Energy aware dynamic virtual machine consolidation in cloud data centers

  • Authors

    • G Anusha
    • P Supraja
    2018-03-19
    https://doi.org/10.14419/ijet.v7i2.8.10519
  • Cloud computing, Resource utilization, VM Consolidation, VM Placement, energy consumption.
  • Cloud computing is a growing technology now-a-days, which provides various resources to perform complex tasks. These complex tasks can be performed with the help of datacenters. Data centers helps the incoming tasks by providing various resources like CPU, storage, network, bandwidth and memory, which has resulted in the increase of the total number of datacenters in the world. These data centers consume large volume of energy for performing the operations and which leads to high operation costs. Resources are the key cause for the power consumption in data centers along with the air and cooling systems. Energy consumption in data centers is comparative to the resource usage. Excessive amount of energy consumption by datacenters falls out in large power bills. There is a necessity to increase the energy efficiency of such data centers. We have proposed an Energy aware dynamic virtual machine consolidation (EADVMC) model which focuses on pm selection, vm selection, vm placement phases, which results in the reduced energy consumption and the Quality of service (QoS) to a considerable level.
  • References

    1. [1] A. Beloglazov and R. Buyya, “Energy efï¬cient resource management in virtualized cloud data centers,†in 10th IEEE/ACM International conference on Cluster, Cloud Grid Computing, pp. 826–831, May 2010.

      [2] A. Beloglazov, J. Abawajy, and R. Buyya, “Energy-aware resource allocation heuristics for efï¬cient management of data centers for cloud computing,†Future Generation Computer Systems, vol 28, pp. 755–768, May 2012.

      [3] Ankita Choudhary, Dr.K.J.Mathai “Optimize Virtual Machine Placement in Banker Algorithm for Energy Efficient Cloud Computing†International Journal of Innovative Research in Computer and communication Engineering, vol 4, issue 4, April 2016.

      [4] D. Frederico, C. Jose, F. Anderson, and G. Vinicius, ‘‘A systematic review on cloud computing,’’ Journal of Supercomputing, vol. 68, pp. 1321–1346, June 2014.

      [5] Dr. Naveen Kumar Gondhi and Mr. Paras Kailu “Prediction Based Energy Efficient Virtual Machine Consolidation in Cloud Computing†Second International Conference on Advances in Computing and Communication Engineering, 2015.

      [6] Divya Bharathi P and Vamsee Krishna Kiran M “Virtual Machine Placement Strategies in Cloud Computing†International Conference on Innovations in Power and Advanced Computing Technologies [iPACT2017], 2017.

      [7] E. Arianyan, H. Taheri , and S. Sharifian, "Novel Energy and SLA Efficient Resource Management Heuristics for Consolidation of Virtual Machines in Cloud Data Centers," Computers & Electrical Engineering, vol. 47, pp. 222-240, 2015.

      [8] FahimehFarahnakian, TapioPahikkala, PasiLiljeberg, JuhaPlosila and HannuTenhunen “Multi-Agent based Architecture for Dynamic VM consolidation in Cloud Data Centers†40 th IEEE Euromicro Conference on Software Engineering and Advanced Applications, 2014.

      [9] G. Keller, M. Tighe, H. Lutï¬yya, and M. Bauer, ‘‘An analysis of ï¬rst ï¬t heuristics for the virtual machine relocation problem,’’ in Proc. 8th International Conference Workshop System Virtualization Management (SVM) Network Service Management. (CNSM), pp. 406–413, Oct. 2012.

      [10] Harshit Verma, Surat Kumar Dhal “Energy Effficient Virtual Machine Migration in Cloud data centers†dissertion, National Institute of Technology, Rourkela,2015.

      [11] Jiankang Dong, Xing Jin, Hongbo Wang, Yangyang Li, Peng Zhang, Shiduan Cheng “Energy-Saving Virtual Machine Placement in Cloud Data Centers†13 th IEEE/ACM International Symposium on Cluster, Cloud, and Grid Computing, 2013.

      [12] Li Hongyou1, Wang Jiangyong, Peng Jian, Wang Junfeng, Liu Tang, “Energy-Aware Scheduling Scheme Using Workload Aware Consolidation Technique in Cloud Data Centres,†China Communications, pp.114-124. Dec 2013.

      [13] Mohammed Rashid Chowdhury, Mohammad Raihan Mahmud, RashedurM.Rahman “Implementation and performance analysis of various VM placement strategies in CloudSim†Journal of Cloud Computing, vol 4, issue 1, Dec 2015.

      [14] Perla Ravi Theja, S.K.Khadar Babu “An Evolutionary Computing based Energy Efficient VM Consolidation Scheme for Optimal Resource Utilization and QoS Assurance†Indian journal of Science and Technology, vol 8, issue 26, Oct 2015.

      [15] Qi Chen, Jianxin Chen, Baoyu Zheng, Jingwu Cui and Yi Qian “Utilization-based VM Consolidation Scheme For Power Efficiency in Cloud Data Centers†IEEE ICC-Cloud Computing Systems, Networks, and Applications(CCSNA), 2015.

      [16] R.N.Calheiros, R.Ranjan, A.Beloglazov, C.A.F.DeRose, and R.Buyya, ‘‘CloudSim: A toolkit for modeling and simulation of cloud computing environments and evaluation of resource provisioning algorithms,’’ Softw. Pract. Exper., vol. 41, pp. 23–50, Sep. 2011.

      [17] R.Ranjana,S.Radha and J.Raja :Performance study of resource aware energy efficient VM Placement Algorithm†IEEE WiSPNET Conference,2016.

      [18] Saad Mustafa, Kashif Bilal, Sajjad A.Madani, Samee U.Khan, Nikos Tziritas and Laurence T.Yang “Performance Evaluation of Energy-aware Best Fit Decreasing Algorithms for Cloud Environments†IEEE International Conference on Data Science and Data Intensive Systems, 2015.

      [19] Thiago Kenji Okada, Albert De La Fuente Vigliotti “Consolidation of VMs to Improve Energy Efficiency in Cloud Computing Environments†Computer networks and distributed systems, 2015.

      [20] Y. Lee and A. Zomaya, “Energy efï¬cient utilization of resources in cloud computing systems,†Journal of Supercomputing, vol. 60, pp. 268– 280, May 2012.

      [21] Zhou, Zhigang Hu, and Keqin Li. "Virtual machine placement algorithm for both energy-awareness and sla violation reduction in cloud data centers." Scientific Programming, 2016.

  • Downloads

  • How to Cite

    Anusha, G., & Supraja, P. (2018). Energy aware dynamic virtual machine consolidation in cloud data centers. International Journal of Engineering & Technology, 7(2.8), 550-553. https://doi.org/10.14419/ijet.v7i2.8.10519