Bidirectional Matching Strategy for Multi-Controller Deployment in Distributed Software Defined Networking

Tao Hu, Peng Yi, Zehua Guo, Julong Lan, Jianhui Zhang

Research output: Contribution to journalArticlepeer-review

17 Scopus citations

Abstract

Software defined networking (SDN) realizes the full decoupling between control plane and data plane, and it could effectively simplify network management and promote network innovation. In the large SDN network, there are the single point of failure and the lack of control resources for one centralized SDN controller, so several researchers have presented deploying multi-controller to improve the reliability and scalability of the network. However, unreasonable deployment of multiple controllers may cause the unbalanced distribution of controller loads, and it is harmful to the network stability. In order to address the above problems, this paper proposes bidirectional matching strategy (BMS) and designs its corresponding algorithm to implement multi-controller deployment. First, through collecting the information of hops, delay, and traffic in the network, we build the matching lists of switches and controllers, respectively. Then, according to the specific sequencing of elements in the matching lists, we design a mutual selection strategy that the switch and controller will select the optimal elements from its list to implement matching in turns until realizing the construction of the distributed network. Meanwhile, we implement the strict mathematical derivation to demonstrate the feasibility of BMS. Finally, simulation shows that BMS can achieve the better multi-controller deployment when compared with the existing algorithms.

Original languageEnglish (US)
Pages (from-to)14946-14954
Number of pages9
JournalIEEE Access
Volume6
DOIs
StatePublished - Jan 25 2018

Bibliographical note

Funding Information:
This work was supported in part by the Project of National Network Cyberspace Security under Grant 2017YFB0803204, in part by the National High-Tech Research and Development Program of China (863 Program) under Grant 2015AA016102, in part by the Foundation for Innovative Research Group of the National Natural Science Foundation of China under Grant 61521003, and in part by the Foundation for the National Natural Science Foundation of China under Grant 61502530.

Keywords

  • OpenFlow
  • Software defined networking
  • load balancing
  • matching
  • multi-controller

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