Advertisement

Cooperative Game Theory-Based Request Distribution Model in Federated Cloud Environment

  • Sahil KansalEmail author
  • Harish Kumar
  • Sakshi Kaushal
Conference paper
  • 17 Downloads
Part of the Advances in Intelligent Systems and Computing book series (AISC, volume 1089)

Abstract

Cloud computing has emerged as the most important paradigm of distributed computing in the last decade. Increasing demand of the cloud users and inadequacy of resources along with the cloud providers has encouraged the federation of multiple cloud providers. In federation, multiple rational providers coordinate for the execution of the user’s tasks. In federated cloud, the distribution of the user’s request for resources and revenue among the providers has evolved as the most challenging task. Existing works aim at the profit maximization of the providers while discounting the importance of fair distribution. This paper presents cooperative game theoretic model for the fair distribution of revenue and resources among the providers, and analyzes the variation of power index with the change in the user’s request. For analysis of the proposed model, comparative evaluation is performed with the existing distribution model. An experimental result demonstrates that the proposed model distributes the resource request and revenue more fairly that the existing state of art.

Keywords

Federated cloud Cooperative game theory Shapley Shubik Power Index Request distribution 

References

  1. 1.
    Armbrust, M., Fox, A., Griffith, R., Joseph, A.D., Katz, R., Konwinski, A., Zaharia, M.: A view of cloud computing. Commun. ACM 53(4), 50–58 (2010)CrossRefGoogle Scholar
  2. 2.
    Liaqat, M., Chang, V., Gani, A., Ab Hamid, S.H., Toseef, M., Shoaib, U., Ali, R.L.: Federated cloud resource management: review and discussion. J. Netw. Comput. Appl. 77, 87–105 (2017)CrossRefGoogle Scholar
  3. 3.
    Niyato, D., Vasilakos, A.V., Kun, Z.: Resource and revenue sharing with coalition formation of cloud providers: game theoretic approach. In: 11th IEEE/ACM International Symposium on Cluster, Cloud and Grid Computing (CCGrid), pp. 215–224. IEEE (2011)Google Scholar
  4. 4.
    Hassan, M.M., Al-Wadud, M.A., Fortino, G.: A socially optimal resource and revenue sharing mechanism in cloud federations. In: IEEE 19th International Conference on Computer Supported Cooperative Work in Design (CSCWD), pp. 620–625. IEEE (2015)Google Scholar
  5. 5.
    El Zant, B., Amigo, I., Gagnaire, M.: Game theoretic approaches for revenue sharing in federated cloud. In: IEEE 3rd International Conference Cloud Networking (CloudNet), pp. 300–306. IEEE (2014)Google Scholar
  6. 6.
    Mihailescu, M., Teo, Y.M.: Strategy-proof dynamic resource pricing of multiple resource types on federated clouds. In: International Conference on Algorithms and Architectures for Parallel Processing, pp. 337–350. Springer, Berlin, Heidelberg (2010)Google Scholar
  7. 7.
    Mihailescu, M., Teo, Y.M.: Dynamic resource pricing on federated clouds. In: Proceedings of the 10th IEEE/ACM International Conference on Cluster, Cloud and Grid Computing, pp. 513–517. IEEE (2010)Google Scholar
  8. 8.
    Mashayekhy, L., Nejad, M.M., Grosu, D.: Cloud federations in the sky: formation game and mechanism. IEEE Trans. Cloud Comput. 3(1), 14–27 (2015)CrossRefGoogle Scholar
  9. 9.
    Hassan, M.M., Song, B., Huh, E.N.: A market-oriented dynamic collaborative cloud services platform. Ann. Telecommun. Annales des Telecommun. 65(11), 669–688 (2010)CrossRefGoogle Scholar
  10. 10.
    Amazon Web Services, [Online]. Available: https://aws.amazon.com/pricing/. Accessed 8 Dec 2017
  11. 11.
    Truong-Huu, T., Tham, C.K.: A game-theoretic model for dynamic pricing and competition among cloud providers. In: IEEE/ACM 6th International Conference Utility and Cloud Computing (UCC), pp. 235–238. IEEE (2013)Google Scholar
  12. 12.
    Guazzone, M., Anglano, C. and Sereno, M.: A game-theoretic approach to coalition formation in green cloud federations. In: 2014 14th IEEE/ACM International Symposium Cluster, Cloud and Grid Computing (CCGrid), pp. 618–625. IEEE (2014)Google Scholar
  13. 13.
    Chalkiadakis, G., Elkind, E., Wooldridge, M.: Computational Aspects of Cooperative Game Theory. Morgan and Claypool Publisher, CA (2011)CrossRefGoogle Scholar
  14. 14.
    Cloud Harmony: Gartner Company, [Online]. Available: https://cloudharmony.com/. Accessed 2 Oct 2017

Copyright information

© Springer Nature Singapore Pte Ltd. 2020

Authors and Affiliations

  1. 1.University Institute of Engineering and TechnologyPanjab UniversityChandigarhIndia

Personalised recommendations