Adaptive Load Balancing Scheme For Data Center Networks Using Software Defined Network

Shavan K. Askar(1)
(1) University of Duhok

Abstract

A new adaptive load balancing scheme for data center networks is proposed in this paper by utilizing the characteristics of Software Defined Networks. Mininet was utilized for the purpose of emulating and evaluating the proposed design, Miniedit was utilized as a GUI tool. In order to obtain a similar environment to the data center network, Fat-Tree topology was utilized. Different scenarios and traffic distributions were applied in order to cover as much cases of the real traffic as possible. The suggested design showed superiority over the traditional scheme in term of throughput and loss rate for all the evaluated scenarios. Two scenarios were implemented; the proposed algorithm presented a loss-free performance compared to 15% to 31% loss rate in the traditional scheme for the first scenario. The proposed scheme showed up to 81% improvement in the loss rate in the second scenario. In term of throughput, the proposed scheme maintained the same level of throughput in the first scenario compared to an average of 5Mbps reduction in the throughput when using the traditional scheme. While in the second scenario, the new scheme outperformed the traditional scheme by showing an improvement of up to 16.6% in the throughput value.

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Authors

Shavan K. Askar
juoz@uoz.edu.krd (Primary Contact)
Author Biography

Shavan K. Askar

Electrical and Computer Engineering Department, Collage of Engineering, University of Duhok, Kurdistan Region-Iraq.

Askar, S. K. (2016). Adaptive Load Balancing Scheme For Data Center Networks Using Software Defined Network. Science Journal of University of Zakho, 4(2), 275-286. https://sjuoz.uoz.edu.krd/index.php/sjuoz/article/view/403

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How to Cite

Askar, S. K. (2016). Adaptive Load Balancing Scheme For Data Center Networks Using Software Defined Network. Science Journal of University of Zakho, 4(2), 275-286. https://sjuoz.uoz.edu.krd/index.php/sjuoz/article/view/403

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