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Journal of Network and Systems Management

, Volume 26, Issue 3, pp 723–754 | Cite as

Green Approach for Joint Management of Geo-Distributed Data Centers and Interconnection Networks

  • Amine BarkatEmail author
  • Mohand-Tahar Kechadi
  • Giacomo Verticale
  • Ilario Filippini
  • Antonio Capone
Article
  • 492 Downloads

Abstract

Every time an Internet user downloads a video, shares a picture, or sends an email, his/her device addresses a data center and often several of them. These complex systems feed the web and all Internet applications with their computing power and information storage, but they are very energy hungry. The energy consumed by Information and Communication Technology (ICT) infrastructures is currently more than 4% of the worldwide consumption and it is expected to double in the next few years. Data centers and communication networks are responsible for a large portion of the ICT energy consumption and this has stimulated in the last years a research effort to reduce or mitigate their environmental impact. Most of the approaches proposed tackle the problem by separately optimizing the power consumption of the servers in data centers and of the network. However, the Cloud computing infrastructure of most providers, which includes traditional telcos that are extending their offer, is rapidly evolving toward geographically distributed data centers strongly integrated with the network interconnecting them. Distributed data centers do not only bring services closer to users with better quality, but also provide opportunities to improve energy efficiency exploiting the variation of prices in different time zones, the locally generated green energy, and the storage systems that are becoming popular in energy networks. In this paper, we propose an energy aware joint management framework for geo-distributed data centers and their interconnection network. The model is based on virtual machine migration and formulated using mixed integer linear programming. It can be solved using state-of-the art solvers such as CPLEX in reasonable time. The proposed approach covers various aspects of Cloud computing systems. Alongside, it jointly manages the use of green and brown energies using energy storage technologies. The obtained results show that significant energy cost savings can be achieved compared to a baseline strategy, in which data centers do not collaborate to reduce energy and do not use the power coming from renewable resources.

Keywords

Green cloud Energy consumption Green energy VM migration Energy efficiency Joint optimization 

Notes

Acknowledgements

This work is partially funded by the European Commission under the Erasmus Mundus Green IT project (Green IT for the benefit of civil society. 3772227-1-2012-ES-ERA MUNDUS-EMA21; Grant Agreement No. 2012-2625/001-001-EMA2).

References

  1. 1.
    Van Heddeghem, W., Lambert, S., Lannoo, B., Colle, D., Pickavet, M., Demeester, P.: Trends in worldwide ICT electricity consumption from 2007 to 2012. Comput. Commun. 50, 64–76 (2014)CrossRefGoogle Scholar
  2. 2.
    Lannoo, B., Lambert, S., Van Heddeghem, W., Pickavet, M., Kuipers, F., Koutitas, G., Niavis, H., Satsiou, A., Beck, M., Fischer, A.: Overview of ICT energy consumption. Netw. Excel. Internet Sci. Deliv. D8 1(02), 1–59 (2013)Google Scholar
  3. 3.
    Gelenbe, E., Caseau, Y.: The impact of information technology on energy consumption and carbon emissions. Ubiquity 2015(June), 1 (2015)CrossRefGoogle Scholar
  4. 4.
    Koomey, J.: Growth in Data Center Electricity Use 2005 to 2010. A report by Analytical Press, completed at the request of The New York Times, p. 9 (2011)Google Scholar
  5. 5.
    Delforge, P.: Americas data centers consuming and wasting growing amounts of energy. In: Natural Resource Defence Council (2014)Google Scholar
  6. 6.
    Power, E.N.: Energy Logic: Reducing Data Center Energy Consumption by Creating Savings that Cascade Across Systems. White paper, Emerson Electric Co, vol. 9 (2009)Google Scholar
  7. 7.
    Liu, J., Zhao, F., Liu, X., He, W.: Challenges towards elastic power management in internet data centers. In: 29th IEEE International Conference on Distributed Computing Systems Workshops, 2009. ICDCS Workshops’ 09, pp. 65–72. IEEE (2009)Google Scholar
  8. 8.
    Chang, R.S., Chang, H.P., Wang, Y.T.: A dynamic weighted data replication strategy in data grids. In: IEEE/ACS International Conference on Computer Systems and Applications, 2008. AICCSA 2008, pp. 414–421. IEEE (2008)Google Scholar
  9. 9.
    Strunk, A., Dargie, W.: Does live migration of virtual machines cost energy? In: 2013 IEEE 27th International Conference on Advanced Information Networking and Applications (AINA), pp. 514–521. IEEE (2013)Google Scholar
  10. 10.
    Huang, Q., Gao, F., Wang, R., Qi, Z.: Power consumption of virtual machine live migration in clouds. In: 2011 Third International Conference on Communications and Mobile Computing (CMC), pp. 122–125. IEEE (2011)Google Scholar
  11. 11.
    Baliga, J., Ayre, R.W., Hinton, K., Tucker, R.S.: Green cloud computing: balancing energy in processing, storage, and transport. Proc. IEEE 99(1), 149–167 (2011)CrossRefGoogle Scholar
  12. 12.
    Hinton, K., Baliga, J., Feng, M., Ayre, R., Tucker, R.S.: Power consumption and energy efficiency in the internet. IEEE Netw. 25(2), 6–12 (2011)CrossRefGoogle Scholar
  13. 13.
    Shang, L., Peh, L.S., Jha, N.K.: Dynamic voltage scaling with links for power optimization of interconnection networks. In: The Ninth International Symposium on High-Performance Computer Architecture, 2003. HPCA-9 2003. Proceedings, pp. 91–102. IEEE (2003)Google Scholar
  14. 14.
    Nedevschi, S., Popa, L., Iannaccone, G., Ratnasamy, S., Wetherall, D.: Reducing network energy consumption via sleeping and rate-adaptation. NSDI 8, 323–336 (2008)Google Scholar
  15. 15.
    Zheng, K., Wang, X., Li, L., Wang, X.: Joint power optimization of data center network and servers with correlation analysis. In: INFOCOM, 2014 Proceedings IEEE, pp. 2598–2606. IEEE (2014)Google Scholar
  16. 16.
    Jin, H., Cheocherngngarn, T., Levy, D., Smith, A., Pan, D., Liu, J., Pissinou, N.: Joint host-network optimization for energy-efficient data center networking. In: 2013 IEEE 27th International Symposium on Parallel and Distributed Processing (IPDPS), pp. 623–634. IEEE (2013)Google Scholar
  17. 17.
    Jiang, J.W., Lan, T., Ha, S., Chen, M., Chiang, M.: Joint VM placement and routing for data center traffic engineering. In: INFOCOM, 2012 Proceedings IEEE, pp. 2876–2880. IEEE (2012)Google Scholar
  18. 18.
    Barkat, A., Capone, A.: Effective management of green cloud data centers using energy storage technologies. In: 2015 23rd International Conference on Software, Telecommunications and Computer Networks (SoftCOM), pp. 27–31. IEEE (2015)Google Scholar
  19. 19.
    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, pp. 41–50. ACM (2009)Google Scholar
  20. 20.
    Verma, A., Ahuja, P., Neogi, A.: pMapper: power and migration cost aware application placement in virtualized systems. In: Middleware 2008, pp. 243–264. Springer, Berlin (2008)Google Scholar
  21. 21.
    Dupont, C., Hermenier, F., Schulze, T., Basmadjian, R., Somov, A., Giuliani, G.: Plug4green: a flexible energy-aware vm manager to fit data centre particularities. Ad Hoc Netw. 25, 505–519 (2015)CrossRefGoogle Scholar
  22. 22.
    Li, B., Li, J., Huai, J., Wo, T., Li, Q., Zhong, L.: Enacloud: an energy-saving application live placement approach for cloud computing environments. In: IEEE International Conference on Cloud Computing, 2009. CLOUD’09, pp. 17–24. IEEE (2009)Google Scholar
  23. 23.
    Ghribi, C., Hadji, M., Zeghlache, D.: Energy efficient VM scheduling for cloud data centers: exact allocation and migration algorithms. In: 2013 13th IEEE/ACM International Symposium on Cluster, Cloud and Grid Computing (CCGrid), pp. 671–678. IEEE (2013)Google Scholar
  24. 24.
    Guo, C., Lu, G., Wang, H.J., Yang, S., Kong, C., Sun, P., Wu, W., Zhang, Y.: Secondnet: a data center network virtualization architecture with bandwidth guarantees. In: Proceedings of the 6th International COnference, p. 15. ACM (2010)Google Scholar
  25. 25.
    Guo, C., Wu, H., Tan, K., Shi, L., Zhang, Y., Lu, S.: Dcell: a scalable and fault-tolerant network structure for data centers. ACM SIGCOMM Comput. Commun. Rev. 38(4), 75–86 (2008)CrossRefGoogle Scholar
  26. 26.
    Itani, W., Ghali, C., Kayssi, A., Chehab, A., Elhajj, I.: G-route: an energy-aware service routing protocol for green cloud computing. Cluster Comput. 18(2), 889–908 (2015)CrossRefGoogle Scholar
  27. 27.
    Baldi, M., Ofek, Y.: Time for a “greener” internet. In: IEEE International Conference on Communications Workshops, 2009. ICC Workshops 2009, pp. 1–6. IEEE (2009)Google Scholar
  28. 28.
    Restrepo, J.C.C., Gruber, C.G., Machuca, C.M.: Energy profile aware routing. In: IEEE International Conference on Communications Workshops, 2009. ICC Workshops 2009, pp. 1–5. IEEE (2009)Google Scholar
  29. 29.
    Bianzino, A.P., Chaudet, C., Larroca, F., Rossi, D., Rougier, J.L.: Energy-aware routing: a reality check. In: GLOBECOM Workshops (GC Wkshps), 2010 IEEE, pp. 1422–1427. IEEE (2010)Google Scholar
  30. 30.
    Bolla, R., Davoli, F., Bruschi, R., Christensen, K., Cucchietti, F., Singh, S.: The potential impact of green technologies in next-generation wireline networks: is there room for energy saving optimization? IEEE Commun. Mag. 49(8), 80–86 (2011)CrossRefGoogle Scholar
  31. 31.
    Chiaraviglio, L., Ciullo, D., Mellia, M., Meo, M.: Modeling sleep modes gains with random graphs. In: 2011 IEEE Conference on Computer Communications Workshops (INFOCOM WKSHPS), pp. 355–360. IEEE (2011)Google Scholar
  32. 32.
    Addis, B., Capone, A., Carello, G., Gianoli, L.G., Sanso, B.: Multi-period traffic engineering of resilient networks for energy efficiency. In: Online Conference on Green Communications (GreenCom), 2012 IEEE, pp. 14–19. IEEE (2012)Google Scholar
  33. 33.
    Amaldi, E., Capone, A., Gianoli, L.G., Mascetti, L.: Energy management in IP traffic engineering with shortest path routing. In: 2011 IEEE International Symposium on a World of Wireless, Mobile and Multimedia Networks (WoWMoM), pp. 1–6. IEEE (2011)Google Scholar
  34. 34.
    Nam, T.M., Thanh, N.H., Thu, N.Q., Hieu, H.T., Covaci, S.: Energy-aware routing based on power profile of devices in data center networks using SDN. In: 2015 12th International Conference on Electrical Engineering/Electronics, Computer, Telecommunications and Information Technology (ECTI-CON), pp. 1–6. IEEE (2015)Google Scholar
  35. 35.
    Chiaraviglio, L., Mellia, M., Neri, F.: Energy-aware networks: reducing power consumption by switching off network elements. In: FEDERICA-Phosphorus tutorial and workshop (TNC2008) (2008)Google Scholar
  36. 36.
    Shang, Y., Li, D., Xu, M.: A comparison study of energy proportionality of data center network architectures. In: 2012 32nd International Conference on Distributed Computing Systems Workshops (ICDCSW), pp. 1–7. IEEE (2012)Google Scholar
  37. 37.
    Wang, L., Zhang, F., Aroca, J.A., Vasilakos, A.V., Zheng, K., Hou, C., Li, D., Liu, Z.: A general framework for achieving energy efficiency in data center networks. arXiv preprint arXiv:1304.3519 (2013)
  38. 38.
    Liu, R., Gu, H., Yu, X., Nian, X.: Distributed flow scheduling in energy-aware data center networks. IEEE Commun. Lett. 17(4), 801–804 (2013)CrossRefGoogle Scholar
  39. 39.
    Buysse, J., Georgakilas, K., Tzanakaki, A., De Leenheer, M., Dhoedt, B., Develder, C., Demeester, P.: Calculating the minimum bounds of energy consumption for cloud networks. In: 2011 Proceedings of 20th International Conference on Computer Communications and Networks (ICCCN), pp. 1–7. IEEE (2011)Google Scholar
  40. 40.
    Shirayanagi, H., Yamada, H., Kenji, K.: Honeyguide: a VM migration-aware network topology for saving energy consumption in data center networks. IEICE Trans. Inf. Syst. 96(9), 2055–2064 (2013)CrossRefGoogle Scholar
  41. 41.
    Huu, T.N., Ngoc, N.P., Thu, H.T., Ngoc, T.T., Minh, D.N., Tai, H.N., Quynh, T.N., Hock, D., Schwartz, C.: Modeling and experimenting combined smart sleep and power scaling algorithms in energy-aware data center networks. Simul. Model. Pract. Theory 39, 20–40 (2013)CrossRefGoogle Scholar
  42. 42.
    Fang, W., Liang, X., Li, S., Chiaraviglio, L., Xiong, N.: Vmplanner: optimizing virtual machine placement and traffic flow routing to reduce network power costs in cloud data centers. Comput. Netw. 57(1), 179–196 (2013)CrossRefGoogle Scholar
  43. 43.
    Addis, B., Capone, A., Carello, G., Gianoli, L., Sansó, B.: Energy management through optimized routing and device powering for greener communication networks. IEEE/ACM Trans. Netw. 22(1), 313–325 (2014)CrossRefGoogle Scholar
  44. 44.
    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), pp. 65–72. IEEE (2011)Google Scholar
  45. 45.
    Guo, C., Lu, G., Li, D., Wu, H., Zhang, X., Shi, Y., Tian, C., Zhang, Y., Lu, S.: Bcube: a high performance, server-centric network architecture for modular data centers. ACM SIGCOMM Comput. Commun. Rev. 39(4), 63–74 (2009)CrossRefGoogle Scholar
  46. 46.
    Heller, B., Seetharaman, S., Mahadevan, P., Yiakoumis, Y., Sharma, P., Banerjee, S., McKeown, N.: Elastictree: saving energy in data center networks. NSDI 10, 249–264 (2010)Google Scholar
  47. 47.
    Dong, J., Jin, X., Wang, H., Li, Y., Zhang, P., Cheng, S.: Energy-saving virtual machine placement in cloud data centers. In: 2013 13th IEEE/ACM International Symposium on Cluster, Cloud and Grid Computing (CCGrid), pp. 618–624. IEEE (2013)Google Scholar
  48. 48.
    Gu, L., Zeng, D., Li, P., Guo, S.: Cost minimization for big data processing in geo-distributed data centers. IEEE Trans. Emerg. Top. Comput. 2(3), 314–323 (2014)CrossRefGoogle Scholar
  49. 49.
    Gu, L., Zeng, D., Guo, S., Ye, B.: Joint optimization of VM placement and request distribution for electricity cost cut in geo-distributed data centers. In: 2015 International Conference on Computing, Networking and Communications (ICNC), pp. 717–721. IEEE (2015)Google Scholar
  50. 50.
    Robertazzi, T.: Introduction to Computer Networking. Springer, Berlin (2017)CrossRefGoogle Scholar
  51. 51.
    Amazon Web Services: Infrastructure mondiale. https://aws.amazon.com/fr/about-aws/global-infrastructure/. Accessed 13 Nov 2017
  52. 52.
    Taheri, M., Ansari, N.: Power-aware admission control and virtual machine allocation for cloud applications. In: 2015 36th IEEE Sarnoff Symposium, pp. 134–139. IEEE (2015)Google Scholar
  53. 53.
    Wolke, A.: Energy efficient capacity management in virtualized data centers. Ph.D. thesis, Universität München (2015)Google Scholar
  54. 54.
    Barati, M., Sharifian, S.: A hybrid heuristic-based tuned support vector regression model for cloud load prediction. J. Supercomput. 71(11), 4235–4259 (2015)CrossRefGoogle Scholar
  55. 55.
    Hines, M.R., Gopalan, K.: Post-copy based live virtual machine migration using adaptive pre-paging and dynamic self-ballooning. In: Proceedings of the 2009 ACM SIGPLAN/SIGOPS International Conference on Virtual Execution Environments, pp. 51–60. ACM (2009)Google Scholar
  56. 56.
    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, vol. 2, pp. 273–286. USENIX Association (2005)Google Scholar
  57. 57.
    Miller, R.: Facebook installs solar panels at new data centers. Datacenter Knowl. (2011). http://www.datacenterknowledge.com/archives/2011/04/16/facebook-installs-solar-panels-at-new-data-center/. Accessed 13 Nov 2017
  58. 58.
    Miller, R.: Wind-powered data center in wyoming (2014). http://www.datacenterknowledge.com/archives/2007/11/29/wind-powered-data-center-in-wyoming/. Accessed 13 Nov 2017
  59. 59.
    International Renewable Energy Agency (IRENA), Summary for policy makers: renewable power generation costs (2012). http://www.irena.org/DocumentDownloads/Publications/Renewable_Power_Generation_Costs.pdf. Accessed 13 Nov 2017
  60. 60.
    Google.com: Data center locations (2016). https://www.google.com/about/datacenters/inside/locations/index.html. Accessed 13 Nov 2017
  61. 61.
    Google: Efficiency of data centers. http://www.google.ca/about/datacenters/efficiency/internal/. Accessed 13 Nov 2017
  62. 62.
    FERC: Electric power markets—new england (iso-ne). https://www.ferc.gov/market-oversight/mkt-electric/new-england.asp. Accessed 13 Nov 2017
  63. 63.
    California ISO. https://www.caiso.com/market/Pages/default.aspx. Accessed 13 Nov 2017
  64. 64.
    FERC: Electric Power Markets. https://www.ferc.gov/market-oversight/mkt-electric/pjm.asp. Accessed 13 Nov 2017
  65. 65.
    Independent Electricity System Operator (IESO). http://www.ieso.ca/. Accessed 13 Nov 2017
  66. 66.
    GME—Gestore dei Mercati Energetici SpA. http://www.mercatoelettrico.org/it/. Accessed 13 Nov 2017
  67. 67.
    PEGAS Spot. http://www.powernext.com/. Accessed 13 Nov 2017
  68. 68.
  69. 69.
    EEX Group. https://www.eex.com/en/. Accessed 13 Nov 2017
  70. 70.
    SEMO—Single Electricty Market Operator. http://www.sem-o.com/Pages/default.aspx. Accessed 13 Nov 2017
  71. 71.
    JEPX. http://www.jepx.org/english/. Accessed 13 Nov 2017
  72. 72.
    Trade System Administrator (ATS). https://www.interrao.ru/en/activity/traiding/. Accessed 13 Nov 2017
  73. 73.
    Juniper Networks, E320 broadband services router specifications (2011). https://www.juniper.net/documentation/hardware/erx/junose151/hw-e120-e320-hardware/index.html. Accessed 13 Nov 2017
  74. 74.
    Internetworldstats: World internet users statistics and 2015 world population stats (2016). http://www.internetworldstats.com/stats.htm. Accessed 13 Nov 2017
  75. 75.
    Amazon Web Services: Ec2 instance types amazon web services (aws) (2016). https://aws.amazon.com/ec2/instance-types/. Accessed 13 Nov 2017
  76. 76.
    Barroso, L.A., Clidaras, J., Hölzle, U.: The datacenter as a computer: an introduction to the design of warehouse-scale machines. Synth. Lect. Comput. Archit. 8(3), 1–154 (2013)CrossRefGoogle Scholar
  77. 77.
    Díaz-González, F., Sumper, A., Gomis-Bellmunt, O., Villafáfila-Robles, R.: A review of energy storage technologies for wind power applications. Renew. Sustain. Energy Rev. 16(4), 2154–2171 (2012)CrossRefGoogle Scholar
  78. 78.

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Authors and Affiliations

  1. 1.Dipartimento di Elettronica, Informazione e Bioingegneria (DEIB)Politecnico di MilanoMilanItaly
  2. 2.Department of Computer Science, Faculty of Exact SciencesUniversity of BejaiaBejaïaAlgeria
  3. 3.School of Computer Science and InformaticsUniversity College DublinDublinIreland

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