CFP last date
20 December 2024
Reseach Article

Improvement in Genetic Algorithm for Virtual Machine Migration in Cloud Computing

Published on July 2018 by Arshdeep Kaur, Simarjit Kaur, Yogesh Kumar
International Conference on Advances in Emerging Technology
Foundation of Computer Science USA
ICAET2017 - Number 2
July 2018
Authors: Arshdeep Kaur, Simarjit Kaur, Yogesh Kumar
bc845d96-86fb-4552-a015-b57808dc331e

Arshdeep Kaur, Simarjit Kaur, Yogesh Kumar . Improvement in Genetic Algorithm for Virtual Machine Migration in Cloud Computing. International Conference on Advances in Emerging Technology. ICAET2017, 2 (July 2018), 29-33.

@article{
author = { Arshdeep Kaur, Simarjit Kaur, Yogesh Kumar },
title = { Improvement in Genetic Algorithm for Virtual Machine Migration in Cloud Computing },
journal = { International Conference on Advances in Emerging Technology },
issue_date = { July 2018 },
volume = { ICAET2017 },
number = { 2 },
month = { July },
year = { 2018 },
issn = 0975-8887,
pages = { 29-33 },
numpages = 5,
url = { /proceedings/icaet2017/number2/29649-7063/ },
publisher = {Foundation of Computer Science (FCS), NY, USA},
address = {New York, USA}
}
%0 Proceeding Article
%1 International Conference on Advances in Emerging Technology
%A Arshdeep Kaur
%A Simarjit Kaur
%A Yogesh Kumar
%T Improvement in Genetic Algorithm for Virtual Machine Migration in Cloud Computing
%J International Conference on Advances in Emerging Technology
%@ 0975-8887
%V ICAET2017
%N 2
%P 29-33
%D 2018
%I International Journal of Computer Applications
Abstract

The cloud computing is the architecture in which hosts, virtual machines, brokers, virtual servers are involved in the communications. The cloud architecture is the de-centralized network for task migration, task allocation, security. This work is based on the task migration when virtual machine get overloaded at the time of cloudlet execution. The brokers are responsible to assign tasks to the most appropriate virtual machine for the execution. When any of the virtual machine get overloaded, the task is migrated from one virtual machine to another which can be decided by the improved genetic algorithm. The proposed and existing algorithms are implement in cloudsim and it analyze the execution time, space utilization. Execution time, space utilization is reduce by the proposed improvement.

References
  1. Abdul Hameed, Alireza Khoshkbarforoushha, Rajiv Ranjan, Prem Prakash Jayaraman, Joanna Kolodziej, Pavan Balaji, Sherali Zeadally," A survey and taxonomy on energy efficient resource allocation techniques for cloud computing systems", 2014, Computing 1–24
  2. Amit N, Sanjay C, Gaurav S," Policy based resource allocation in IaaS cloud", 2012, Future Gener Comput Syst 28:94–103
  3. Christian V, Rodrigo NC, Dileban K, Rajkumar B," Deadline-driven provisioning of resources for scientific applications in hybrid clouds with Aneka", 2012, Future Gener Comput Syst 28:58–65
  4. Doulamis ND, Kokkinos P, Varvarigos E," Resource selection for tasks with time requirements using spectral clustering", 2014, IEEE Trans Comput 63(2):461–474 Vol. 63, No. 2
  5. Guiyi W, Athanasios V, Vasilakos YZ, Naixue X," A game-theoretic method of fair resource allocation for cloud computing services", 2012, J Supercomput 54:252–269
  6. Hassan MM, Song B, Hossain MS, Alamri A," QoS-aware resource provisioning for big data processing in cloud computing environment", 2014, international conference on computational science and computational intelligence, Las Vegas, NV, USA
  7. Huangke Chen, Xiaomin Zhu, Hui Guo, Jianghan Zhu, Xiao Qin, Jianhong Wu," Towards Energy-Efficient Scheduling for Real-Time Tasks under Uncertain Cloud Computing Environment", 2015, J Syst Softw 99:20–35
  8. Liang Q, Zhang J, Zhang YH, Liang JM," The placement method of resources and applications based on request prediction in cloud data center", 2014, Inf Sci 279:735–745
  9. Simon SW, Jelena M," Optimal application allocation on multiple public clouds", 2014, Comput Network 68:138–148
  10. Yin C, Huang BQ, Liu F et al," Common key technology system of cloud manufacturing service platform for small and medium enterprises", 2011, Comput Integr Manuf Syst 17:495–503
  11. Young Choon Lee, Albert Y. Zomaya," Energy efficient utilization of resources in cloud computing systems", 2012, J Supercomput60:268–280
  12. Zhanjie Wang, Xianxian Su," Dynamically hierarchical resource-allocation algorithm in cloud computing environment", 2015, J Supercomput
Index Terms

Computer Science
Information Sciences

Keywords

Cloudlets Brokers Virtual Machine Genetic Algorithm