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Design and analysis of a novel collision notification scheme for IoT environments

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Abstract

This paper is the first one that reveals two potential problems in CSMA/CN and proposes an adaptive collision notification (ACN) to solve them. The famous CSMA/CN (collision notification) protocol can detect the ongoing transmission collision early and use CN feedback to inform the sender to abort its transmission immediately, thereby improving the channel utilization. However, there are two potential problems in CN: (a) CN cross-boundary, namely the CN feedback might be later than a standard transmission, and (b) CN interference, namely the CN feedback might interfere with other links. To solve the above problems, in ACN, we design a generalized CN structure and a flexible CN feedback mechanism. The receiver will determine whether to send CN feedback by the collision occurring position for solving the problem (a) and select the transmission power and length of the CN feedback by the interference range for solving the problem (b). We also theoretically quantify the transmission opportunity and power of the CN feedback. We compared ACN and standard CSMA/CN through simulation experiments. Extensive simulations verify that ACN can solve both problems and significantly improve the system throughput, while CSMA/CN will have low throughput due to both problems. Therefore, the design of ACN is an extension of the standard CSMA/CN, which can help wireless network engineers to optimize CSMA/CN network deployment.

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Data availability

The data used to support the findings of this study are available from the corresponding author upon request.

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Acknowledgements

This work is funded in part by the National Natural Science Foundation of China (File Nos. 61872451 and 61872452), in part by the Science and Technology Development Fund, Macau SAR (File Nos. 0098/2018/A3, 0037/2020/A1, and 0062/2020/A2).

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Authors and Affiliations

  1. Faculty of Information Technology, Macau University of Science and Technology, Avenida Wei Long, Taipa, Macau, China

    Fangxin Xu, Li Feng, Jie Yang & Hong Liang

  2. Department of Information Management, Yu Da University of Science and Technology, Miaoli, 36143, Taiwan

    Yu-Teng Chang

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  1. Fangxin Xu
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Correspondence to Li Feng.

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Xu, F., Feng, L., Yang, J. et al. Design and analysis of a novel collision notification scheme for IoT environments. J Supercomput 78, 18130–18152 (2022). https://doi.org/10.1007/s11227-022-04585-2

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