Skip to main content
Log in

Network-aware energy saving multi-objective optimization in virtualized data centers

  • Published:
Cluster Computing Aims and scope Submit manuscript

    We’re sorry, something doesn't seem to be working properly.

    Please try refreshing the page. If that doesn't work, please contact support so we can address the problem.

Abstract

With the current growth of data centers, improving energy saving is becoming more important to cloud service providers. The data centers architectural design and the advancement of virtualization technologies can be exploited for energy saving. In this paper, we studied the energy saving problem in data centers using virtual machines placement and live migration taking to account the status of the network links load. The problem was formulated as multi-objective integer linear program, which solvable by CPLEX, to minimize the energy consumed by the servers and minimize the time to migrate virtual machines. To overcome CPLEX high computation, a heuristic algorithm is introduced to provide practical and efficient virtual machines placement while minimizing their migration overhead to the network. The heuristic is evaluated in terms of energy consumed and performance using a real data center testbed that is stressed by running Hadoop Hibench benchmarks. The results where compared to the ones obtained by distributed resource scheduler (DRS) and the base case. The results show that the heuristic algorithm can save up to 30% of the server’s energy. For scalability and validity of optimality, the results of the heuristic were compared to the ones provided by CPLEX where the gap difference was less than 7%.

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

Access this article

Subscribe and save

Springer+ Basic
€32.70 /Month
  • Get 10 units per month
  • Download Article/Chapter or eBook
  • 1 Unit = 1 Article or 1 Chapter
  • Cancel anytime
Subscribe now

Buy Now

Price includes VAT (France)

Instant access to the full article PDF.

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

Similar content being viewed by others

References

  1. Hammadi, A., Mhamdi, L.: A survey on architectures and energy efficiency in data center networks. Comput. Commun. 40, 1 (2014)

    Article  Google Scholar 

  2. Koomey, J., Oakland, C.A.: A Scalable, Commodity Data Center Network Architecture. Analytics Press, Berkeley (2011)

    Google Scholar 

  3. Gao, P.X., Curtis, A.R., Wong, B., Keshav, S.: It’s not easy being green. ACM SIGCOMM Comput. Commun. Rev. 42(4), 211 (2012)

    Article  Google Scholar 

  4. Zhang, Q., Cheng, L., Boutaba, R.: Cloud computing: state-of-the-art and research challenges. J. Internet Serv. Appl. 1(1), 7 (2010)

    Article  Google Scholar 

  5. Tso, F.P., Hamilton, G., Oikonomou, K., Pezaros, D.P.: Implementing scalable, network-aware virtual machine migration for cloud data centers. In: 2013 IEEE Sixth International Conference on Cloud Computing (CLOUD), IEEE, pp. 557–564 (2013)

  6. Shanmuganathan, G., Gulati, A., Holler, A., Kalyanaraman, S., Padala, P., Zhu, X., Griffith, R., et al.: Towards proactive resource management in virtualized datacenters. VMware Labs (2013)

  7. VMware Infrastructure: Resource management with VMware DRS. VMware Whitepaper 13 (2006)

  8. Kansal, N.J., Chana, I.: An empirical evaluation of energy-aware load balancing technique for cloud data center. Clust. Comput. 1–19 (2017)

  9. Duggan, M., Duggan, J., Howley, E., Barrett, E.: A network aware approach for the scheduling of virtual machine migration during peak loads. Clust. Comput. 20(3), 2083 (2017)

    Article  Google Scholar 

  10. Bobroff, N., Kochut, A., Beaty, K.: Dynamic placement of virtual machines for managing sla violations. In: 10th IFIP/IEEE International Symposium on Integrated Network Management, IM’07, IEEE, pp. 119–128 (2007)

  11. Hermenier, F., Lorca, X., Menaud, J.M., Muller, G., Lawall, J.: Entropy: a consolidation manager for clusters. In: Proceedings of the 2009 ACM SIGPLAN/SIGOPS International Conference on Virtual Execution Environments (ACM), pp. 41–50 (2009)

  12. Nguyen Van, H., Dang Tran, F., Menaud, J.M.: Autonomic virtual resource management for service hosting platforms, In: Proceedings of the 2009 ICSE Workshop on Software Engineering Challenges of Cloud Computing (IEEE Computer Society), pp. 1–8 (2009)

  13. Cardosa, M., Korupolu, M.R., Singh, A.: Shares and utilities based power consolidation in virtualized server environments. In: IFIP/IEEE International Symposium on Integrated Network Management, IM’09, IEEE, pp. 327–334 (2009)

  14. Li, X., Qian, Z., Lu, S., Wu, J.: Energy efficient virtual machine placement algorithm with balanced and improved resource utilization in a data center. Math. Comput. Modell. 58(5), 1222 (2013)

    Article  MathSciNet  Google Scholar 

  15. Mills, K., Filliben, J., Dabrowski, C.: Comparing vm-placement algorithms for on-demand clouds. In: IEEE Third International Conference on Cloud Computing Technology and Science (CloudCom), IEEE, pp. 91–98 (2011)

  16. Srikantaiah, S., Kansal, A., Zhao, F.: Energy aware consolidation for cloud computing. In: Proceedings of the 2008 Conference on Power Aware Computing and Systems, vol. 10, pp. 1–5. San Diego (2008)

  17. Xu, J., Fortes, J.A.: Multi-objective virtual machine placement in virtualized data center environments. In: Proceedings of the 2010 IEEE/ACM Int’l Conference on Green Computing and Communications & Int’l Conference on Cyber, Physical and Social Computing (IEEE Computer Society), pp. 179–188 (2010)

  18. Yang, T., Lee, Y.C., Zomaya, A.Y.: Energy-efficient data center networks planning with virtual machine placement and traffic configuration. In: 2014 IEEE 6th International Conference on Cloud Computing Technology and Science (CloudCom), IEEE, pp. 284–291 (2014)

  19. Zhang, Z., Hsu, C.C., Chang, M.: Cool cloud: a practical dynamic virtual machine placement framework for energy aware data centers. In: 2015 IEEE 8th International Conference on Cloud Computing (CLOUD), IEEE, pp. 758–765 (2015)

  20. Wood, T., Shenoy, P.J., Venkataramani, A., Yousif, M.S.: Black-box and Gray-box strategies for virtual machine migration. NSDI 7, 17–17 (2007)

    Google Scholar 

  21. Abts, D., Marty, M.R., Wells, P.M., Klausler, P., Liu, H.: Multi-objective virtual machine placement in virtualized data center environments. In: ACM SIGARCH Computer Architecture News (ACM), vol. 38, pp. 338–347

  22. Huang, L., Jia, Q., Wang, X., Yang, S., Li, B.: Pcube: Improving power efficiency in data center networks. In: 2011 IEEE International Conference on Cloud Computing (CLOUD), IEEE, pp. 65–72

  23. Shin, J.Y., Wong, B., Sirer, E.G.: Small-world datacenters, In: Proceedings of the 2nd ACM Symposium on Cloud Computing (ACM), p. 2 (2011)

  24. Wang, T., Su, Z., Xia, Y., Qin, B., Hamdi, M.: NovaCube: A low latency Torus-based network architecture for data centers. In: 2014 IEEE Global Communications Conference IEEE, pp. 2252–2257 (2014)

  25. Abu-Libdeh, H., Costa, P., Rowstron, A., O’Shea, G., Donnelly, A.: Symbiotic routing in future data centers. ACM SIGCOMM Comput. Commun. Rev. 40(4), 51 (2010)

    Article  Google Scholar 

  26. Valancius, V., Laoutaris, N., Massoulié, L., Diot, C., Rodriguez, P.: Greening the internet with nano data centers. In: Proceedings of the 5th International Conference on Emerging Networking Experiments and Technologies (ACM), pp. 37–48 (2009)

  27. Singla, A., Singh, A., Ramachandran, K., Xu, L., Zhang, Y.: Proteus: a topology malleable data center network. In: Proceedings of the 9th ACM SIGCOMM Workshop on Hot Topics in Networks (ACM), p. 8 (2010)

  28. Heller, B., Seetharaman, S., Mahadevan, P., Yiakoumis, Y., Sharma, P., Banerjee, S., McKeown, N.: ElasticTree: Saving energy in data center networks. In: NSDI, vol. 10, pp. 249–264

  29. Wang, X., Yao, Y., Wang, X., Lu, K., Cao, Q.: Carpo: Correlation-aware power optimization in data center networks. In: 2012 Proceedings IEEE on INFOCOM (IEEE), pp. 1125–1133

  30. Vasi, N., Bhurat, P., Novakovi, D., Canini, M., Shekhar, S., Kosti, D.: Identifying and using energy-critical paths. In: Proceedings of the Seventh Conference on emerging Networking Experiments and Technologies (ACM), p. 18

  31. Zhang, M., Yi, C., Liu, B., Zhang, B.: GreenTE: Power-aware traffic engineering. In: 18th IEEE International Conference on Network Protocols (ICNP), IEEE, pp. 21–30 (2010)

  32. Carrega, A., Singh, S., Bolla, R., Bruschi, R.: Applying traffic merging to datacenter networks. In: Proceedings of the 3rd International Conference on Future Energy Systems: Where Energy, Computing and Communication Meet, p. 3 (2012)

  33. Wang, L., Zhang, F., Hou, C., Aroca, J.A., Liu, Z.: Incorporating rate adaptation into green networking for future data centers. In: 2013 12th IEEE International Symposium on Network Computing and Applications (NCA), IEEE, pp. 106–109 (2013)

  34. Shang, Y., Li, D., Xu, M.: Greening data center networks with flow preemption and energy-aware routing. In: 19th IEEE Workshop on Local and Metropolitan Area Networks (LANMAN), IEEE, pp. 1–6 (2013)

  35. Shang, Y., Li, D., Xu, M.: Energy-aware routing in data center network. In: Proceedings of the First ACM SIGCOMM Workshop on Green networking (ACM), pp. 1–8

  36. Wang, T., Xia, Y., Muppala, J., Hamdi, M.: Achieving energy efficiency in data centers using an artificial intelligence abstraction model. In: IEEE Transactions on Cloud Computing, vol. 1, p. 99 (2015). https://doi.org/10.1109/TCC.2015.2511720

  37. Liu, L., Wang, H., Liu, X., Jin, X., He, W.B., Wang, Q.B., Chen, Y.: GreenCloud: a new architecture for green data center, In: Proceedings of the 6th International Conference Industry Session on Autonomic Computing and Communications Industry Session (ACM), pp. 29–38 (2009)

  38. Teng, F., Deng, D., Yu, L., Magoulès, F.: An energy-efficient vm placement in cloud datacenter. In: 2014 IEEE Intl Conf on High Performance Computing and Communications, 2014 IEEE 6th Intl Symp on Cyberspace Safety and Security, 2014 IEEE 11th Intl Conf on Embedded Software and Syst (HPCC, CSS, ICESS), IEEE, pp. 173–180 (2014)

  39. Meisner, D., Wenisch, T.F.: Peak power modeling for data center servers with switched-mode power supplies. In: Proceedings of the 16th ACM/IEEE International Symposium on Low Power Electronics and Design (ACM), pp. 319–324 (2010)

  40. Chou, Y., Fahs, B., Abraham, S.: Microarchitecture optimizations for exploiting memory-level parallelism. In: ACM SIGARCH Computer Architecture News, vol. 32, IEEE Computer Society, p. 76 (2004)

  41. Dai, X., Wang, J.M., Bensaou, B.: Energy-efficient virtual machines scheduling in multi-tenant data centers. IEEE Trans. Cloud Comput. 4(2), 210 (2016)

    Article  Google Scholar 

  42. Gulati, A., Holler, A., Ji, M., Shanmuganathan, G., Waldspurger, C., Zhu, X.: Vmware distributed resource management: design, implementation, and lessons learned. VMware Tech. J. 1(1), 45 (2012)

    Google Scholar 

  43. kill a watt meter—electricity usage monitor. http://www.p3international.com/products/p4400.html. Accessed 29 Aug 2018

  44. IBM ILOG CPLEX. Users manual for cplex 12.7 (2016)

Download references

Author information

Authors and Affiliations

Authors

Corresponding author

Correspondence to Motassem Al-Tarazi.

Rights and permissions

Reprints and permissions

About this article

Check for updates. Verify currency and authenticity via CrossMark

Cite this article

Al-Tarazi, M., Chang, J.M. Network-aware energy saving multi-objective optimization in virtualized data centers. Cluster Comput 22, 635–647 (2019). https://doi.org/10.1007/s10586-018-2869-5

Download citation

  • Received:

  • Revised:

  • Accepted:

  • Published:

  • Issue Date:

  • DOI: https://doi.org/10.1007/s10586-018-2869-5

Keywords

Navigation