Skip to main content

Advertisement

SpringerLink
Log in

Carbon-aware distributed cloud: multi-level grouping genetic algorithm

  • Published:
Cluster Computing Aims and scope Submit manuscript

Abstract

Global warming caused by greenhouse gas (GHG) emissions is one of the main concerns for both developed and developing countries. In a fast growing Information and Communication Technology industry, current energy efficiency methodologies are not sufficient for new raising problems such as optimization of complex distributed systems. Therefore, proper methodologies tailored for this type of systems could significantly reduce their GHG emissions. In this paper, a new genetic algorithm (GA) is introduced, namely multi-level grouping GA (MLGGA), which is designed for multi-level bin packing problems such as that of carbon footprint reduction in a distributed cloud over a network of data centers. The new MLGGA algorithm is tested on real data in a simulation platform, and its results are compared with other state-of-the-art methodologies. The results show a significant increase in the performance achieved by the proposed algorithm.

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
Fig. 10
Fig. 11
Fig. 12
Fig. 13
Fig. 14

Similar content being viewed by others

Notes

  1. http://www.greenservices.info/2011/10/simulation-environment.html

References

  1. Agrawal, S., Bose, S.K., Sundarrajan, S.: Grouping genetic algorithm for solving the serverconsolidation problem with conflicts. In: Proceedings of the First ACM/SIGEVO Summit on Genetic and Evolutionary Computation, pp. 1–8. ACM, Shanghai, (2009).

  2. Ajiro, Y., Tanaka, A.: Improving packing algorithms for server consolidation. In: Proceedings of the International Conference for the Computer Measurement Group (CMG) (2007).

  3. Beloglazov, A., Buyya, R., Lee, Y.C., Zomaya, A.: A taxonomy and survey of energy-efficient data centers and cloud computing systems. Technical Report CLOUDS-TR-2010-3 Cloud Computing and Distributed Systems Laboratory. University of Melbourne, Melbourne (2010).

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

    Article  Google Scholar 

  5. Clark, C., Fraser, K., Hand, S., Hansen, J.G., Jul, E., Limpach, C., Pratt, I., Warfield, A.: Live migration of virtual machines. In: Proceedings of the 2nd Conference on Symposium on Networked Systems Design and Implementation (NSDI05), Vol. 2. USENIX Association, Berkeley (2005).

  6. Falkenauer, E., Delchambre, A.: A genetic algorithm for bin packing and line balancing. IEEE International Conference on Robotics and Automation 2, 1186–1192 (1992)

    Google Scholar 

  7. Garey, M.R., Johnson, D.S.: A Guide to The Theory of NP-Completeness. Technical report. W.H.Freeman Co., San Francisco (1979)

    MATH  Google Scholar 

  8. GeSI: Smart 2020: Enabling the low carbon economy in the information age (2008). www.smart2020.org/_assets/files/02_Smart2020Report.pdf. Accessed 4 March 2014

  9. Gmach, D., Rolia, J., Cherkasova, L., Kemper, A.: Resource pool management: reactive versus proactive or let’s be friends. Comput. Netw. 53(17), 2905–2922 (2009)

    Article  Google Scholar 

  10. GreenStar Network Project. www.greenstarnetwork.com. Accessed 1 Sept 2013

  11. Gupta, R., Bose, S., Sundarrajan, S., Chebiyam, M., Chakrabarti, A.: A two stage heuristic algorithm for solving the server consolidation problem with item-item and bin-item incompatibility constraints. In: IEEE International Conference on Services Computing SCC ’08, pp. 39–46 (2008).

  12. Lenzen, M.: Current state of development of electricity-generating technologies: a literature review. Energies 3, 462–591 (2010)

    Article  Google Scholar 

  13. 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, pp. 29–38. ACM, Barcelona (2009).

  14. Marzolla, M., Babaoglu, O., Panzieri, F.: Server consolidation in clouds through gossiping. In: IEEE International Symposium on the World of Wireless, Mobile and Multimedia Networks (WoWMoM), pp. 1–6 (2011).

  15. McKinsey: The impact of ict on global emissions. Technical report on behalf of the Global eSustainability Initiative (GeSI) (2007).

  16. Farrahi Moghaddam, F., Cheriet, M.: Decreasing live virtual machine migration down-time using a memory page selection based on memory Change PDF. In: Proceedings of the International Conference on IEEE Networking, Sensing and Control (ICNSC), pp. 355–359 (2010).

  17. Farrahi Moghaddam, F., Cheriet, M., Nguyen, K.K.: Low carbon virtual private clouds. In: Proceedings of the IEEE International Conference on Cloud Computing (CLOUD’ 11), pp. 259–266. Washington (2011).

  18. Farrahi Moghaddam, F., Farrahi Moghaddam, R., Cheriet, M.: Carbon metering and effective tax cost modeling for virtual machines. In: IEEE 5th International Conference on Cloud Computing (CLOUD), pp. 758–763. IEEE (2012).

  19. Farrahi Moghaddam, F., Farrahi Moghaddam, R., Cheriet, M.: A modified GhG intensity indicator: toward a sustainable global economy based on a carbon border tax and emissions trading. Energy Policy 57, 363–380 (2013)

  20. Petrucci, V., Loques, O., Moss, D.: A dynamic configuration model for power-efficient virtualized server clusters. In: Proceedings of the 11th Brazilian Workshop on Real-Time and Embedded Systems (2009).

  21. Pop, C.B., Anghel, I., Cioara, T., Salomie, I., Vartic, I.: A swarm-inspired data center consolidation methodology. In: Proceedings of the 2nd International Conference on Web Intelligence, Mining and Semantics, pp. 41:1–41:7. New York (2012).

  22. Speitkamp, B., Bichler, M.: A mathematical programming approach for server consolidation problems in virtualized data centers. Serv. Comput. 3, 266–278 (2010)

    Google Scholar 

  23. Srikantaiah, S., Kansal, A., Zhao, F.: Energy aware consolidation for cloud computing. In: Conference on Power Aware Computing and Systems, pp. 10–10. USENIX Association, San Diego (2008).

  24. Van der Merwe, J., Ramakrishnan, K.K., Fairchild, M., Flavel, A., Houle, J., Lagar-Cavilla, H.A., Mulligan, J.: Towards a ubiquitous cloud computing infrastructure. In: Proceedings of the 17th IEEE Workshop on Local and Metropolitan Area Networks (LANMAN), pp. 1–6 (2010).

  25. Wilcox, D., McNabb, A., Seppi, K.: Solving virtual machine packing with a reordering grouping genetic algorithm. In: Proceedings of the IEEE Congress on Evolutionary Computation (CEC), pp. 362–369 (2011).

  26. Wood, T., Gerber, A., Ramakrishnan, K.K., Shenoy, P., der Merwe, J.V.: The case for enterprise-ready virtual private clouds. In: Conference on Hot Topics in Cloud Computing (HotCloudG09). USENIX Association, Berkeley (2009).

  27. Wood, T., Ramakrishnan, K., van der Merwe, J., Shenoy, P.: CloudNet: A platform for optimized wan migration of virtual machines. University of Massachusetts Technical, Report TR-2010-002 (2010).

  28. Xu, J., Fortes, J.: Multi-objective virtual machine placement in virtualized data center environments. In: Proceedings of the IEEE/ACM International Conference on Green Computing and Communications and International Conference on Cyber, Physical and Social Computing. Hangshou (2010).

  29. Zhang, Q., Cheng, L., Boutaba, R.: Cloud computing: state-of-the-art and research challenges. J. Internet Serv. Appl. 1(1), 7–18 (2008)

    Article  Google Scholar 

Download references

Acknowledgments

The authors thank the Natural Sciences and Engineering Research Council of Canada (NSERC) for their financial support under Grant CRDPJ 424371-11.

Author information

Authors and Affiliations

  1. Synchromedia Laboratory, École de Technologie Supérieure, Montreal, QC, Canada

    Fereydoun Farrahi Moghaddam & Reza Farrahi Moghaddam

  2. Automatic Production Engineering Department, École de Technologie Supérieure, Montreal, QC, Canada

    Mohamed Cheriet

Authors
  1. Fereydoun Farrahi Moghaddam
    View author publications

    You can also search for this author in PubMed Google Scholar

  2. Reza Farrahi Moghaddam
    View author publications

    You can also search for this author in PubMed Google Scholar

  3. Mohamed Cheriet
    View author publications

    You can also search for this author in PubMed Google Scholar

Corresponding author

Correspondence to Fereydoun Farrahi Moghaddam.

Rights and permissions

Reprints and permissions

About this article

Cite this article

Moghaddam, F.F., Moghaddam, R.F. & Cheriet, M. Carbon-aware distributed cloud: multi-level grouping genetic algorithm. Cluster Comput 18, 477–491 (2015). https://doi.org/10.1007/s10586-014-0359-y

Download citation

  • Received:

  • Revised:

  • Accepted:

  • Published:

  • Issue Date:

  • DOI: https://doi.org/10.1007/s10586-014-0359-y

Keywords

Search

Navigation