Journal of Systems Engineering and Electronics ›› 2019, Vol. 30 ›› Issue (5): 974-984.doi: 10.21629/JSEE.2019.05.14

• Systems Engineering • Previous Articles     Next Articles

MTSS: multi-path traffic scheduling mechanism based on SDN

Xiaolong XU1,*(), Yun CHEN2(), Liuyun HU3(), Anup KUMAR4()   

  1. 1 Jiangsu Key Laboratory of Big Data Security & Intelligent Processing, Nanjing University of Posts and Telecommunications, Nanjing 210023, China
    2 Institute of Big Data Research at Yancheng, Nanjing University of Posts and Telecommunications, Yancheng 224000, China
    3 School of Computer Science, Nanjing University of Posts and Telecommunications, Nanjing 210023, China
    4 Department of Computer Engineering and Computer Science, University of Louisville, Louisville KY40292, USA
  • Received:2018-07-17 Online:2019-10-08 Published:2019-10-09
  • Contact: Xiaolong XU E-mail:xuxl@njupt.edu.cn;1215043122@njupt.edu.cn;1216043127@njupt.edu.cn;anup.kumar@louisville.edu
  • About author:XU Xiaolong was born in 1977. He received his B.S. degree in computer and its applications, M.S. degree in computer software and theories and Ph.D. degree in communications and information systems from Nanjing University of Posts & Telecommunications, Nanjing, China, in 1999, 2002 and 2008, respectively. He worked as a postdoctoral researcher at Station of Electronic Science and Technology, Nanjing University of Posts & Telecommunications from 2011 to 2013. He is currently a professor in College of Computer, Nanjing University of Posts & Telecommunications. He is a senior member of China Computer Federation. His current research interests include cloud computing and big data, mobile computing, intelligent agent and information security. E-mail: xuxl@njupt.edu.cn|CHEN Yun was born in 1990. He received his B.E. degree in communication engineering from Jiangsu University of Science and Technology, Zhenjiang, China, in 2015. He works as an engineer in Institute of Big Data Research at Yancheng, China, carrying out research in cloud computing and software defined networking. E-mail: 1215043122@njupt.edu.cn|HU Liuyun was born in 1992. He received his B.E. degree in software engineering from Nanjing University of Posts & Telecommunications, Nanjing, China, in 2016. He is now a graduate student at School of Computer Science, Nanjing University of Posts & Telecommunications, carrying out research in cloud computing and software defined networking. E-mail: 1216043127@njupt.edu.cn|KUMAR Anup was born in 1963. He received his Ph.D. degree in Electrical and Computer Engineering Department, North Carolina State University, Raleigh, NC, in 2006. He is currently a professor and the director of Mobile Information Network and Distributed Systems Lab, Computer Engineering and Computer Science Department, University of Louisville, Louisville, USA. His current research interests include cloud computing and big data. E-mail: anup.kumar@louisville.edu
  • Supported by:
    the National Key Research and Development Program of China(2018YFB1003702);the National Natural Science Foundation of China(61472192);the Scientific and Technological Support Project (Society) of Jiangsu Province(BE2016776);This work was supported by the National Key Research and Development Program of China (2018YFB1003702), the National Natural Science Foundation of China (61472192), and the Scientific and Technological Support Project (Society) of Jiangsu Province (BE2016776)

Abstract:

Large-scale and diverse businesses based on the cloud computing platform bring the heavy network traffic to cloud data centers. However, the unbalanced workload of cloud data center network easily leads to the network congestion, the low resource utilization rate, the long delay, the low reliability, and the low throughput. In order to improve the utilization efficiency and the quality of services (QoS) of cloud system, especially to solve the problem of network congestion, we propose MTSS, a multi-path traffic scheduling mechanism based on software defined networking (SDN). MTSS utilizes the data flow scheduling flexibility of SDN and the multi-path feature of the fat-tree structure to improve the traffic balance of the cloud data center network. A heuristic traffic balancing algorithm is presented for MTSS, which periodically monitors the network link and dynamically adjusts the traffic on the heavy link to achieve programmable data forwarding and load balancing. The experimental results show that MTSS outperforms equal-cost multi-path protocol (ECMP), by effectively reducing the packet loss rate and delay. In addition, MTSS improves the utilization efficiency, the reliability and the throughput rate of the cloud data center network.

Key words: cloud data center, software defined networking (SDN), load balancing, multi-path transmission, OpenFlow