R-learning- based team game model for Internet of things quality-of-service control scheme

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초록

In modern times, it has been observed that Internet of things technology makes it possible for connecting various smart objects together through the Internet. For the effective Internet of things management, it is necessary to design and develop service models that ensure appropriate level of quality-of-service. Therefore, the design of quality-of-service management schemes has been a hot research issue. In this work, we formulate a new quality-of-service management scheme based on the IoT system power control algorithm. Using the emerging and largely unexplored concept of the Rlearning algorithm and docitive paradigm, system agents can teach other agents how to adjust their power levels while reducing computation complexity and speeding up the learning process. Therefore, our proposed power control approach can provide the ability to practically respond to current Internet of things system conditions and suitable for real wireless communication operations. Finally, we validate the introduced concept and confirm the effectiveness of the proposed scheme in comparison with the existing schemes through extensive simulation analysis.

키워드

R-learningpower control algorithmInternet of thingsteam game modeldocitive network paradigminteractive mechanism
제목
R-learning- based team game model for Internet of things quality-of-service control scheme
저자
Kim, Sungwook
DOI
10.1177/1550147716687558
발행일
2017-01
유형
Article
저널명
International Journal of Distributed Sensor Networks
13
1