A Scalable Load Balancing Scheme for Software-Defined Datacenter Networks based on Fuzzy Logic

doi:10.23940/ijpe.19.08.p22.22172227

Int J Performability Eng ›› 2019, Vol. 15 ›› Issue (8): 2217-2227.doi: 10.23940/ijpe.19.08.p22.22172227

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A Scalable Load Balancing Scheme for Software-Defined Datacenter Networks based on Fuzzy Logic

Guoyan Li^a, Xinqiang Wang^b,*, Zhigang Zhang^a, Yadong Chen^a, and Shudong Liu^a

a School of Computer and Information Engineering, Tianjin Chengjian University, Tianjin, 300384, China
b School of Software and Communication, Tianjin Sino-German University of Applied Sciences, Tianjin, 300350, China

Submitted on ;
Contact: * E-mail address: waffchiang@163.com
About author:Guoyan Li received her M.S degree and Ph.D. in computer applications from Hebei University of Technology in 2009 and 2013, respectively. Her research interests include future internet architecture, network function virtualization, and software-defined networking. Email: ligy@tcu.edu.cn Xinqiang Wang received his M.S. degree from Nankai University in 2009. He is currently pursuing a Ph.D. in the School of Software at Tianjin University. His research interests include network optimization and routing in highly dynamic networks. Email: waffchiang@163.com Zhigang Zhang received his M.S. degree in software engineering from Nankai University in 2005 and his Ph.D. in computer applications from Tianjin University of Technology in 2017. He is currently an associate professor at Tianjin Chengjian University. His research interests include internet architecture, network function virtualization, and network optimization. Email: zzg@tcu.edu.cn Yadong Chen received her M.S. degree in computer applications from Chang'an University in 2003. She is currently an associate professor at Tianjin Chengjian University. Her research interests include network function virtualization and network optimization. Email: cyd@tcu.edu.cn Shudong Liu received his Ph.D. degree from Harbin Institute of Technology in 2001. He is currently a professor at Tianjin Chengjian University. His research interests include communication technology and Internet of things technology. Email: lsd@tcu.edu.cn
Supported by:
This work was partially supported by the Project of Natural Science Foundation of Tianjin (No. 17JCQNJC00500), the Tianjin Educational Science Project Planning for 13th Five-year (No. HE3045), the Fund for the Development of Science and Technology of Tianjin Education Committee (No. 2018KJ174), and the Project of Tianjin Science and Technology (No. 18JCTPJC61800).

Abstract

Abstract: In order to solve the problem that traditional load balancing technology lacks sufficient scalability and flexibility, we propose a dynamic and scalable load balancing scheme based on fuzzy logic for datacenter networks using the SDN architecture characteristics of control and forwarding separation, named LBSFL. The main parameters affecting the server load performance are analyzed and used as the input variables of fuzzy logic system to evaluate the server load, and then SDN controller schedules current network requests to achieve server load balancing. Additionally, we take into account the issue of server activation and deactivation under various traffic loads in this scheme. The experimental results show that the response time of the system can be increased by about 15% compared with LBBSRT, and it can also maintain the system load between the lower (30%) and normal (50%) boundaries. The scheme can greatly improve the load balance of servers under the premise of guaranteeing the network performance.

Key words: software-defined networking, load balancing scheme, fuzzy logic

Guoyan Li, Xinqiang Wang, Zhigang Zhang, Yadong Chen, and Shudong Liu. A Scalable Load Balancing Scheme for Software-Defined Datacenter Networks based on Fuzzy Logic [J]. Int J Performability Eng, 2019, 15(8): 2217-2227.

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A Scalable Load Balancing Scheme for Software-Defined Datacenter Networks based on Fuzzy Logic

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