Skip to main content
SpringerLink
Log in

VRAA: virtualized resource auction and allocation based on incentive and penalty

  • Published:
Cluster Computing Aims and scope Submit manuscript

Abstract

Virtualization is widely used in cloud computing environments to efficiently manage resources, but it also raises several challenges. One of them is the fairness issue of resource allocation among virtual machines. Traditional virtualized resource allocation approaches distribute physical resources equally without taking into account the actual workload of each virtual machine and thus often leads to wasting. In this paper, we propose a virtualized resource auction and allocation model (VRAA) based on incentive and penalty to correct this wasting problem. In our approach, we use Nash equilibrium of cooperative games to fairly allocate resources among multiple virtual machines to maximize revenue of the system. To illustrate the effectiveness of the proposed approach, we then apply the basic laws of auction gaming to investigate how CPU allocation and contention can affect applications’ performance (i.e., response time), and its effect on CPU utilization. We find that in our VRAA model, the fairness index is high, and the resource allocation is closely proportional to the actual workloads of the virtual machines, so the wasting of resources is reduced. Experiment results show that our model is general, and can be applied to other virtualized non-CPU resources.

This is a preview of subscription content, log in via an institution to check access.

Access this article

Log in via an institution

Price excludes VAT (USA)
Tax calculation will be finalised during checkout.

Instant access to the full article PDF.

Institutional subscriptions

Fig. 1
Fig. 2
Fig. 3
Fig. 4
Fig. 5
Fig. 6
Fig. 7
Fig. 8
Fig. 9

Similar content being viewed by others

References

  1. Padala, P., Hou, K.-Y., Shin, K.G., Zhu, X., Uysal, M., Wang, Z., Singhal, S., Merchant, A.: Automated control of multiple virtualized resources. In: Proceedings of the European Conference on Computer Systems (EuroSys), pp. 13–26 (2009)

    Google Scholar 

  2. Urgaonkar, B., Pacifici, G., Shenoy, P., Spreitzer, M., Tantawi, A.: An analytical model for multi-tier Internet services and its applications. In: Proceedings of the ACM International Conference on Measurement and Modeling of Computer Systems (SIGMETRICS), vol. 33, pp. 291–302 (2005)

    Google Scholar 

  3. Zhang, Q., Cherkasova, L., Smirni, E.: A regression-based analytic model for dynamic resource provisioning of multi-tier application. In: Proceedings of the 4th Int. Conf. on Autonomic Computing and Communications (ICAC), pp. 27–37 (2007)

    Google Scholar 

  4. Watson, B.J., Marwah, M., Gmach, D., Chen, Y., Arlitt, M., Wang, Z.: Probabilistic performance modeling of virtualized resource allocation. In: Proceedings of International Conference on Autonomic Computing (ICAC), pp. 99–108 (2010)

    Google Scholar 

  5. Jiang, C., Xu, X., Zhang, J., Li, Y., Wan, J.: Resource allocation in contending virtualized environments through VM performance modeling and feedback. In: Proceedings of 2011 6th Annual ChinaGrid Conference (ChinaGrid), pp. 196–203 (2011)

    Chapter  Google Scholar 

  6. Maille, P., Tuffin, B.: Analysis of price competition in a slotted resource allocation game. In: Proceedings of 27th Annual IEEE International Conference on Computer Communications (INFOCOM), pp. 888–896 (2008)

    Google Scholar 

  7. Key, P., Mcauley, D.: Differential QoS and pricing in networks: where flow-control meets game theory. IEEE Proc. Softw. 146(1), 39–43 (1999)

    Article  Google Scholar 

  8. Grosu, D., Chronopoulos, A.T., Leung, M.Y.: Load balancing in distributed systems: an approach using cooperative games. In: Proceedings of IEEE International Parallel and Distributed Processing Symposium(IPDPS), pp. 52–61 (2002)

    Google Scholar 

  9. Fang, Z., Bensaou, B.: Fair bandwidth sharing algorithms based on game theory frameworks for wireless ad-hoc networks. In: Proceedings of 23rd Annual IEEE International Conference on Computer Communications (INFOCOM), pp. 1284–1295 (2004)

    Google Scholar 

  10. Buyya, R., Abramson, D., Giddy, J., Stockinger, H.: Economic models for resource management and scheduling in grid computing. J. Concurr. Comput., Pract. Exp. 14, 1507–1542 (2002)

    Article  MATH  Google Scholar 

  11. Ghosh, P., Roy, N., Basu, K., Das, S.K.: A game theory based pricing strategy for job allocation in mobile grids. In: Proceedings of the 18th IEEE International Parallel and Distributed Processing Symposium (IPDPS), pp. 82–91 (2004)

    Google Scholar 

  12. Ghosh, P., Roy, N., Basu, K., Das, S.K., Basu, K.: A pricing strategy for job allocation in mobile grids using a non-cooperative bargaining theory framework. J. Parallel Distrib. Comput. 65, 1366–1383 (2005)

    Article  MATH  Google Scholar 

  13. Rzadca, K., Trystram, D., Wierzbicki, A.: Fair game-theoretic resource management in dedicated grids. In: Proceedings of the Seventh IEEE International Symposium on Cluster Computing and the Grid (CCGrid), pp. 343–350 (2007)

    Chapter  Google Scholar 

  14. Ghosh, P., Das, S.K.: Mobility-aware cost-efficient job scheduling for single-class grid jobs in a generic mobile grid architecture. Future Gener. Comput. Syst. 26(8), 1356–1367 (2010)

    Article  Google Scholar 

  15. Yolken, B., Bambos, N.: Game based capacity allocation for utility computing environments. Telecommun. Syst. 47, 165–181 (2011)

    Article  Google Scholar 

  16. Wei, G., Athanasios, V., Zheng, Y., Xiong, N.: A game-theoretic method of fair resource allocation for cloud computing services. J. Supercomput. 54(2), 252–269 (2009)

    Article  Google Scholar 

  17. Ardagna, D., Panicucci, B., Passacantando, M.: A game theoretic formulation of the service provisioning problem in cloud systems. In: Proceedings of the 20th international conference on World Wide Web (WWW), pp. 177–186 (2011)

    Chapter  Google Scholar 

  18. Niyato, D., Vasilakos, A., Kun, Z.: Resource and revenue sharing with coalition formation of cloud providers: game theoretic approach. In: Proceedings of IEEE/ACM International Symposium on Cluster Cloud and Grid Computing, pp. 215–224 (2011)

    Google Scholar 

  19. Gui, C., Jian, Q., Wang, H.: Repeated game theory based penalty incentive mechanism in Internet-based virtual computing environment. J. Softw. 21(12), 3042–3055 (2010)

    Article  Google Scholar 

  20. Ma, R.T.B., Lee, S.C.M., Lui, J.C.S.: Incentive and service differentiation in P2P networks: a game theoretic approach. IEEE/ACM Trans. Netw. 14(5), 978–991 (2006)

    Article  Google Scholar 

Download references

Acknowledgements

The funding supports of this work by Natural Science Fund of China (Nos. 61003077, 60873023 and 60973029), State Key Development Program of Basic Research of China (No. 2007CB310906), Natural Science Fund of Zhejiang Province (Nos. Y1090940, Y1101092, Y1101104), and Research Fund of Department of Education of Zhejiang Province (No. GK100800010) are greatly appreciated.

Author information

Authors and Affiliations

  1. School of Computer Science and Technology, Hangzhou Dianzi University, Hangzhou, 310037, China

    Congfeng Jiang, Liangcheng Duan, Jian Wan & Li Zhou

  2. Department of Mathematics and Computer Science, Valdosta State University, Valdosta, GA, 31698, USA

    Chunlei Liu

Authors
  1. Congfeng Jiang
    View author publications

    You can also search for this author in PubMed Google Scholar

  2. Liangcheng Duan
    View author publications

    You can also search for this author in PubMed Google Scholar

  3. Chunlei Liu
    View author publications

    You can also search for this author in PubMed Google Scholar

  4. Jian Wan
    View author publications

    You can also search for this author in PubMed Google Scholar

  5. Li Zhou
    View author publications

    You can also search for this author in PubMed Google Scholar

Corresponding author

Correspondence to Congfeng Jiang.

Rights and permissions

Reprints and permissions

About this article

Cite this article

Jiang, C., Duan, L., Liu, C. et al. VRAA: virtualized resource auction and allocation based on incentive and penalty. Cluster Comput 16, 639–650 (2013). https://doi.org/10.1007/s10586-012-0235-6

Download citation

  • Received:

  • Accepted:

  • Published:

  • Issue Date:

  • DOI: https://doi.org/10.1007/s10586-012-0235-6

Keywords

Search

Navigation