18435969. OPTIMAL AP CONNECTION METHOD AND SYSTEM USING REINFORCEMENT LEARNING TO IMPROVE ENERGY EFFICIENCY AND LATENCY OF IoT DEVICES (KOREA ADVANCED INSTITUTE OF SCIENCE AND TECHNOLOGY)

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OPTIMAL AP CONNECTION METHOD AND SYSTEM USING REINFORCEMENT LEARNING TO IMPROVE ENERGY EFFICIENCY AND LATENCY OF IoT DEVICES

Organization Name

KOREA ADVANCED INSTITUTE OF SCIENCE AND TECHNOLOGY

Inventor(s)

Oh Hyeontaek of Daejeon (KR)

Lee Seung Jin of Daejeon (KR)

Park Jaeeun of Daejeon (KR)

Choi Hyungwoo of Daejeon (KR)

Lee Chanhyung of Daejeon (KR)

Choi Junkyun of Daejeon (KR)

OPTIMAL AP CONNECTION METHOD AND SYSTEM USING REINFORCEMENT LEARNING TO IMPROVE ENERGY EFFICIENCY AND LATENCY OF IoT DEVICES

This abstract first appeared for US patent application 18435969 titled 'OPTIMAL AP CONNECTION METHOD AND SYSTEM USING REINFORCEMENT LEARNING TO IMPROVE ENERGY EFFICIENCY AND LATENCY OF IoT DEVICES



Original Abstract Submitted

Disclosed is an optimal AP connection method including transmitting, by an IoT device, a probe request message to a plurality of iAPs; transmitting, by each of the plurality of iAPs that receives the probe request message, the probe request message to an iAP controller and transmitting local information to each iAP to the iAP controller; performing, by the iAP controller, reinforcement learning for IoT device using global information that is updated from the local information; selecting, by the iAP controller, an optimal iAP based on RL reinforcement learning and transmitting recommended Tx power value information on the IoT device and a probe response message to the selected corresponding iAP; and transmitting, by the corresponding iAP that receives its selection as the optimal iAP in response to the probe request from the iAP controller, the probe response message and the recommended Tx power value information to the IoT device.