Skip to main content
SpringerLink
Log in

SOC: Satisfaction-Oriented Virtual Machine Consolidation in Enterprise Data Centers

  • Published:
International Journal of Parallel Programming Aims and scope Submit manuscript

Abstract

Server sprawl is a problem faced by data centers, which causes unnecessary waste of hardware resources, collateral costs of space, power and cooling systems, and administration. This is usually combated by virtualization based consolidation, and both industry and academia have put many efforts into solving the underlying virtual machine (VM) placement problem. However, IT managers’ preferences are seldom considered when making VM placement decisions. This paper proposes a satisfaction-oriented VM consolidation mechanism (SOC) to plan VM consolidation while taking IT managers’ preferences into consideration. In the mechanism, we propose: (1) an XML-based description language to express managers’ preferences and metrics to evaluate the satisfaction degree; (2) to apply matchmaking to locate entities [i.e., VMs and physical machines (PMs)] that best match each other’s preferences; (3) to employ the VM placement algorithm proposed in our previous work to minimize the number of hosts required and the resource wastage on allocated hosts. SOC is compared with two baselines: placement-only and matchmaking-only. The simulation results show that most of the VM-to-PM mappings output from placement-only violate given preferences, while SOC has a satisfaction degree close to matchmaking-only, without requiring too many PMs as matchmaking-only does, but only an amount close to placement-only. In brief, SOC is effective in minimizing the number of hosts required to support a certain set of VMs, while maximizing the satisfaction degree of both managers from the provider and requester side.

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. Alicherry, M., Lakshman, T.: Network aware resource allocation in distributed clouds. In: Proceedings of the 31st International Conference on Computer Communications, INFOCOM ’12, pp. 963–971. IEEE (2012)

  2. Beloglazov, A., Buyya, R.: Adaptive threshold-based approach for energy-efficient consolidation of virtual machines in cloud data centers. In: Proceedings of the International Workshop on Middleware for Grids, Clouds and e-Science, MGC ’10, pp. 4:1–4:6. ACM (2010)

  3. Beloglazov, A., Abawajy, J., Buyya, R.: Energy-aware resource allocation heuristics for efficient management of data centers for cloud computing. Future Gener. Comput. Syst. 28(5), 755–768 (2012)

    Article  Google Scholar 

  4. Best practices for identifying and resolving infrastructure problems. http://www-03.ibm.com/software/products/us/en/tivomoni/. Accessed 16 Mar 2014

  5. Biran, O., Corradi, A., Fanelli, M., Foschini, L., Nus, A., Raz, D., Silvera, E.: A stable network-aware vm placement for cloud systems. In: Proceedings of the International Symposium on Cluster, Cloud and Grid Computing, CCGRID ’12, pp. 498–506. IEEE (2012)

  6. Breitgand, D., Epstein, A.: Sla-aware placement of multi-virtual machine elastic services in compute clouds. In: Proceedings of the IFIP/IEEE International Symposium on Integrated Network Management, IM ’11, pp. 161–168. IEEE (2011)

  7. Cafaro, M., Mirto, M., Aloisio, G.: Preference-based matchmaking of grid resources with cp-nets. J. Grid Comput. 11(2), 211–237 (2013)

    Article  Google Scholar 

  8. Cardellini, V., Casalicchio, E., Lo Presti, F., Silvestri, L.: Sla-aware resource management for application service providers in the cloud. In: Proceedings of the International Symposium on Network Cloud Computing and Applications, NCCA ’11, pp. 20–27 (2011)

  9. Chen, M., Zhang, H., Su, Y.Y., Wang, X., Jiang, G., Yoshihira, K.: Effective vm sizing in virtualized data centers. In: Proceedings of the IFIP/IEEE International Symposium on Integrated Network Management, IM ’11, pp. 594–601. IEEE (2011)

  10. Feller, E., Rilling, L., Morin, C.: Energy-aware ant colony based workload placement in clouds. In: Proceedings of the IEEE/ACM 12th International Conference on Grid Computing, GRID ’11, pp. 26–33 (2011)

  11. Govindan, S., Liu, J., Kansal, A., Sivasubramaniam, A.: Cuanta: quantifying effects of shared on-chip resource interference for consolidated virtual machines. In: Proceedings of the 2nd ACM Symposium on Cloud Computing, SOCC ’11, pp. 22:1–22:14 (2011)

  12. Isci, C., Hanson, J., Whalley, I., Steinder, M., O.Kephart, J.: Runtime demand estimation for effective dynamic resource management. In: Proceeding of the IEEE Network Operations and Management Symposium, NOMS ’10, pp. 381–388

  13. Jin, H., Qin, H., Wu, S., Guo, X.: Ccap: a cache contention-aware virtual machine placement approach for hpc cloud. Int. J. Parallel Program. 1–18 (2013). doi:10.1007/s10766-013-0286-1

  14. Li, X., Ventresque, A., Murphy, J., Thorburn, J.: A fair comparison of vm placement heuristics and a more effective solution. In: Proceedings of the 13th International Symposium on Parallel and Distributed Computing, ISPDC ’14. IEEE (2014)

  15. Liu, C., Foster, I.: A constraint language approach to matchmaking. In: Proceedings of the 14th International Workshop on Research Issues on Data Engineering: Web Services for E-Commerce and E-Government Applications, RIDE ’04, pp. 7–14. IEEE (2004)

  16. Liu, C., Yang, L., Foster, I., Angulo, D.: Design and evaluation of a resource selection framework for grid applications. In: Proceedings of the 11th International Symposium on High Performance Distributed Computing, HPDC ’02, pp. 63–72. IEEE (2002)

  17. Meng, X., Pappas, V., Zhang, L.: Improving the scalability of data center networks with traffic-aware virtual machine placement. In: Proceedings of the 29th Conference on Information Communications, INFOCOM ’10, pp. 1154–1162 (2010)

  18. Moore, J., Chase, J., Ranganathan, P., Sharma, R.: Making scheduling ”cool”: temperature-aware workload placement in data centers. In: Proceedings of the Annual Conference on USENIX Annual Technical Conference, ATEC ’05, pp. 5–5 (2005)

  19. Raman, R., Livny, M., Solomon, M.: Matchmaking: Distributed resource management for high throughput computing. In: Proceedings of the 7th International Symposium on High Performance Distributed Computing, HPDC ’98, pp. 140–146. IEEE (1998)

  20. Raman, R., Livny, M., Solomon, M.: Policy driven heterogeneous resource co-allocation with gangmatching. In: Proceedings of the 12th International Symposium on High Performance Distributed Computing, HPDC ’03, pp. 80–89. IEEE (2003)

  21. Sycara, K., Widoff, S., Klusch, M., Lu, J.: Larks: dynamic matchmaking among heterogeneous software agents in cyberspace. Auton. Agents Multi Agent Syst. 5(2), 173–203 (2002)

    Article  Google Scholar 

  22. Van, H.N., Tran, F.D., Menaud, J.M.: Sla-aware virtual resource management for cloud infrastructures. In: Proceedings of the 9th International Conference on Computer and Information Technology, vol. 02, CIT ’09, pp. 357–362. IEEE (2009)

  23. Verma, A., Ahuja, P., Neogi, A.: pmapper: power and migration cost aware application placement in virtualized systems. In: Proceedings of the 9th ACM/IFIP/USENIX International Conference on Middleware, Middleware ’08, pp. 243–264 (2008)

  24. Verma, A., Ahuja, P., Neogi, A.: Power-aware dynamic placement of hpc applications. In: Proceedings of the 22nd Annual International Conference on Supercomputing, ICS ’08, pp. 175–184. ACM (2008)

  25. Vogels, W.: Beyond server consolidation. Queue 6(1), 20–26 (2008)

    Article  Google Scholar 

Download references

Acknowledgments

This work was supported, in part, by Science Foundation Ireland Grant 10/CE/I1855 to Lero—the Irish Software Engineering Research Centre (www.lero.ie) and by Enterprise Ireland Innovation Partnership in cooperation with IBM and University College Dublin under Grant IP/2010/0061. Anthony Ventresque was supported, in part, by Science Foundation Ireland Industry Fellowship Grant 12/IF/12789.

Author information

Authors and Affiliations

  1. Lero@UCD, School of Computer Science and Informatics, University College Dublin, Dublin, Ireland

    Xi Li, Anthony Ventresque & John Murphy

  2. IBM Research, Smarter Cities Technology Centre, Damastown Industrial Estate, Dublin, Ireland

    Anthony Ventresque

  3. IBM Software Group, Toronto, ON, Canada

    James Thorburn

Authors
  1. Xi Li
    View author publications

    You can also search for this author in PubMed Google Scholar

  2. Anthony Ventresque
    View author publications

    You can also search for this author in PubMed Google Scholar

  3. John Murphy
    View author publications

    You can also search for this author in PubMed Google Scholar

  4. James Thorburn
    View author publications

    You can also search for this author in PubMed Google Scholar

Corresponding author

Correspondence to Xi Li.

Rights and permissions

Reprints and permissions

About this article

Check for updates. Verify currency and authenticity via CrossMark

Cite this article

Li, X., Ventresque, A., Murphy, J. et al. SOC: Satisfaction-Oriented Virtual Machine Consolidation in Enterprise Data Centers. Int J Parallel Prog 44, 130–150 (2016). https://doi.org/10.1007/s10766-014-0333-6

Download citation

  • Received:

  • Accepted:

  • Published:

  • Issue Date:

  • DOI: https://doi.org/10.1007/s10766-014-0333-6

Keywords

Search

Navigation