Advertisement

Batch Auction Design for Cloud Container Services

  • Yu He
  • Lin Ma
  • Ruiting ZhouEmail author
  • Chuanhe Huang
Conference paper
Part of the Lecture Notes of the Institute for Computer Sciences, Social Informatics and Telecommunications Engineering book series (LNICST, volume 300)

Abstract

Cloud containers represent a new, light-weight alternative to virtual machines in cloud computing. A user job may be described by a container graph that specifies the resource profile of each container and container dependence relations. This work is the first in the cloud computing literature that designs efficient market mechanisms for container based cloud jobs. Our design targets simultaneously incentive compatibility, computational efficiency, and economic efficiency. It further adapts the idea of batch online optimization into the paradigm of mechanism design, leveraging agile creation of cloud containers and exploiting delay tolerance of elastic cloud jobs. The new and classic techniques we employ include: (i) compact exponential optimization for expressing and handling non-traditional constraints that arise from container dependence and job deadlines; (ii) the primal-dual schema for designing efficient approximation algorithms for social welfare maximization; and (iii) posted price mechanisms for batch decision making and truthful payment design. Theoretical analysis and trace-driven empirical evaluation verify the efficacy of our container auction algorithms.

Keywords

Cloud container Online auction 

References

  1. 1.
  2. 2.
  3. 3.
  4. 4.
  5. 5.
  6. 6.
  7. 7.
    Bitton, S., Emek, Y., Kutten, S.: Efficient dispatching of job batches in emerging clouds. In: Proceedings of IEEE INFOCOM (2018)Google Scholar
  8. 8.
    Chen, B., Deng, X., Zang, W.: On-line scheduling a batch processing system to minimize total weighted job completion time. J. Comb. Optim. 8(1), 85–95 (2004)MathSciNetCrossRefGoogle Scholar
  9. 9.
    Dove, A.: Life science technologies: biology watches the cloud. Science 340(6138), 1350–1352 (2013)CrossRefGoogle Scholar
  10. 10.
    Etzion, H., Moor, S.: Simulation of online selling with posted-price and auctions: comparison of dual channel’s performance under different auction mechanisms. In: Proceedings of HICSS (2008)Google Scholar
  11. 11.
    Golin, M.J., Rote, G.: A dynamic programming algorithm for constructing optimal prefix-free codes with unequal letter costs. IEEE Trans. Inf. Theor. 44(5), 1770–1781 (1998)MathSciNetCrossRefGoogle Scholar
  12. 12.
    Gopinathan, A., Li, Z.: Strategyproof auctions for balancing social welfare and fairness in secondary spectrum markets. In: Proceedings of the IEEE INFOCOM (2011)Google Scholar
  13. 13.
    Gu, S., Li, Z., Wu, C., Huang, C.: An efficient auction mechanism for service chains in the NFV market. In: Proceedings of IEEE INFOCOM (2016)Google Scholar
  14. 14.
    He, S., Guo, L., Guo, Y., Wu, C.: Elastic application container: a lightweight approach for cloud resource provisioning. In: Proceedings of IEEE International Conference on Advanced Information Networking and Applications (2012)Google Scholar
  15. 15.
    Huang, Z., Kim, A.: Welfare maximization with production costs: a primal dual approach. In: Proceedings of ACM-SIAM SODA (2015)Google Scholar
  16. 16.
    Kumar, D., Shae, Z., Jamjoom, H.: Scheduling batch and heterogeneous jobs with runtime elasticity in a parallel processing environment. In: Proceedings of IEEE IPDPSW (2012)Google Scholar
  17. 17.
    Mohamed, N.M., Lin, H., Feng, W.: Accelerating data-intensive genome analysis in the cloud. In: Proceedings of BICoB (2013)Google Scholar
  18. 18.
    Myerson, R.B.: Optimal auction design. Math. Oper. Res. 6(1), 58–73 (1981)MathSciNetCrossRefGoogle Scholar
  19. 19.
    RightScale: Social Gaming in the Cloud: A Technical White Paper (2013)Google Scholar
  20. 20.
    Shi, W., Wu, C., Li, Z.: RSMOA: a revenue and social welfare maximizing online for dynamic cloud resource provisioning. In: Proceedings of IEEE IWQoS (2014)Google Scholar
  21. 21.
    Shi, W., Zhang, L., Wu, C., Li, Z., Lau, F.: An online auction framework for dynamic resource provisioning in cloud computing. In: Proceedings of ACM SIGMETRICS (2014)Google Scholar
  22. 22.
    Tosatto, A., Ruiu, P., Attanasio, A.: Container-based orchestration in cloud: state of the art and challenges. In: Proceedings of Ninth International Conference on Complex, Intelligent, and Software Intensive Systems (2015)Google Scholar
  23. 23.
    Waibel, P., Yeshchenko, A., Schulte, S., Mendling, J.: Optimized container-based process execution in the cloud. In: Panetto, H., Debruyne, C., Proper, H., Ardagna, C., Roman, D., Meersman, R. (eds.) On the Move to Meaningful Internet Systems, OTM 2018 Conferences, OTM 2018. Lecture Notes in Computer Science, vol. 11230, pp. 3–21. Springer, Cham (2018).  https://doi.org/10.1007/978-3-030-02671-4_1CrossRefGoogle Scholar
  24. 24.
    Williamson, D.P.: The primal-dual method for approximation algorithms. Math. Program. 91(3), 447–478 (2002)MathSciNetCrossRefGoogle Scholar
  25. 25.
    Xu, X., Yu, H., Pei, X.: A novel resource scheduling approach in container based clouds. In: Proceedings of IEEE ICCS (2014)Google Scholar
  26. 26.
    Zhang, E., Zhuo, Y.Q.: Online advertising channel choice - posted price vs. auction (2011)Google Scholar
  27. 27.
    Zhang, H., Jiang, H., Li, B., Liu, F., Vasilakos, A.V., Liu, J.: A framework for truthful online auctions in cloud computing with heterogeneous user demands. IEEE Trans. Comput. 65(3), 805–818 (2016)MathSciNetCrossRefGoogle Scholar
  28. 28.
    Zhang, L., Li, Z., Wu, C.: Dynamic resource provisioning in cloud computing: a randomized auction approach. In: Proceedings of IEEE INFOCOM (2014)Google Scholar
  29. 29.
    Zhang, X., Huang, Z., Wu, C., Li, Z., Lau, F.: Online auctions in IaaS clouds: welfare and profit maximization with server costs. In: Proceedings of ACM SIGMETRICS (2015)Google Scholar

Copyright information

© ICST Institute for Computer Sciences, Social Informatics and Telecommunications Engineering 2020

Authors and Affiliations

  1. 1.School of Computer ScienceWuhan UniversityWuhanChina
  2. 2.School of Cyber Science and EngineeringWuhan UniversityWuhanChina

Personalised recommendations