Cloud Environment Workload Prediction

Authors

  • Smitha Krishnan SB College, Chanaganacherry, (Research Scholar Bharatiar University,Coimbatore) Author
  • Dr.B.G Prashanthi ST,Josephs, College, Bangalore(Research Scholar Bharatiar University,Coimbatore) Author

DOI:

https://doi.org/10.61841/70cs4234

Keywords:

Prediction, Genetic Algorithm, KNN

Abstract

 Scalability and elasticity are very important features in Cloud environment. Analysis of workload can be done and future work load can be predicted for better resource allocation and efficacy of cloud platform there by reducing the cost. A number of regression models are taken for that. 

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References

1. Fusion model for cpu load prediction in cloud computing: journal of networks, vol. 8, no. 11, november

2013

2. Time series forecasting of cloud data center workloads vazquez, krishnan, and john

3. 2019 27th euromicro international conference on parallel, distributed and network-based a preliminary

study of machine learning workload prediction techniques for cloud applications

4. Dionatr˜a f. Kirchoff, miguelxavier, julianamastella and c´esar a. F de roseprocessing

5. International journal of computer applications (0975 – 8887) volume 109 – no. 9, january 2015 a review

on workload prediction of cloud services supreetkaursahi

6. International conference on computational intelligence: modeling techniques and applications (cimta)

2013-a genetic algorithm (ga) based load balancing strategy for cloud computing, kousikdasguptaa

7. Research on the prediction model of cpu utilization based on arima-bp

8. Neural network- 2019 27th euromicro international conference on parallel, distributed and network-based

processing

9. A preliminary study of machine learning workload prediction techniques for cloud applicationsDionatr˜a

f. Kirchoff, miguelxavier, julianamastella and c´esar a. F de rose

10. International conference on computational intelligence: modeling techniques and applications-a genetic

algorithm (ga) based load balancing strategy forCloud computing kousikdasguptaa,

11. International journal of computer trends and technology (ijctt) – volume 44 issue 1- february 2017 issn:

2231-2803 http://www.ijcttjournal.org page 15 energy efficient cloud computing vm placement based on

genetic algorithm poojadaharwal (soitrgpvbhopal) dr.varshasharma (soitrgpvbhopal)

12. A multi-objective genetic algorithm for virtual machine placement in cloud computing

avinashkumarsharma, dr. Nitin

13. A utilization based genetic algorithm for virtual machine placement in cloud computing systems a thesis

submitted to the graduate school of engineering and science of bilkent university in partial fulfillment of

the requirements for the degree of master of science in computer engineering by mustafa can c¸ avdar

14. Combining time series prediction models using genetic algorithm to auto-scaling web applications hosted

in the cloud infrastructure valterrog´eriomessias · juliocezarestrella · ricardoehlers · marco

15. Combining genetic algorithms and simulation to search for failure scenarios in system models kevin mills,

christopherdabrowski, jamesfilliben and sandy ressler(ijacsa) international journal of advanced computer

science and applications, vol. 7, no. 4, 2016

16. Genetic-based task scheduling algorithm in cloud computing environment safwat a. Hamad department of

computer science, faculty of computers & information, cairo university, cairo, egyptfatma

17. Omara department of computer science, faculty of computers & information, cairo university, cairo, egypt

18. International conference on computational intelligence: modeling techniques and applications (cimta)

2013 a genetic algorithm (ga) based load balancing strategy for cloud computing kousikdasguptaa

,brototimandalb, paramarthaduttac , jyotsnakumarmondop conference series: materials science and

engineering paper • open access load balancing in multi cloud computing environment with genetic

algorithm

19. International Journal of Computer Applications (0975 – 8887) Volume 182– No.12, August 2018

20. Load Balancing Technique in Public Cloud Environments using Combination of Heuristic Function and

KNN ClassificationRahul Dongarde

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Published

31.10.2019

How to Cite

Krishnan, S., & Prashanthi, .B.G. (2019). Cloud Environment Workload Prediction. International Journal of Psychosocial Rehabilitation, 23(4), 1937-1941. https://doi.org/10.61841/70cs4234