Skip to main content
SpringerLink
Log in

Multi-Layer Resource Management in Cloud Computing

  • Published:
Journal of Network and Systems Management Aims and scope Submit manuscript

Abstract

The paper studies multi-layer optimization in service oriented cloud computing to optimize the utility function of cloud computing, subject to resource constraints of an IaaS provider at the resource layer, service provisioning constraints of a SaaS provider at the service layer, and user QoS (quality of service) constraints of cloud users at application layer, respectively. The multi-layer optimization problem can be decomposed into three subproblems: cloud computing resource allocation problem, SaaS service provisioning problem, and user QoS maximization problem. The proposed algorithm decomposes the global optimization problem of cloud computing into three sub-problems via an iterative algorithm. The experiments are conducted to test the efficiency of the proposed algorithm with varying environmental parameters. The experiments also compare the performance of the proposed approach with other related work.

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

Similar content being viewed by others

References

  1. Armbrust, M., Fox, A., Griffith, R., Joseph, A., Katz, R., Konwinski, A., Lee, G., Patterson, D., Rabkin, A., Stoica, I., Zaharia, M.: A view of cloud computing. Commun. ACM 53(4), 50–58 (2010)

    Article  Google Scholar 

  2. Vaquero, L.M., Rodero-Merino, L., Caceres, J., Lindner, M.: A break in the clouds: towards a cloud definition. SIGCOMM Comput. Commun. Rev. 39(1), 50–55 (2009)

    Article  Google Scholar 

  3. Armbrust, M., Fox, A., Griffith, R., Joseph, A.D., Katz, R., Konwinski, A., Lee, G., Patterson, D., Rabkin, A., Stoica, I., Zaharia, M.: Above the Clouds: A Berkeley View of Cloud Computing. Technical Report No. UCB EECS-2009-28, University of California at Berkley, USA, Feb 10, 2009

  4. Kaur P.D., Chana I.: Enhancing Grid Resource Scheduling Algorithms for Cloud Environments. HPAGC 2011, pp. 140–144, (2011)

  5. Vouk, M.A.: Cloud computing: Issues, research and implementations. In: Information Technology Interfaces. ITI 2008. 30th International Conference on, 2008, pp. 31–40, (2008)

  6. Srikantaiah, S., Kansal, A., Zhao, F.: Energy aware consolidation for cloud computing. Cluster Comput. 12, 1–15 (2009)

    Article  Google Scholar 

  7. Berl, A., Gelenbe, E., di Girolamo, M., Giuliani, G., de Meer, H., Pentikousis, K., Dang, M.Q.: Energy-efficient cloud computing. Comput. J. 53(7), 1045–1051 (2010)

    Article  Google Scholar 

  8. Garg, S.K., Yeo, C.S., Anandasivam, A., Buyya, R.: Environment-conscious scheduling of HPC applications on distributed cloud-oriented data centers. J Parallel Distrib Comput. Elsevier Press, Amsterdam, (2011)

  9. Warneke, D., Kao, O.: Exploiting dynamic resource allocation for efficient parallel data processing in the cloud. IEEE Trans. Parallel Distrib. Syst. 22(6), 985–997 (2011)

    Google Scholar 

  10. Wu, L., Garg, S.K., Buyya, R.: SLA-based Resource Allocation for a Software as a Service Provider in Cloud Computing Environments. In: Proceedings of the 11th IEEE/ACM International Symposium on Cluster Computing and the Grid (CCGrid 2011), Los Angeles, USA, May 23–26, 2011

  11. Addis, B., Ardagna, D., Panicucci, B.: Autonomic Management of Cloud Service Centers with Availability Guarantees. 2010 IEEE 3rd International Conference on Cloud Computing, pp 220–207, (2010)

  12. Saure, D., Sheopuri, A., Huiming, Q., Jamjoom, H., Zeevi, A.: Time-of-use pricing policies for offering cloud computing as service. IEEE SOLI 2010, 300–305 (2010)

    Google Scholar 

  13. Zhu, Q., Agrawal, G.: Resource provisioning with budget constraints for adaptive applications in cloud environments. HPDC 10 Proceedings of the 19th ACM International Symposium on High Performance Distributed Computing, pp. 304–307, (2010)

  14. Rodero, I., Jaramillo, J., Quiroz, A., Parashar, M., Guim, F.: Energy-efficient application-aware online provisioning for virtualized clouds and data centers. International Conference on Green Computing (GREENCOMP 10), (2010)

  15. Abdelsalam, H.S., Maly, K., Kaminsky, D.: Analysis of Energy Efficiency in Clouds. 2009 Computation World: Future Computing, Service Computation, Cognitive, Adaptive, Content, Patterns, pp. 416–422, (2009)

  16. Younge, A.J., von Laszewski, G., Wang, L.: Efficient resource management for Cloud computing environments. IEEE Int. Green Comput. Conf. (IGCC), pp 357–364, (2010)

  17. Chang, F., Ren, J., Viswanathan, R.: Optimal Resource Allocation in Clouds. 2010 IEEE 3rd International Conference on Cloud Computing, pp. 418–425, (2010)

  18. Yoon, H., Lee, H.: An Intelligence Virtualization Rule Based on Multi-layer to Support Social-Media Cloud Service. 2011 First ACIS/JNU International Conference on Computers, Networks, Systems and Industrial Engineering (CNSI), vol., no., pp. 210–215, 23–25 May 2011

  19. Lacoste W.M., Debar, H.: Towards Multi-Layer Autonomic Isolation of Cloud Computing and Networking Resources. 2011 Conference on Network and Information Systems Security (SAR-SSI), vol., no., pp. 1–9, 18–21 May 2011

  20. Teng, F., Magouĺes, F.: Resource Pricing and Equilibrium Allocation Policy in Cloud Computing. 2010 10th IEEE International Conference on Computer and Information Technology (CIT 2010), pp 195–202, (2010)

  21. Yazir, Y.O., Matthews, C., Farahbod, R.: Dynamic Resource Allocation in Computing Clouds using Distributed Multiple Criteria Decision Analysis. IEEE 3rd International Conference on Cloud Computing, pp. 91–98, (2010)

  22. Mihailescu, M., Teo, Y.M.: Dynamic Resource Pricing on Federated Clouds. 2010 10th IEEE/ACM International Conference on Cluster, Cloud and Grid Computing, pp. 513–517, (2010)

  23. Chunlin, L., Layuan, L.: Joint QoS optimization for layered computational grid. Inf. Sci. vol 177/15, pp. 3038–3059 (2007)

  24. Chunlin, L., Layuan, L.: Energy constrained resources allocation optimization for mobile grid. J Parallel Distrib. Comput. Elsevier, vol 70/2, 245–258, (2010)

    Google Scholar 

  25. Chunlin, L., Layuan, L.: Hierarchical control policy for dynamic resource management in grid virtual organization. J. Supercomput. vol 49/2, pp. 190–218, (2009)

  26. Kelly, F., Maulloo, A., Tan, D.: Rate control for communication networks: shadow prices, proportional fairness and stability. J. Operational Res. Soc. 49(3), 237–252 (1998)

    MATH  Google Scholar 

  27. Spotcloud: Cloud capacity clearing house/spot market: Home, http://www.spotcloud.com

Download references

Acknowledgments

The work was partly supported by the National Natural Science Foundation of China (NSF) under grant (No. 61272116, No. 61171075), Specialized Research Fund for the Doctoral Program of Higher Education under Grant No. 20120143110014, the National Key Basic Research Program of China (973 Program) under Grant No. 2011CB302601, and the Open Fund of the State Key Laboratory of Software Development Environment. Any opinions, findings, and conclusions are those of the authors and do not necessarily reflect the views of the above agencies.

Author information

Authors and Affiliations

  1. Department of Computer Science, Wuhan University of Technology, Wuhan, 430063, People’s Republic of China

    Li Chunlin & Li Layuan

Authors
  1. Li Chunlin
    View author publications

    You can also search for this author in PubMed Google Scholar

  2. Li Layuan
    View author publications

    You can also search for this author in PubMed Google Scholar

Corresponding author

Correspondence to Li Chunlin.

Rights and permissions

Reprints and permissions

About this article

Cite this article

Chunlin, L., Layuan, L. Multi-Layer Resource Management in Cloud Computing. J Netw Syst Manage 22, 100–120 (2014). https://doi.org/10.1007/s10922-012-9261-1

Download citation

  • Received:

  • Revised:

  • Accepted:

  • Published:

  • Issue Date:

  • DOI: https://doi.org/10.1007/s10922-012-9261-1

Keywords

Search

Navigation