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Flow Management Mechanism in Software-Defined Network

Eugene Tan, Yung-Wey Chong*, Mohammed F. R. Anbar

National Advanced IPv6 Centre, Universiti Sains Malaysia, USM, Penang, Malaysia

* Corresponding Author: Yung-Wey Chong. Email: email

(This article belongs to this Special Issue: Emerging Trends in Software-Defined Networking for Industry 4.0)

Computers, Materials & Continua 2022, 70(1), 1437-1459. https://doi.org/10.32604/cmc.2022.019516

Abstract

Software-defined networking (SDN) is a paradigm shift in modern networking. However, centralised controller architecture in SDN imposed flow setup overhead issue as the control plane handles all flows regardless of size and priority. Existing frameworks strictly reduce control plane overhead and it does not focus on rule placement of the flows itself. Furthermore, existing frameworks do not focus on managing elephant flows like RTSP. Thus, the proposed mechanism will use the flow statistics gathering method such as random packet sampling to determine elephant flow and microflow via a pre-defined threshold. This mechanism will ensure that the control plane works at an optimum workload because the controller only manages elephant flows via reactive routing and rule placement respectively. Reactive routing has reduced link bandwidth usage below the pre-defined threshold. Furthermore, rule placement has increased average throughput and total transfer to 238%. Meanwhile, the data plane switches will be able to forward microflows via multipath wildcard routing without invoking controller in greater responding time by 85 ms faster in two Transmission Control Protocol (TCP) traffic and achieved 11% and 12% higher total transfer size and throughput respectively. Hence, the controller’s workload reduced significantly to 48% in two TCP traffic.

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Cite This Article

E. Tan, Y. Chong and M. F. R. Anbar, "Flow management mechanism in software-defined network," Computers, Materials & Continua, vol. 70, no.1, pp. 1437–1459, 2022. https://doi.org/10.32604/cmc.2022.019516



cc This work is licensed under a Creative Commons Attribution 4.0 International License , which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
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