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Dynamic Load Balancing for Software-Defined Data Center Networks

  • Yun Chen
  • Weihong Chen
  • Yao Hu
  • Lianming ZhangEmail author
  • Yehua Wei
Conference paper
Part of the Lecture Notes of the Institute for Computer Sciences, Social Informatics and Telecommunications Engineering book series (LNICST, volume 201)

Abstract

In recent years, along with the increasing demand for cloud services, the network traffic is increased inside data center networks (DCNs). The inherent defects of TCP/IP network architecture have hindered the development of network technologies for a long time, and the software-defined network (SDN) has recently gained unprecedented attention from industry and research communities, and it has completely overturned the existing network architecture. In this paper, we have proposed a new network frame for software-defined data center network (SDDCN), and developed a dynamic schedule strategy of the network traffic by calculating available path coefficient of the SDDCN, then presented a schedule algorithm for the dynamic load balancing (SDLB) based on the path coefficient of network available bandwidth in real-time, and developed the components of the Ryu controller of the SDDCN, which is responsible for running the SDLB algorithm. Based on Mininet platform, the experimental results show that the SDLB algorithm has better performance of dynamic load balancing in the SDDCN, which has provided an effective solution for the load balancing of the existing DCNs.

Keywords

Software-defined data center network Load balancing Path coefficient 

Notes

Acknowledgment

This research is supported in part by the grant from the National Natural Science Foundation of China (61572191 and 61402170), the Hunan Provincial Science and Technology Program Project of China (No. 2013FJ4051), and the Hunan Provincial Education Department Scientific Research Fund of China (No. 13B065).

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Copyright information

© ICST Institute for Computer Sciences, Social Informatics and Telecommunications Engineering 2017

Authors and Affiliations

  • Yun Chen
    • 1
  • Weihong Chen
    • 1
  • Yao Hu
    • 1
  • Lianming Zhang
    • 1
    Email author
  • Yehua Wei
    • 1
  1. 1.Key Laboratory of Internet of Things Technology and Application, College of Physics and Information ScienceHunan Normal UniversityChangshaChina

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