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International Conference on Artificial Intelligence and Security

ICAIS 2022: Artificial Intelligence and Security pp 448–459Cite as

Review of Detection and Avoidance of Interference Among Multiple Applications in Software-Defined Networks

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Part of the book series: Lecture Notes in Computer Science ((LNCS,volume 13339))

Abstract

To provide better programmability, software-defined networks (SDN) separate the control plane and data plane. This feature facilitates the development of new network functions but brings new problems. There may be interference among multiple applications which are developed according to different requirements. SDN applications control the network by issuing flow tables, therefore interference among multiple applications may cause network failures. At present, many researchers are devoted to the correctness and reliability of SDN applications and have achieved a lot of valuable results. However, the existing reviews focus on the study of individual SDN applications, and there are few reviews of how to detect and avoid interference among multiple SDN applications. In this paper, we summarize the related works on interference among SDN multiple applications, which can be divided into two aspects: detecting interference and avoiding interference. Then we compare these works and conclude their advantages and disadvantages. Finally, we discuss the future research directions, such as automatic detection according to real-time network environment changes, and detection combining individual SDN application testing.

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Acknowledgement

This work was supported by the Hainan Provincial Natural Science Foundation of China (620RC562, 2019RC096, 620RC560), the Scientific Research Setup Fund of Hainan University (KYQD(ZR)1877), the Program of Hainan Association for Science and Technology Plans to Youth R&D Innovation (QCXM201910), and the National Natural Science Foundation of China (61802092, 62162021).

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Authors and Affiliations

  1. Hainan University, Haikou, 570228, China

    Jiangyuan Yao, Shengjun Lin, Chunxiang Xu, Min Jing, Deshun Li & Minrui Wang

  2. University of British Columbia, Vancouver, BC, V6T 1Z4, Canada

    Xingcan Cao

Authors
  1. Jiangyuan Yao
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  2. Shengjun Lin
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  3. Chunxiang Xu
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  4. Min Jing
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  5. Deshun Li
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  6. Minrui Wang
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  7. Xingcan Cao
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Corresponding author

Correspondence to Deshun Li .

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Editors and Affiliations

  1. Nanjing University of Information Science and Technology, Nanjing, China

    Xingming Sun

  2. Nanjing University of Information Science and Technology, Nanjing, China

    Xiaorui Zhang

  3. Jinan University, Guangzhou, China

    Zhihua Xia

  4. Purdue University, West Lafayette, IN, USA

    Elisa Bertino

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Yao, J. et al. (2022). Review of Detection and Avoidance of Interference Among Multiple Applications in Software-Defined Networks. In: Sun, X., Zhang, X., Xia, Z., Bertino, E. (eds) Artificial Intelligence and Security. ICAIS 2022. Lecture Notes in Computer Science, vol 13339. Springer, Cham. https://doi.org/10.1007/978-3-031-06788-4_38

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  • DOI: https://doi.org/10.1007/978-3-031-06788-4_38

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  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-031-06787-7

  • Online ISBN: 978-3-031-06788-4

  • eBook Packages: Computer ScienceComputer Science (R0)

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