: Proceedings of the 16th International Conference on World Wide Web, pp. 1013–1022. ACM, New York (2007)Google Scholar
  7. 7.
    Menzel, M., Ranjan, R.: Cloudgenius: decision support for web server cloud migration. In: Proceedings of the 21st International Conference on World Wide Web, pp. 979–988. ACM, New York (2012)Google Scholar
  8. 8.
    Zhang, M., Ranjan, R., Nepal, S., Menzel, M., Haller, A.: A declarative recommender system for cloud infrastructure services selection. In: Vanmechelen, K., Altmann, J., Rana, O.F. (eds.) GECON 2012. LNCS, vol. 7714, pp. 102–113. Springer, Heidelberg (2012). doi: 10.1007/978-3-642-35194-5_8 CrossRefGoogle Scholar
  9. 9.
    Son, S., Jung, G., Jun, S.C.: An sla-based cloud computing that facilitates resource allocation in the distributed data centers of a cloud provider. J. Supercomput. 64(2), 606–637 (2013)CrossRefGoogle Scholar
  10. 10.
    Emeakaroha, V.C., Brandic, I., Maurer, M., Breskovic, I.: SLA-aware application deployment and resource allocation in clouds. computer software and applications conference workshops (COMPSACW), 2011. IEEE 35th Annual, pp. 298–303 (2011)Google Scholar
  11. 11.
    Wu, L., Garg, S.K., Buyya, R.: SLA-based resource allocation for software as a service provider (SaaS) in cloud computing environments. In: 11th IEEE/ACM International Symposium on Cluster, Cloud and Grid Computing (CCGrid), pp. 195-204. IEEE (2011)Google Scholar
  12. 12.
    Wu, L., Garg, S.K., Versteeg, S., Buyya, R.: SLA-based resource provisioning for hosted software-as-a-service applications in cloud computing environments. IEEE Trans. Serv. Comput. 7(3), 465–485 (2014)CrossRefGoogle Scholar
  13. 13.
    Dastjerdi, A.V., Tabatabaei, S.G.H., Buyya, R.: An effective architecture for automated appliance management system applying ontology-based cloud discovery. 2010. In: 10th IEEE/ACM International Conference on Cluster, Cloud and Grid Computing (CCGrid), pp. 104–112 (2010)Google Scholar
  14. 14.
    Hsu, C.L.: A cloud service selection model based on user-specified quality of service level. computer science & information technology (CS & IT), pp. 43–54 (2014)Google Scholar
  15. 15.
    Nussbaumer, N., Liu, X.: Cloud migration for SMEs in a service oriented approach. computer software and applications conference workshops (COMPSACW), 2013. IEEE 37th Annual, pp. 457–462, 22-26 July 2013 (2013)Google Scholar
  16. 16.
    Ruiz-Alvarez, A., Humphrey, M.: An automated approach to cloud storage service selection. In: Proceedings of the 2nd Workshop on Scientific Cloud Computing (Science Cloud 2011), pp. 39–48. ACM, New York (2011)Google Scholar
  17. 17.
    Kwon, H.K., Seo, K.K.: A decision-making model to choose a cloud service using fuzzy AHP. Adv. Sci. Technol. Lett. Cloud Super Comput. 35, 93–96 (2013)Google Scholar
  18. 18.
    Qu, L., Wang, Y., Orgun, M.A.: Cloud service selection based on the aggregation of user feedback and quantitative performance assessment. In: Proceedings of the IEEE 10th International Conference on Services Computing (SCC 2013), pp. 152–159 (2013)Google Scholar
  19. 19.
    Li, A., Yang, X., Kandula, S., Zhang, M.: CloudCmp: comparing public cloud providers. In: Proceedings of the 10th ACM SIGKCOMM Conference on Internet Measurement, IMC2010, pp. 1–14. ACM (2010)Google Scholar
  20. 20.
    Beserra, P.V., Camara, A., Ximenes, R., Albuquerque, A.B., Mendonça, N.C.: Cloudstep: a step-by-step decision process to support legacy application migration to the cloud. In: Proceedings of IEEE 6th International Workshop on the Maintenance and Evolution of Service-Oriented and Cloud-Based Systems (MESOCA), pp. 7–16. IEEE, Trento (2012)Google Scholar
  21. 21.
    Farokhi, S., Jrad, F., Brandic, I., Streit, A.: HS4MC-hierarchical SLA-based service selection for multi-cloud environments. In: Proceedings of the 4th International Conference on Cloud Computing and Services Science (CLOSER 2014), pp. 722–734. Barcelona, Spain (2014)Google Scholar
  22. 22.
    Jrad, F., Tao, J., Streit, A., Knapper, R., Flath, C.: A utility-based approach for customised cloud service selection. Int. J. Comput. Sci. Eng. 10(1/2), 32–44 (2015)CrossRefGoogle Scholar

Copyright information

© Springer International Publishing AG 2017

Authors and Affiliations

  • Hela Malouche
    • 1
  • Youssef Ben Halima
    • 1
  • Henda Ben Ghezala
    • 1
  1. 1.RIADI Labs, National School of Computer ScienceManouba UniversityTunisTunisia

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