Youngchan Lee, SoYeon Lee, Dae-Young Kim, Journal of Internet Computing and Services, Vol. 20, No. 5, pp. 95-104, Oct. 2019
10.7472/jksii.2019.20.5.95, Full Text:
Keywords: Internet of Things, WiFi, Feed Forward Neural Network, Access point, Network Control

Abstract

Various kinds of devices are used for the Internet of Things (IoT) service, and IoT devices mainly use communication technology that uses the frequency of the unlicensed band. There are several types of communication technology in the unlicensed band, but WiFi is most commonly used. Devices used for IoT services vary in computing resources from devices with limited capabilities to smartphones and provide services over wireless networks such as WiFi. Most IoT devices can't perform complex operations for network control, thus they choose a WiFi access point (AP) based on signal strength. This causes a decrease in IoT service efficiency. In this paper, an intelligent AP system that can efficiently control the WiFi connection of the IoT devices is implemented. Based on the network information measured by the IoT device, the access point learns using a feed forward neural network algorithm, and predicts a network connection state to control the WiFi connection. By controlling the WiFi connection at the AP, the service efficiency of the IoT device can be improved.

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