187
Views
8
CrossRef citations to date
0
Altmetric
Original Articles

Data analytics for energy-efficient clouds: design, implementation and evaluation

, &
Pages 690-705 | Received 15 Dec 2017, Accepted 02 Mar 2018, Published online: 21 Mar 2018

References

  • Dong J , Jin X , Wang H , et al. Energy-saving virtual machine placement in cloud data centers. In: Proceedings of the 2013 13th IEEE/ACM International Conference on Cluster, Cloud and Grid Computing, CCGRID ’13. Delft, Netherlands: IEEE Computer Society; 2013. p. 618–624.
  • Cesario E , Talia D . Distributed data mining patterns and services: an architecture and experiments. Concurr Comput Pract Exp. 2012;24:1751–1774.
  • Tseng HW , Yang TT , Yang KC , et al. An energy efficient vm management scheme with power-law characteristic in video streaming data centers. IEEE Trans Parallel Distrib Syst. 2017;PP:1–1.
  • Cicirelli F , Guerrieri A , Spezzano G , et al . An edge-based platform for dynamic smart city applications. Future Gener Comput Syst. 2017;76:106–118.
  • Mastroianni C , Meo M , Papuzzo G . Self-economy in cloud data centers: statistical assignment and migration of virtual machines. In: Proceedings of the 17th International Conference on Parallel Processing - Volume Part I, Euro-Par’11. Berlin, Heidelberg: Springer-Verlag; 2011. p. 407–418.
  • Barroso LA , Hölzle U . The case for energy-proportional computing. Computer. 2007;40:33–37.
  • Dong D , Herbert J . Energy efficient vm placement supported by data analytic service. In: Proceedings of the 2013 13th IEEE/ACM International Conference on Cluster, Cloud and Grid Computing, CCGRID ’13; IEEE Computer Society; 2013. p. 648–655.
  • Greenberg A , Hamilton J , Maltz DA , et al . The cost of a cloud: research problems in data center networks. SIGCOMM Comput Commun Rev. 2008;39:68–73.
  • Altomare A , Cesario E , Talia D . Energy-aware migration of virtual machines driven by predictive data mining models. In: Proceedings of the 23rd Euromicro International Conference on Parallel, Distributed, and Network-Based Processing, CCGRID ’10. Turku, Finlan: IEEE Computer Society; 2015. p. 549–553.
  • Altomare A , Cesario E . A data-driven approach based on auto-regressive models for energy-efficient clouds. In: Proceedings of the 17th IEEE/ACM International Symposium on Cluster, Cloud and Grid Computing, CCGRID 2017. Madrid, Spain: IEEE; 2017. p. 1062–1069.
  • Srikantaiah S , Kansal A , Zhao F . Energy aware consolidation for cloud computing. In: Proceedings of the 2008 Conference on Power Aware Computing and Systems, HotPower’08. San Diego (CA): USENIX Association; 2008. p. 10–10.
  • Piraghaj SF , Calheiros RN , Chan J , et al . Virtual machine customization and task mapping architecture for efficient allocation of cloud data center resources. Comput J. 2016;59:208–224.
  • Subirats J , Guitart J . Assessing and forecasting energy efficiency on cloud computing platforms. Future Gener Comput Syst. 2015;45:70–94.
  • Cardosa M , Korupolu MR , Singh A . Shares and utilities based power consolidation in virtualized server environments. In: Proceedings of the 11th IFIP/IEEE International Conference on Symposium on Integrated Network Management, IM’09. Long Island (NY): IEEE Press; 2009. p. 327–334.
  • Mazzucco M , Dyachuk D , Deters R . Maximizing cloud providers’ revenues via energy aware allocation policies. In: Proceedings of the 2010 IEEE 3rd International Conference on Cloud Computing, CLOUD ’10; IEEE Computer Society; 2010. p. 131–138.
  • Chase JS , Anderson DC , Thakar PN , et al. Managing energy and server resources in hosting centers. In: Proceedings of the Eighteenth ACM Symposium on Operating Systems Principles, SOSP ’01. New York (NY): ACM; 2001. p. 103–116.
  • Elnozahy EN , Kistler M , Rajamony R . Energy-efficient server clusters. In: Proceedings of the 2nd International Conference on Power-aware Computer Systems, PACS’02. Berlin, Heidelberg: Springer-Verlag; 2003. p. 179–197.
  • Pinheiro E , Bianchini R , Carrera EV , et al . Load balancing and unbalancing for power and performance in cluster-based systems. In: Proceedings of the Workshop on Compilers and Operating Systems for Low Power, COLP’01; 2001. p. 182–195.
  • Tchana A , Palma ND , Safieddine I , et al . Software consolidation as an efficient energy and cost saving solution. Future Gener Comput Syst. 2016;58:1–12.
  • Zhang Q , Chen H , Shen Y , et al . Optimization of virtual resource management for cloud applications to cope with traffic burst. Future Gener Comput Syst. 2016;58:42–55.
  • VMware vCenter Server [Online; accessed 2014 Aug 30]. Available from: http://www.vmware.com/products/vcenter-server/
  • Beloglazov A , Abawajy J , Buyya R . Energy-aware resource allocation heuristics for efficient management of data centers for cloud computing. Future Gener Comput Syst. 2012;28:755–768.
  • Voorsluys W , Broberg J , Venugopal S , et al. Cost of virtual machine live migration in clouds: a performance evaluation. In: Proceedings of the 1st International Conference on Cloud Computing, CloudCom ’09. Berlin, Heidelberg: Springer-Verlag; 2009. p. 254–265.
  • Tan PN , Steinbach M , Kumar V . Introduction to data mining. Boston: Addison-Wesley; 2005.
  • Quinlan JR . C4.5: programs for machine learning. San Francisco (CA): Morgan Kaufmann Publishers Inc.; 1993.
  • Cohen WW . Fast effective rule induction. In: Twelfth International Conference on Machine Learning. Tahoe City (CA): Morgan Kaufmann; 1995. p. 115–123.
  • Breiman L . Random forests. Mach Learn. 2001;45:5–32.
  • Beloglazov A , Buyya R . Energy efficient allocation of virtual machines in cloud data centers. In: Proceedings of the 2010 10th IEEE/ACM International Conference on Cluster, Cloud and Grid Computing, CCGRID ’10. Washington (DC): IEEE Computer Society; 2010. p. 577–578.
  • Gandhi A , Harchol-Balter M , Das R , et al . Optimal power allocation in server farms. SIGMETRICS Perform Eval Rev. 2009;37:157–168.
  • Kusic D , Kephart JO , Hanson JE , et al. Power and performance management of virtualized computing environments via lookahead control. In: Proceedings of the 2008 International Conference on Autonomic Computing, ICAC ’08; 2008. p. 3–12.
  • 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; Springer-Verlag New York Inc; 2008. p. 243–264.

Reprints and Corporate Permissions

Please note: Selecting permissions does not provide access to the full text of the article, please see our help page How do I view content?

To request a reprint or corporate permissions for this article, please click on the relevant link below:

Academic Permissions

Please note: Selecting permissions does not provide access to the full text of the article, please see our help page How do I view content?

Obtain permissions instantly via Rightslink by clicking on the button below:

If you are unable to obtain permissions via Rightslink, please complete and submit this Permissions form. For more information, please visit our Permissions help page.