Energy-efficient scheme based on user task characteristic in virtual cloud platform (original) (raw)

References

  1. Senyo, P.K., Addae, E., Boateng, R.: Cloud computing research: a review of research themes, frameworks, methods and future research directions. Int. J. Inf. Manag. 38(1), 128–139 (2018)
    Article Google Scholar
  2. Chang, Z., Zhou, S., Ristaniemi, T., et al.: Collaborative mobile clouds: an energy efficient paradigm for content sharing. IEEE Wirel. Commun. 25(2), 186–192 (2018)
    Article Google Scholar
  3. Susanta, N.A.: Survey on virtualization technologies. . http://www.ecsl.cs.sunysb.edu/tr/TR179.pdf (2011). Accessed 20 June 2011
  4. Liu, X.F., Zhan, Z.H., Deng, J.D., et al.: An energy efficient ant colony system for virtual machine placement in cloud computing. IEEE Trans. Evol. Comput. 22(1), 113–128 (2018)
    Article Google Scholar
  5. Hameed, A., Khoshkbarforoushha, A., Ranjan, R., et al.: A survey and taxonomy on energy efficient resource allocation techniques for cloud computing systems. Computing 98(7), 751–774 (2016)
    Article MathSciNet Google Scholar
  6. Magklis, G., Scott, M.L., Semeraro, G., et al.: Profile-based dynamic voltage and frequency scaling for a multiple clock domain microprocessor. In: ACM SIGARCH Computer Architecture News, vol. 31, No. 2, pp. 14–27. ACM (2003)
  7. Kusic, D., Kephart, J.O., Hanson, J.E., et al.: Power and performance management of virtualized computing environments via lookahead control. Cluster Comput 12(1), 1–15 (2009)
    Article Google Scholar
  8. Buyya, R., Ranjan, R., Calheiros, R.N.: Modeling and simulation of scalable cloud computing environments and the CloudSim toolkit: challenges and opportunities. In: Proceedings of the 7th High Performance Computing & Simulation Conference, pp. 1–11. IEEE, Leipzig (2009)
  9. 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
  10. Duan, H., Chen, C., Min, G., et al.: Energy-aware scheduling of virtual machines in heterogeneous cloud computing systems. Future Gener. Comput. Syst. 74, 142–150 (2017)
    Article Google Scholar
  11. Aujla, G.S., Kumar, N.: MEnSuS: an efficient scheme for energy management with sustainability of cloud data centers in edge–cloud environment. Future Gener. Comput. Syst. 86, 1279–1300 (2018)
    Article Google Scholar
  12. Leverich, J., Kozyrakis, C.: On the energy in efficiency of Hadoop clusters. ACM SIGOPS Oper. Syst. Rev. 44(1), 61–65 (2010)
    Article Google Scholar
  13. Mei, J., Li, K., Li, K.: Customer-satisfaction-aware optimal multiserver configuration for profit maximization in cloud computing. T-SUSC 2(1), 17–29 (2017)
    Google Scholar
  14. Boru, D., Kliazovich, D., Granelli, F., et al.: Energy-efficient data replication in cloud computing datacenters. Cluster Comput 18(1), 385–402 (2015)
    Article Google Scholar
  15. Nguyen, T.H., Di Francesco, M., Yla-Jaaski, A.: Virtual machine consolidation with multiple usage prediction for energy-efficient cloud data centers. IEEE Trans. Serv. Comput. (2017). https://doi.org/10.1109/TSC.2017.2648791
  16. Chen, H., Zhu, X., Guo, H., et al.: Towards energy-efficient scheduling for real-time tasks under uncertain cloud computing environment. J. Syst. Softw. 99, 20–35 (2015)
    Article Google Scholar
  17. Chang, F., Ren, J., Viswanathan, R.: Optimal resource allocation in clouds. In: Proceedings of the 2010 IEEE 3rd International Conference on Cloud Computing, pp. 418–425 IEEE Computer Society (2010)
  18. Fu, Z., Sun, X., Liu, Q., et al.: Achieving efficient cloud search services: multi-keyword ranked search over encrypted cloud data supporting parallel computing. IEICE Trans. Commun. 98(1), 190–200 (2015)
    Article Google Scholar
  19. Liu, J., Yu, J., Shen, S.: Energy-efficient two-layer cooperative defense scheme to secure sensor-clouds. IEEE Trans. Inf. Forensics Secur. 13(2), 408–420 (2018)
    Article Google Scholar
  20. Zhang, K., Mao, Y., Leng, S., et al.: Energy-efficient offloading for mobile edge computing in 5G heterogeneous networks. IEEE Access 4, 5896–5907 (2016)
    Article Google Scholar
  21. Papadimitriou, C.H.: Computational complexity. Wiley, Chichester (2003)
    MATH Google Scholar
  22. Li, X., Jiang, X., Garraghan, P., et al.: Holistic energy and failure aware workload scheduling in cloud data centers. Future Gener. Comput. Syst. 78, 887–900 (2018)
    Article Google Scholar
  23. Marahatta, A., Pirbhulal, S., Zhang, F., et al.: Classification-based and energy-efficient dynamic task scheduling scheme for virtualized cloud data center. IEEE Trans. Cloud Comput. (2019). https://doi.org/10.1109/TCC.2019.2918226

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