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AAMcon: an adaptively distributed SDN controller in data center networks

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Abstract

When evaluating the performance of distributed software-defined network (SDN) controller architecture in data center networks, the required number of controllers for a given network topology and their location are major issues of interest. To address these issues, this study proposes the adaptively adjusting and mapping controllers (AAMcon) to design a stateful data plane. We use the complex network community theory to select a key switch to place the controller which is closer to switches it controls in a subnet. A physically distributed but logically centralized controller pool is built based on the network function virtualization (NFV). And then we propose a fast start/overload avoid algorithm to adaptively adjust the number of controllers according to the demand. We performed an analysis for AAMcon to find the optimal distance between the switch and controller. Finally, experiments show the following results. (1) For the number of controllers, AAMcon can greatly follow the demand; for the placement location of controller, controller can respond to the request of switch with the least distance to minimize the delay between the switch and it. (2) For failure tolerance, AAMcon shows good robustness. (3) AAMcon requires less delay to the network with more significant community structure. In fact, there is an inverse relationship between the community modularity and average distance between the switch and controller, i.e., the average delay decreases when the community modularity increases.(4) AAMcon can achieve the load balance between the controllers. (5) Compared to DCP-GK and k-critical, AAMcon shows good performance.

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Acknowledgements

This work was supported by the National Natural Science Foundation of China (Grant Nos. 61872102, 61571141, 61802080, 51575116, 61806058), the China National Spark Program (2015GA780065), the Science and Technology Project of Guangdong Province (2017A010102014, 2016A010102022); the Innovative Team Project of Guangdong Universities (2017KCXTD025); the Innovative Academic Team Project of Guangzhou Education System (1201610013), and Guangzhou Science and Technology Project (201604016001), China.

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Authors and Affiliations

  1. Department of Electronic and Information Engineering, Guangzhou University, Guangzhou, 510006, China

    Waixi Liu, Yu Wang, Jie Zhang, Hongjian Liao, Zhongwei Liang & Xiaochu Liu

Authors
  1. Waixi Liu
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  2. Yu Wang
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  3. Jie Zhang
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  4. Hongjian Liao
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  5. Zhongwei Liang
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  6. Xiaochu Liu
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Correspondence to Waixi Liu.

Additional information

Waixi Liu received the PhD in communication and information system from Sun Yat-Sen University, China in 2013. He is currently an associate professor in the Department of Electronic and Information Engineering, Guangzhou University. His research interests are in future network, data mining and network coding. He has published more than 20 papers.

Yu Wang received the PhD degree in computer science from Deakin University, Victoria. He is currently associate professor with Guangzhou University, China. His research interests include network traffic modeling and classification, social networks, mobile networks, and network security.

Jie Zhang received the MS degree in electrical engineering from South China University of Technology, China in 2006. Presently, he is an engineer in the School of Mechanical and Electrical Engineering at Guangzhou University, China. His research field is distribution system reliability evaluation.

Hongjian Liao is a PhD candidate of South China Normal University, China and he is currently associate research fellow with Guangzhou University, China. His research interests include knowledge recommendation based on context-aware, e-learning and blended learning.

Zhongwei Liang received the PhD degrees from South China University of Technology, China in 2010. He now is a professor in Guangzhou University, China. His current research interests include deep learning, intelligent manufacturing and image processing.

Xiaochu Liu received the PhD degrees from South China University of Technology, China in 2006. He now is a professor in Guangzhou University, China. His current research interests include robotics, intelligent manufacturing, and the resource allocation in next-generation wireless communication systems.

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Liu, W., Wang, Y., Zhang, J. et al. AAMcon: an adaptively distributed SDN controller in data center networks. Front. Comput. Sci. 14, 146–161 (2020). https://doi.org/10.1007/s11704-019-7266-6

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