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애드혹 센서 네트워크 수명 연장을 위한 Q-러닝 기반 에너지 균등 소비 라우팅 프로토콜 기법
김기상 ( Kim Ki Sang ),김승욱 ( Kim Sung Wook ) 한국정보처리학회 2021 정보처리학회논문지. 컴퓨터 및 통신시스템 Vol.10 No.10
최근 스마트 센서는 다양한 환경에서 사용되고 있으며, 애드혹 센서 네트워크 (ASN) 구현에 대한 연구가 활발하게 진행되고 있다. 그러나 기존 센서 네트워크 라우팅 알고리즘은 특정 제어 문제에 초점을 맞추며 ASN 작업에 직접 적용할 수 없는 문제점이 있다. 본 논문에서는 Q-learning 기술을 이용한 새로운 라우팅 프로토콜을 제안하는데, 제안된 접근 방식의 주요 과제는 균형 잡힌 시스템 성능을 확보하면서 효율적인 에너지 할당을 통해 ASN의 수명을 연장하는 것이다. 제안된 방법의 특징은 다양한 환경적 요인을 고려하여 Q-learning 효과를 높이며, 특히 각 노드는 인접 노드의 Q 값을 자체 Q 테이블에 저장하여 데이터 전송이 실행될 때마다 Q 값이 업데이트되고 누적되어 최적의 라우팅 경로를 선택하는 것이다. 시뮬레이션 결과 제안된 방법이 에너지 효율적인 라우팅 경로를 선택할 수 있으며 기존 ASN 라우팅 프로토콜에 비해 우수한 네트워크 성능을 얻을 수 있음을 확인하였다. Recently, smart sensors are used in various environments, and the implementation of ad-hoc sensor networks (ASNs) is a hot research topic. Unfortunately, traditional sensor network routing algorithms focus on specific control issues, and they can’t be directly applied to the ASN operation. In this paper, we propose a new routing protocol by using the Q-learning technology, Main challenge of proposed approach is to extend the life of ASNs through efficient energy allocation while obtaining the balanced system performance. The proposed method enhances the Q-learning effect by considering various environmental factors. When a transmission fails, node penalty is accumulated to increase the successful communication probability. Especially, each node stores the Q value of the adjacent node in its own Q table. Every time a data transfer is executed, the Q values are updated and accumulated to learn to select the optimal routing route. Simulation results confirm that the proposed method can choose an energy-efficient routing path, and gets an excellent network performance compared with the existing ASN routing protocols.
김기상(Ki-sang Kim),김민규(Min-gyu Kim),이상용(Sang-yong Lee),이현륭(Hyun-ryung Lee),전충환(Chung-hwan Jeon) 한국에너지기후변화학회 2016 에너지기후변화학회지 Vol.11 No.1
The fuel characteristics, the combustion characteristics, and petrographic study of biomass samples that had been torrefied at 200~300 °C were investigated for wood pellets and empty fruit bunch (EFB). In the fuel characteristics, when higher torrefaction temperature was used, reduction of the yield, and increase in the calorie value, and decrease of volatile content were found. As a result, improvement of the fuel characteristics was confirmed. In the combustion characteristics, when the biomass was torrefied at 230 °C, each of the differential thermogravimetric analysis results was similar to the results that before torrefied. When comparing torrefied wood pellet with torrefied EFB at 230 °C, the torrefied EFB had higher combustion reactivity. This result was revealed to the petrographic result. Petrologically, wood pellet has thick wall structure, dense population, and few voids. On the other hand, EFB has thin wall structure, small size organic structure and many voids. Oxygen can more invade the biomass because of the thin wall structure and many voids. As a result, EFB had higher combustion reactivity.