VNR_CCP: A New Approach to Congestion Control Using Virtualization Technique and Switch Migration in SDN

Document Type : Computer Article

Authors

1 PhD Student, Department of Computer Engineering, Maybod Branch, Islamic Azad University, Maybod, Iran

2 Assistant Professor, Department of Computer Engineering, Taft Branch, Islamic Azad University, Taft, Iran

3 Assistant Professor, Department of Computer Engineering, Maybod Branch, Islamic Azad University, Maybod, Iran

Abstract

By separating the data layer from the control layer in the software defined network and the possibility of centralized and programmable management, many limitations and common problems in traditional networks can be solved or improved. One of the existing problems in these networks is the issue of congestion and its control. In software defined networks, the use of information under the supervision of domain controllers and the collection of network statistics can be useful in controlling or preventing congestion. When an SDN switch node is subjected to many requests, the network becomes congested, and to solve this problem, the controller can use network virtualization and switch migration, taking into account the free resources available in the switches and links.  In this paper, a software-based network approach for congestion control and optimal resource management called VNR_CCP is presented. In this approach, an attempt has been made to control congestion by calculating the nodes and links profit to search for congestion and request the virtual network to reduce the existing load and manage resources. The result of the simulation using the NS2 simulator shows that the proposed approach has better performance compared to the similar method. It was concluded that the throughput has increased by 4.3%, the delay has decreased by 5.3%, and the average cost has decreased by 26% compared to the similar method.
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References

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Journal of Modeling in Engineering
Volume 22, Issue 76
May 2024
Pages 85-98

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History

  • Receive Date: 28 October 2022
  • Revise Date: 08 September 2023
  • Accept Date: 20 September 2023

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