Towards a PaaS Architecture for Resource Allocation in IaaS Providers Considering Different Charging Models

  • Cristiano C. A. Vieira
  • Luiz F. Bittencourt
  • Edmundo R. M. Madeira
Part of the Lecture Notes in Computer Science book series (LNCS, volume 8193)


With the increase in computing infrastructure commercialization through the pay-as-you-go model, competition among providers puts the user as a decision agent on which is the best provider to comply with his/her demands and requirements. Currently, users rely on instances offered as on-demand, reserved, and spot to decide which is the best resource allocation model over the time. In this work, we present substantial contributions to compose a PaaS architecture that leverages different charging models, where we propose the use of a new charging model called time-slotted reservation. Moreover, we developed an integer linear program (ILP) to perform the scheduling of incoming requests according to different QoS levels, proposing a mapping of those levels into the charging models offered by IaaS providers. Simulations show the applicability of the ILP in the proposed model, being able to maximize the number of requisitions executed following the user’s QoS requirements.


Cloud Computing Architecture PaaS IaaS Charging model Scheduling 


Unable to display preview. Download preview PDF.

Unable to display preview. Download preview PDF.


  1. 1.
    Assunção, M.D., Costanzo, A., Buyya, R.: A cost-benefit analysis of using cloud computing to extend the capacity of clusters. Cluster Computing 13(3), 335–347 (2010)CrossRefGoogle Scholar
  2. 2.
    Genez, T.A.L., Bittencourt, L.F., Madeira, E.R.M.: Workflow scheduling for SaaS / PaaS cloud providers considering two SLA levels. In: 2012 IEEE Network Operations and Management Symposium (NOMS), pp. 906–912 (April 2012)Google Scholar
  3. 3.
    Bittencourt, L.F., Senna, C.R., Madeira, E.R.M.: Scheduling service workflows for cost optimization in hybrid clouds. In: Proceedings of the International Conference on Network and Service Management (CNSM), pp. 394–397 (October 2010)Google Scholar
  4. 4.
    Díaz Sánchez, F., Doumith, E.A., Al Zahr, S., Gagnaire, M.: An economic agent maximizing cloud provider revenues under a pay-as-you-book pricing model. In: Vanmechelen, K., Altmann, J., Rana, O.F. (eds.) GECON 2012. LNCS, vol. 7714, pp. 29–45. Springer, Heidelberg (2012)CrossRefGoogle Scholar
  5. 5.
    Zhao, H., Yu, Z., Tiwari, S., Mao, X., Lee, K., Wolinsky, D., Li, X., Figueiredo, R.: Cloudbay: Enabling an online resource market place for open clouds. In: Proceedings of 5th IEEE/ACM International Conference on Utility and Cloud Computing, UCC 2012, Chicago, USA (2012)Google Scholar
  6. 6.
    Toosi, A.N., Thulasiram, R.K., Buyya, R.: Financial option market model for federated cloud environments. In: Proceedings of 5th IEEE/ACM International Conference on Utility and Cloud Computing, UCC 2012, Chicago, USA (2012)Google Scholar
  7. 7.
    Chen, J., Wang, C., Zhou, B.B., Sun, L., Lee, Y.C., Zomaya, A.Y.: Tradeoffs between profit and customer satisfaction for service provisioning in the cloud. In: Proceedings of the 20th International Symposium on High Performance Distributed Computing, HPDC 2011, pp. 229–238. ACM, New York (2011)Google Scholar
  8. 8.
    Wu, L., Garg, S., Buyya, R., Chen, C., Versteeg, S.: Automated SLA negotiation framework for cloud computing. In: 2013 13th IEEE/ACM International Symposium on Cluster, Cloud and Grid Computing (CCGrid), pp. 235–244 (2013)Google Scholar
  9. 9.
    Konstantinou, I., Floros, E., Koziris, N.: Public vs private cloud usage costs: the stratuslab case. In: Proceedings of the 2nd International Workshop on Cloud Computing Platforms, CloudCP 2012, pp. 3:1–3:6. ACM, New York (2012)Google Scholar
  10. 10.
    Khajeh-Hosseini, A., Greenwood, D., Sommerville, I.: Cloud migration: A case study of migrating an enterprise it system to IaaS. In: Proceedings of the 2010 IEEE 3rd International Conference on Cloud Computing, CLOUD 2010, pp. 450–457. IEEE Computer Society Press, Washington, DC (2010)Google Scholar
  11. 11.
    Garg, S., Venugopal, S., Buyya, R.: A meta-scheduler with auction based resource allocation for global grids. In: 14th IEEE International Conference on Parallel and Distributed Systems, ICPADS 2008, pp. 187–194 (December 2008)Google Scholar
  12. 12.
    Mihailescu, M., Teo, Y.M.: On economic and computational-efficient resource pricing in large distributed systems. In: Proceedings of the 2010 10th IEEE/ACM International Conference on Cluster, Cloud and Grid Computing, Washington, DC, USA, pp. 838–843 (2010)Google Scholar
  13. 13.
    Raj, G.: An efficient broker cloud management system. In: Proceedings of the International Conference on Advances in Computing and Artificial Intelligence, ACAI 2011, pp. 72–76. ACM, New York (2011)Google Scholar
  14. 14.
    Ibarra, O.H., Kim, C.E.: Heuristic algorithms for scheduling independent tasks on nonidentical processors. J. ACM 24(2), 280–289 (1977)MathSciNetzbMATHCrossRefGoogle Scholar

Copyright information

© Springer International Publishing Switzerland 2013

Authors and Affiliations

  • Cristiano C. A. Vieira
    • 1
  • Luiz F. Bittencourt
    • 2
  • Edmundo R. M. Madeira
    • 2
  1. 1.Faculty of ComputingFederal University of Mato Grosso do SulCampo GrandeBrasil
  2. 2.Institute of ComputingUniversity of CampinasCampinasBrasil

Personalised recommendations