Data Traffic Reduction in Wireless Internet of Things Using Deep Compressive Sensing and Reconstruction Algorithm

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Hemant Rajoriya
Ritesh Sadiwala

Abstract

Companies across a wide variety of sectors are rapidly moving to IoT to boost productivity, understand better clients in order to provide better customer service, enhance decision-making, and maximize the profitability of their businesses. But having these advantages, there is a drawback in using this technology, that large amount of data transmission creates congestion or traffic inside the network thus to reduces such drawback the technique namely compressed sensing was used. This paper reviews the Internet of things (IoT), traffic or congestion in the network, compressed sensing.

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How to Cite
Rajoriya, H., & Sadiwala, R. (2023). Data Traffic Reduction in Wireless Internet of Things Using Deep Compressive Sensing and Reconstruction Algorithm. SAMRIDDHI : A Journal of Physical Sciences, Engineering and Technology, 15(01), 182-185. https://doi.org/10.18090/10.18090/samriddhi.v15i01.32
Section
Review Article

References

[1] J. Liang, L. Li and C. Zhao, “A Transfer Learning Approach for Compressed Sensing in 6G-IoT,” in IEEE Internet of Things Journal, vol. 8, no. 20, pp. 15276-15283, 15 Oct.15, 2021, doi: 10.1109/JIOT.2021.3053088.
[2] Z. Zhang, Y. Liu, J. Liu, F. Wen and C. Zhu, “AMP-Net: DenoisingBased Deep Unfolding for Compressive Image Sensing,” in IEEE Transactions on Image Processing, vol. 30, pp. 1487-1500, 2021, doi: 10.1109/TIP.2020.3044472.
[3] B. Jiang, G. Huang, F. Li and S. Zhang, “Compressed Sensing With Dynamic Retransmission Algorithm in Lossy Wireless IoT,” in IEEE Access, vol. 8, pp. 133827-133842, 2020.
[4] C. Zhang, O. Li, Y. Yang, G. Liu, and X. Tong, ‘‘Energy-efficient data gathering algorithm relying on compressive sensing in lossy WSNs,’’ Measurement, vol. 147, Dec. 2019, Art. no. 106875.
[5] J. Chen, N. Wang, D. Chen and J. Wan, “An Adaptive Dynamic Topology WSN Data Collection Method Based on Compressive Sensing,” 2018 2nd IEEE Advanced Information Management,C ommunicates,Electronic and Automation Control Conference (IMCEC), 2018, pp. 1376-1379, doi: 10.1109/IMCEC.2018.8469 397.
[6] G. Ramachandra and M. S. Bhat, “Compressed Sensing for Energy and Bandwidth Starved IoT Applications,” 2018 IEEE Distributed Computing, VLSI, Electrical Circuits and Robotics (DISCOVER), 2018, pp. 131-134, doi: 10.1109/DISCOVER.2018.8674107.
[7] X. Sun, X. Gao and C. Li, “A joint abnormal event detection scheme based on compressed sensing for Internet of Things,” 2016 16th International Symposium on Communications
and Information Technologies (ISCIT), 2016, pp. 509-513, doi: 10.1109/ISCIT.2016.7751684.
[8] Satish Kumar Nalluri, Venkata Krishna Bharadwaj Parasaram, Varun Teja Bathini. (2020). Secure Automation Frameworks for Smart Manufacturing Using Blockchain-Assisted Traceability.
International Journal of Research & Technology, 8(2), 47–53.
Retrieved from https://ijrt.org/j/article/view/879
[9] Y. Chen, W. Liu, T. Wang, Q. Deng, A. Liu, and H. Song, ‘‘An adaptive retransmit mechanism for delay differentiated services in industrial WSNs,’’ EURASIP J. Wireless Commun. Netw., vol.
2019, no. 1, p. 258, Dec. 2019.
[10] H. Kim, J. Ahn and H. Nam, “Wideband spectrum sensing using low-power IoT device,” 2020 International Conference on Information and Communication Technology Convergence
(ICTC), 2020, pp. 424-426, doi: 10.1109/ICTC49870.2020.9289566.
[11] M. Amarlingam, P. K. Mishra, K. V. V. Durga Prasad and P.
Rajalakshmi, “Compressed sensing for different sensors: A real scenario for WSN and IoT,” 2016 IEEE 3rd World Forum on Internet of Things (WF-IoT), 2016, pp. 289-294, doi: 10.1109/ WF-IoT.2016.7845487.
[12] M. Shaban and A. Abdelgawad, “A study of distributed compressive sensing for the Internet of Things (IoT),” 2018 IEEE 4th World Forum on Internet of Things (WF-IoT), 2018, pp. 173178, doi: 10.1109/WF-IoT.2018.8355095.