Open Access

ARTICLE

Performance Evaluation of Topologies for Multi-Domain Software-Defined Networking

Jiangyuan Yao¹, Weiping Yang¹, Shuhua Weng¹, Minrui Wang¹, Zheng Jiang², Deshun Li^1,*, Yahui Li³, Xingcan Cao⁴

1 School of Computer Science and Technology, Hainan University, Haikou, 570100, China
2 School of Cyberspace Security, Hainan University, Haikou, 570100, China
3 School of Software, Beijing Jiaotong University, Beijing, 10004, China
4 University of British Columbia, Vancouver, V5K1K5, Canada

* Corresponding Author: Deshun Li. Email:

Computer Systems Science and Engineering 2023, 47(1), 741-755. https://doi.org/10.32604/csse.2023.031531

Received 20 April 2022; Accepted 20 June 2022; Issue published 26 May 2023

Abstract

Software-defined networking (SDN) is widely used in multiple types of data center networks, and these distributed data center networks can be integrated into a multi-domain SDN by utilizing multiple controllers. However, the network topology of each control domain of SDN will affect the performance of the multi-domain network, so performance evaluation is required before the deployment of the multi-domain SDN. Besides, there is a high cost to build real multi-domain SDN networks with different topologies, so it is necessary to use simulation testing methods to evaluate the topological performance of the multi-domain SDN network. As there is a lack of existing methods to construct a multi-domain SDN simulation network for the tool to evaluate the topological performance automatically, this paper proposes an automated multi-domain SDN topology performance evaluation framework, which supports multiple types of SDN network topologies in cooperating to construct a multi-domain SDN network. The framework integrates existing single-domain SDN simulation tools with network performance testing tools to realize automated performance evaluation of multi-domain SDN network topologies. We designed and implemented a Mininet-based simulation tool that can connect multiple controllers and run user-specified topologies in multiple SDN control domains to build and test multi-domain SDN networks faster. Then, we used the tool to perform performance tests on various data center network topologies in single-domain and multi-domain SDN simulation environments. Test results show that Space Shuffle has the most stable performance in a single-domain environment, and Fat-tree has the best performance in a multi-domain environment. Also, this tool has the characteristics of simplicity and stability, which can meet the needs of multi-domain SDN topology performance evaluation.

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Keywords

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