An Adaptive and Lightweight Update Mechanism for SDN

Changhe Yu, Julong Lan, Zehua Guo, Yuxiang Hu, Thar Baker

Research output: Contribution to journalArticlepeer-review

8 Scopus citations

Abstract

To improve the network resources utilization and the quality of service, the provision of an adaptive and customizable network service is deemed a feasible approach. In this paper, based on the quality of service (QoS)-aware traffic classification and real-time network status, an adaptive update mechanism is presented to change the traditional rigid update techniques in software-defined networking. The developed update mechanism aims at abstracting the common update mechanism into update operations and calculates the update sequence on the operation granularity. The mechanism has three work modes, and each mode has a corresponding algorithm. It can adjust the work modes adaptively based on the network condition and the flow QoS requirements to improve the performance. The experimental results demonstrate that the three work modes can achieve optimal performance in ternary content addressable memory (TCAM) overhead reduction, delay, and bandwidth consumption, respectively. For example, when the tri-fusion work mode is leveraged, it provides at least an 85% reduction of the additional TCAM overhead and improves by at least 9%, 65%, and 82% compared to other work modes and the compared algorithms.

Original languageEnglish (US)
Article number8624382
Pages (from-to)12914-12927
Number of pages14
JournalIEEE Access
Volume7
DOIs
StatePublished - 2019

Bibliographical note

Funding Information:
This work was supported in part by the National Natural Science Foundation of China under Grant 61872382, and in part by the National Natural Science Foundation of China under Grant 61802429.

Keywords

  • SDN
  • adaptive mechanism
  • network update

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