Vol.9, No.1, February 2020.                                                                                                                                                                           ISSN: 2217-8309

                                                                                                                                                                                                                        eISSN: 2217-8333


TEM Journal



Association for Information Communication Technology Education and Science

A Principal Component Analysis and Clustering based Load Balancing Strategy for Cloud Computing


Law Siew Xue, NazatulAini Abd Majid, Elankovan A. Sundararajan


© 2020 NazatulAini Abd Majid, published by UIKTEN. This work is licensed under the Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 License. (CC BY-NC-ND 4.0)


Citation Information: TEM Journal. Volume 9, Issue 1, Pages 93-100, ISSN 2217-8309, DOI: 10.18421/TEM91-14, February 2020.


Received: 04 July 2019.

Revised:   21 January 2020.
Accepted:  26 January 2020.
Published: 28 February 2020.




The objective of the research is to develop a model based on Principal Component Analysis and clustering for batch-processing load balancing in the cloud computing environment. The findings show that the model is able to extract the current computing resources of the physical hosts and cluster the hosts based on their similarity features. The computing resources of the virtual machine for a new requested task is then extracted and matched with the hosts clusters to select the most suitable physical hosts based on the computing resources. Conversely, when compared with the simulation results of the Round Robin and First Come First Serve load balancing models, the proposed method shows a decrease failure rate of task deployment events.


Keywords –Load balancing, Principal Component Analysis, Clustering, Cloud Computing, Task Allocation, Physical host pool.



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