Estimating SDN traffic matrix based on online adaptive information gain maximization method

  • Dongyang Li
  • Changyou Xing
  • Ningyun Dai
  • Fei Dai
  • Guomin Zhang
Part of the following topical collections:
  1. Special Issue on Software Defined Networking: Trends, Challenges and Prospective Smart Solutions


Traffic Matrix (TM) estimation is important for network management and traffic engineering. However, current estimation methods are insufficient in estimation accuracy and measurement cost. In this paper, by using the flow measurement capability in Software Defined Networks (SDN), we propose an Online Information Gain Maximization based SDN traffic matrix estimation method IGME. IGME uses the information gain metric to determine which flows are most informative, and then constructs the measurement flow set iteratively until the accuracy requirement is satisfied or the measurement resource constraint is reached. The experiment results on three Internet measurement datasets show that IGME can improve the estimation accuracy only by consuming a small amount of measurement resource. Besides, the iteration feature of IGME provides a means to dynamically adjust the measurement flow selection choice, so as to adapt to the time-varying characteristics of the network traffic.


Traffic matrix estimation Software defined networking Information entropy OpenFlow 



We wish to express our great thanks for the discussion with Dr. Marco Polverini. This research was supported by a research grant from the National Basic Research Program of China (973 Program) under Grant No.2012CB315806, the China PostDoctoral Science Foundation under Grant No. 2017 M610286, the National Natural Science Foundation of China under Grant No. 61379149, and the Natural Science Foundation of Jiangsu under Grant No. BK20140070.


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© Springer Science+Business Media, LLC, part of Springer Nature 2018

Authors and Affiliations

  • Dongyang Li
    • 1
  • Changyou Xing
    • 1
  • Ningyun Dai
    • 1
  • Fei Dai
    • 1
  • Guomin Zhang
    • 1
  1. 1.College of Command Control EngineeringArmy Engineering University of PLANanjingChina

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