TIIS (한국인터넷정보학회)
Current Result Document :
| 한글제목(Korean Title) |
A Learning-based Power Control Scheme for Edge-based eHealth IoT Systems |
| 영문제목(English Title) |
A Learning-based Power Control Scheme for Edge-based eHealth IoT Systems |
| 저자(Author) |
Haoru Su
Xiaoming Yuan
Yujie Tang
Rui Tian
Enchang Sun
Hairong Yan
|
| 원문수록처(Citation) |
VOL 15 NO. 12 PP. 4385 ~ 4399 (2021. 12) |
한글내용
(Korean Abstract) |
|
영문내용
(English Abstract) |
The Internet of Things (IoT) eHealth systems composed by Wireless Body Area Network (WBAN) has emerged recently. Sensor nodes are placed around or in the human body to collect physiological data. WBAN has many different applications, for instance health monitoring. Since the limitation of the size of the battery, besides speed, reliability, and accuracy; design of WBAN protocols should consider the energy efficiency and time delay. To solve these problems, this paper adopt the end-edge-cloud orchestrated network architecture and propose a transmission based on reinforcement algorithm. The priority of sensing data is classified according to certain application. System utility function is modeled according to the channel factors, the energy utility, and successful transmission conditions. The optimization problem is mapped to Q-learning model. Following this online power control protocol, the energy level of both the senor to coordinator, and coordinator to edge server can be modified according to the current channel condition. The network performance is evaluated by simulation. The results show that the proposed power control protocol has higher system energy efficiency, delivery ratio, and throughput. |
| 키워드(Keyword) |
IoT
eHealth
Body Area Networks
power control
low energy
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| 파일첨부 |
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