Open Access   Article Go Back

Virtual Machine Placement using Interactive Artificial Bee Colony Algorithm(VMPIABC)

Shubham Kumar1 , Atul Tripathi2

Section:Research Paper, Product Type: Journal Paper
Volume-9 , Issue-10 , Page no. 1-6, Oct-2021

CrossRef-DOI:   https://doi.org/10.26438/ijcse/v9i10.16

Online published on Oct 31, 2021

Copyright © Shubham Kumar, Atul Tripathi . This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.

View this paper at   Google Scholar | DPI Digital Library

XML View
PDF Download

How to Cite this Paper

  • IEEE Citation
  • MLA Citation
  • APA Citation
  • BibTex Citation
  • RIS Citation

IEEE Style Citation: Shubham Kumar, Atul Tripathi, “Virtual Machine Placement using Interactive Artificial Bee Colony Algorithm(VMPIABC),” International Journal of Computer Sciences and Engineering, Vol.9, Issue.10, pp.1-6, 2021.

MLA Style Citation: Shubham Kumar, Atul Tripathi "Virtual Machine Placement using Interactive Artificial Bee Colony Algorithm(VMPIABC)." International Journal of Computer Sciences and Engineering 9.10 (2021): 1-6.

APA Style Citation: Shubham Kumar, Atul Tripathi, (2021). Virtual Machine Placement using Interactive Artificial Bee Colony Algorithm(VMPIABC). International Journal of Computer Sciences and Engineering, 9(10), 1-6.

BibTex Style Citation:
@article{Kumar_2021,
author = {Shubham Kumar, Atul Tripathi},
title = {Virtual Machine Placement using Interactive Artificial Bee Colony Algorithm(VMPIABC)},
journal = {International Journal of Computer Sciences and Engineering},
issue_date = {10 2021},
volume = {9},
Issue = {10},
month = {10},
year = {2021},
issn = {2347-2693},
pages = {1-6},
url = {https://www.ijcseonline.org/full_paper_view.php?paper_id=5404},
doi = {https://doi.org/10.26438/ijcse/v9i10.16}
publisher = {IJCSE, Indore, INDIA},
}

RIS Style Citation:
TY - JOUR
DO = {https://doi.org/10.26438/ijcse/v9i10.16}
UR - https://www.ijcseonline.org/full_paper_view.php?paper_id=5404
TI - Virtual Machine Placement using Interactive Artificial Bee Colony Algorithm(VMPIABC)
T2 - International Journal of Computer Sciences and Engineering
AU - Shubham Kumar, Atul Tripathi
PY - 2021
DA - 2021/10/31
PB - IJCSE, Indore, INDIA
SP - 1-6
IS - 10
VL - 9
SN - 2347-2693
ER -

VIEWS PDF XML
347 454 downloads 162 downloads
  
  
           

Abstract

As cloud computing is becoming part of our life day by day, it has attracted research community to tackle the research problems of cloud computing environment. Virtual machine placement is a brewing area for cloud researchers so in the proposed model virtual machine placement problem is modelled as an optimization problem with the objective of resource wastage. As huge resource wastage can affect the cloud service provider so, an virtual machine placement algorithm based on interactive artificial bee colony was proposed. The performance of the proposed method is thoroughly compared with other competing algorithms through exhaustive experiments and results are presented.

Key-Words / Index Term

Virtual Machine, Cloud Computing, Artificial Bee Colony, Resource Wastage, Optimization

References

[1] A. Tripathi, “Task Allocation on Cloud Resources using Analytic Network Process,” pp. 971–978, 2015.
[2] A. Tripathi, I. Pathak, and D. Prakash, “Modified Dragonfly Algorithm for Optimal Virtual Machine Placement in Cloud Computing,” pp. 1316-1342, 2020
[3] S. Azizi, M. Shojafar, and S. Member, “GRVMP?: A Greedy Randomized Algorithm for Virtual Machine Placement in Cloud Data Centers,” pp. 1–12, 2020.
[4] W. Zhang, X. Chen, and J. Jiang, “A Multi-Objective Optimization Method of Initial Virtual Machine Fault-Tolerant Placement for Star Topological Data Centers of Cloud Systems,” vol. 26, no. 1, pp. 95–111, 2021.
[5] X. Fu and C. Zhou, “Predicted Affinity Based Virtual Machine Placement in Cloud Computing Environments,” IEEE Trans. Cloud Comput., vol. 8, no. 1, pp. 246–255, 2020.
[6] M. Ghetas, “A multi-objective Monarch Butterfly Algorithm for virtual machine placement in cloud computing,” Neural Comput. Appl., vol. 33, no. 17, pp. 11011–11025, 2021.
[7] S. Gharehpasha, M. Masdari, and A. Jafarian, "Virtual machine placement in cloud data centers using a hybrid multi-verse optimization algorithm," vol. 54, no. 3. Springer Netherlands, 2021.
[8] D. Alboaneen, H. Tianfield, Y. Zhang, and B. Pranggono, “A metaheuristic method for joint task scheduling and virtual machine placement in cloud data centers,” Futur. Gener. Comput. Syst., vol. 115, pp. 201–212, 2021.
[9] B. Zhang, X. Wang, and H. Wang, “Virtual machine placement strategy using cluster-based genetic algorithm,” Neurocomputing, vol. 428, pp. 310–316, 2021.
[10] Shalu and D. Singh, “Artificial neural network-based virtual machine allocation in cloud computing,” pp. 1-12, 2021.
[11] K. M. B. S. V. Bhanu, “A multi-objective krill herd algorithm for virtual machine placement in cloud computing,” vol. 76, no. 6, pp. 4525-4542, 2018.
[12] A. Ponraj, “Optimistic Virtual Machine Placement in Cloud Data Centers using Queuing Approach,” vol. 93, pp. 338-344, 2018.
[13] W. Yao, Y. Shen, and D. Wang, “A Weighted PageRank-Based Algorithm for Virtual Machine Placement in Cloud Computing,” IEEE Access, vol. 7, pp. 176369–176381, 2019.
[14] Z. Zhou, M. Shojafar, M. Alazab, J. Abawajy, and F. Li, “AFED-EF: An Energy-Efficient VM Allocation Algorithm for IoT Applications in a Cloud Data Center,” IEEE Trans. Green Commun. Netw., vol. 5, no. 2, pp. 658–669, 2021.
[15] X. Yu, W. Chen, and X. Zhang, “An Artificial Bee Colony Algorithm for Solving Constrained Optimization Problems,” Proc. 2018 2nd IEEE Adv. Inf. Manag. Commun. Electron. Autom. Control Conf. IMCEC 2018, pp. 2663–2666, 2018.
[16] I. Pathak and D. P. Vidyarthi, “An Interactive Artificial Bee Colony based Virtual Network Embedding,” pp. 1-6, 2015.
[17] P. W. Tsai, M. K. Khan, J. S. Pan, and B. Y. Liao, “Interactive artificial bee colony supported passive continuous authentication system,” IEEE Syst. J., vol. 8, no. 2, pp. 395–405, 2014.
[18] A. Tripathi, I. Pathak, and D. P. Vidyarthi, “Energy Efficient VM Placement for Effective Resource Utilization using Modified Binary PSO,” Comput. J., vol. 61, no. 6, pp. 832–846, 2018.