A Novel Adaptive Optimization of Intragrated Network Topology and Transmission Path for IoT System

The Internet of Things (IoT) is currently the emerging trend in network applications. The core component is the network layer in the IoT system. There are already some existing improvements, most of them are focused either on the transmission path or on the network topology. We have previously desig...

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Veröffentlicht in:IEEE sensors journal 2019-08, Vol.19 (15), p.6452-6459
Hauptverfasser: Jong, Gwo-Jia, Wang, Zhi-Hao, Hendrick, Hsieh, Kai-Sheng, Horng, Gwo-Jiun
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Sprache:eng
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Zusammenfassung:The Internet of Things (IoT) is currently the emerging trend in network applications. The core component is the network layer in the IoT system. There are already some existing improvements, most of them are focused either on the transmission path or on the network topology. We have previously designed the Queen Honey Bee Migration (QHBM) algorithm which is a new method for solving routing and transmission path. In this paper, we further improve both the transmission path and the network topology at the same time. The authors designed two novel adaptive models to solve the optimization of networking. We employed the Adaptive Model of Network Topology (AMNT) based on the QHBM algorithm to optimize the repeater; moreover, we also used the probability model to design Adaptive Model of Transmission Path (AMTP) to optimize the end-device. It allows the access point (AP) in the network to perform transmission path transfer or network topology reorganization according to the specified conditions. We evaluated two network performance parameters: transmission time and packet loss rate. The control mode maintains a conventional mode and does not change the existing network topology or transmission path with any factors. The experimental mode performs according to the novel adaptive integrated network topology and the transmission path for the IoT system, thus this system will operate according to the setting of the environment with the signal interference source generated by a random process method. We found that in laboratory testing, compared to conventional mode, the network performance of the novel integrated network topology and the transmission path for the IoT system has been increased by AMNT and AMTP. The performance index of the transmission time increased by 70.6±11%, and the performance index of the packet loss rate increased by 84 ± 38%. We conclude that our novel adaptive optimization of integrated network topology and the transmission path for the IoT system is practically applicable and has achieved encouraging result in terms of IoT performance. We hope for a wide application of this novel design on the networking of the IoT in the future.
ISSN:1530-437X
1558-1748
DOI:10.1109/JSEN.2019.2908702