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Channel List Selection Based on Quality Prediction in WirelessHART Networks

  • Research paper
  • Published:
Journal of Communications and Information Networks

Abstract

WirelessHART is one of the most widely used technologies in industrial wireless networks. However, its performance is highly influenced by the quality of wireless channels. To improve the reliability of wireless communications, WirelessHART employs channel blacklisting and channel hopping mechanisms, which highlights the importance of channel assessment. Traditional methods generally resort to packet reception ratio (PRR) of the previous time slot to assess and allocate channels, but this is not accurate. In this paper, we propose a learning-based framework for predicting the PRR, and on the basis of the predicted PRR, we develop a heuristic channel selection algorithm to confirm the channel list, which takes into account the balance of channel diversity and route diversity. Simulation results demonstrate that our algorithm outperforms existing ones in terms of achieved reliability.

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Authors and Affiliations

  1. Southeast University, Nanjing, 210096, China

    Gongpu Chen, Rui Ma, Mengdan Lei & Xianghui Cao

Authors
  1. Gongpu Chen
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  2. Rui Ma
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  3. Mengdan Lei
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  4. Xianghui Cao
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Corresponding author

Correspondence to Rui Ma.

Additional information

This work was supported in part by the National Natural Science Foundation of China (No. 61573103), the State Key Laboratory of Synthetical Automation for Process Industries, and the Fundamental Research Funds for the Central Universities. The associate editor coordinating the review of this paper and approving it for publication was X. Cheng.

Gongpu Chen received his B.S. degree in automation engineering from University of Electronic Science and Technology of China, Chengdu, China, in 2016. He is currently working towards his M.S. degree in Control Science and Engineering in Southeast University, Nanjing, China. His research interests include cyber physical system and network resource allocation.

Rui Ma [corresponding author] received her B.S. degree in automation engineering from Nanjing University of Aeronautics and Astronautics, Nanjing, China, in 2016. She is currently working towards her M.S. degree in Control Science and Engineering in Southeast University, Nanjing, China. Her research interests include machine learning and network scheduling.

Mengdan Lei received her B.S. degree in electrical engineering and automation from Soochow University of Rail Transportation, Suzhou, China, in 2017. She is currently working towards her M.S. degree in Control Science and Engineering in Southeast University, Nanjing, China. Her research interests include cyber physical system and network security.

Xianghui Cao (S’08-M’11-SM’16) received his B.S. and Ph.D. degrees in control science and engineering from Zhejiang University, Hangzhou, China, in 2006 and 2011, repectively. From 2012 to 2015, he was a Senior Research Associate with the Department of Electrical and Computer Engineering, Illinois Institute of Technology, Chicago, IL, USA. He is currently an Associate Professor with the School of Automation, Southeast University, Nanjing, China. His current research interests include cyber-physical systems, wireless network performance analysis, wireless networked control, and network security. Dr. Cao was a recipient of the Best Paper Runner-Up Award of ACM MobiHoc14. He also serves as an Associate Editor for several journals, including Acta Auromatica Sinica, IEEE/CAA Journal of Automatica Sinica, KSII Transactions on Internet and Information Systems, Security and Communication Networks, and International Journal of Ad Hod and Ubiquitous Computing. He served as the Publicity Co-Chair for ACM MobiHoc15, the Symposium Co-Chair for ICNC17 and IEEE/CIC ICCC15, and has been a TPC member for a number of conferences.

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Chen, G., Ma, R., Lei, M. et al. Channel List Selection Based on Quality Prediction in WirelessHART Networks. J. Commun. Inf. Netw. 3, 49–56 (2018). https://doi.org/10.1007/s41650-018-0030-5

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  • DOI: https://doi.org/10.1007/s41650-018-0030-5

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