An IoT and machine learning-based routing protocol for reconfigurable engineering application

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Abstract

With new telecommunications engineering applications, the cognitive radio (CR) network-based internet of things (IoT) resolves the bandwidth problem and spectrum problem. However, the CR-IoT routing method sometimes presents issues in terms of road finding, spectrum resource diversity and mobility. This study presents an upgradable cross-layer routing protocol based on CR-IoT to improve routing efficiency and optimize data transmission in a reconfigurable network. In this context, the system is developing a distributed controller which is designed with multiple activities, including load balancing, neighbourhood sensing and machine-learning path construction. The proposed approach is based on network traffic and load and various other network metrics including energy efficiency, network capacity and interference, on an average of 2 bps/Hz/W. The trials are carried out with conventional models, demonstrating the residual energy and resource scalability and robustness of the reconfigurable CR-IoT.

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CITATION STYLE

APA

Natarajan, Y., Srihari, K., Dhiman, G., Chandragandhi, S., Gheisari, M., Liu, Y., … Alharbi, H. F. (2022). An IoT and machine learning-based routing protocol for reconfigurable engineering application. IET Communications, 16(5), 464–475. https://doi.org/10.1049/cmu2.12266

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