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DOI: 10.14569/IJACSA.2018.090462
PDF

Load Balancing based on Bee Colony Algorithm with Partitioning of Public Clouds

Author 1: Pouneh Ehsanimoghadam
Author 2: Mehdi Effatparvar*

International Journal of Advanced Computer Science and Applications(IJACSA), Volume 9 Issue 4, 2018.

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Abstract: Cloud computing is an emerging trend in the IT industry that provides new opportunities to control costs associated with the creation and maintenance of applications. Of prevalent issues in cloud computing, load balancing is a primary one as it has a significant impact on efficiency and plays a leading role in improved management. In this paper, by using a heuristic search technique called the bee colony algorithm, tasks are balanced on a virtual machine such that their waiting time in the queue is minimized. In the proposed model, the cloud is partitioned into several sectors with many nodes as resources of distributed computing. Furthermore, the indices of speed and cost are considered to prioritize virtual machines. The results of a simulation show that the proposed model outperforms prevalent algorithms as it balances the prioritization of tasks on the virtual machine as well as the entire cloud system and minimizes the waiting times of tasks in the queue. It also reduces the completion time of tasks in comparison with the HBB-LB, WRR, and FCFS algorithms.

Keywords: Cloud computing; load balancing; bee colony algorithm; public cloud; cloud partitioning

Pouneh Ehsanimoghadam and Mehdi Effatparvar*, “Load Balancing based on Bee Colony Algorithm with Partitioning of Public Clouds” International Journal of Advanced Computer Science and Applications(IJACSA), 9(4), 2018. http://dx.doi.org/10.14569/IJACSA.2018.090462

@article{Ehsanimoghadam2018,
title = {Load Balancing based on Bee Colony Algorithm with Partitioning of Public Clouds},
journal = {International Journal of Advanced Computer Science and Applications},
doi = {10.14569/IJACSA.2018.090462},
url = {http://dx.doi.org/10.14569/IJACSA.2018.090462},
year = {2018},
publisher = {The Science and Information Organization},
volume = {9},
number = {4},
author = {Pouneh Ehsanimoghadam and Mehdi Effatparvar*}
}



Copyright Statement: This is an open access article licensed under a Creative Commons Attribution 4.0 International License, which permits unrestricted use, distribution, and reproduction in any medium, even commercially as long as the original work is properly cited.

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