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Matching Model of Flow Table for Software-Defined Internet of Things

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Wireless Sensor Networks (CWSN 2018)

Part of the book series: Communications in Computer and Information Science ((CCIS,volume 984))

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Abstract

The heterogeneity of the IoT devices increases the difficulty of management. Software-defined Internet of Things (SD-IoT) provides a workable and practical paradigm for designing more efficient and flexible IoT. Matching strategy in the flow table of SD-IoT switches is most crucial. In this paper, we use a classification approach to analyze the structure of packets based on the tuple-space lookup mechanism, and propose a matching model of the flow table in SD-IoT switches by classifying packets based on a set of fields, which is called an F-OpenFlow. The experimental results show that the proposed F-OpenFlow effectively improves the utilization rate and matching efficiency of the flow table in SD-IoT switches.

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Acknowledgment

This research is supported in part by the grant from the National Natural Science Foundation of China (61572191 and 61672447), the Natural Science Foundation of Hunan Province (2018JJ4058).

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Authors and Affiliations

  1. Key Laboratory of Internet of Things Technology and Application, College of Information Science and Engineering, Hunan Normal University, Changsha, 410081, China

    Yiheng Su, Ting Peng, Xiaoxun Zhong & Lianming Zhang

Authors
  1. Yiheng Su
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  2. Ting Peng
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  3. Xiaoxun Zhong
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  4. Lianming Zhang
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Corresponding author

Correspondence to Lianming Zhang .

Editor information

Editors and Affiliations

  1. Kunming University, Kunming, China

    Shikai Shen

  2. Kunming University, Kunming, China

    Kaiguo Qian

  3. Kunming University, Kunming, China

    Shaojun Yu

  4. Yunnan Nationalities University, Kunming, China

    Wu Wang

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Su, Y., Peng, T., Zhong, X., Zhang, L. (2019). Matching Model of Flow Table for Software-Defined Internet of Things. In: Shen, S., Qian, K., Yu, S., Wang, W. (eds) Wireless Sensor Networks. CWSN 2018. Communications in Computer and Information Science, vol 984. Springer, Singapore. https://doi.org/10.1007/978-981-13-6834-9_5

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  • DOI: https://doi.org/10.1007/978-981-13-6834-9_5

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  • Publisher Name: Springer, Singapore

  • Print ISBN: 978-981-13-6833-2

  • Online ISBN: 978-981-13-6834-9

  • eBook Packages: Computer ScienceComputer Science (R0)

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