RISS 학술연구정보서비스

검색
다국어 입력

http://chineseinput.net/에서 pinyin(병음)방식으로 중국어를 변환할 수 있습니다.

변환된 중국어를 복사하여 사용하시면 됩니다.

예시)
  • 中文 을 입력하시려면 zhongwen을 입력하시고 space를누르시면됩니다.
  • 北京 을 입력하시려면 beijing을 입력하시고 space를 누르시면 됩니다.
닫기
    인기검색어 순위 펼치기

    RISS 인기검색어

      KCI등재

      A Comparative Study and Analysis of LoRaWAN Performance in NS3

      한글로보기

      https://www.riss.kr/link?id=A108948031

      • 0

        상세조회
      • 0

        다운로드
      서지정보 열기
      • 내보내기
      • 내책장담기
      • 공유하기
      • 오류접수

      부가정보

      다국어 초록 (Multilingual Abstract) kakao i 다국어 번역

      Long Range Wide Area Network (LoRaWAN) is a widely adopted Internet of Things (IoT) protocol due to its high range and lower energy consumption. LoRaWAN utilizes Adaptive Data Rate (ADR) for efficient resource (e.g., spreading factor and transmission power) management. The ADR manages these two resource parameters on the network server side and end device side. This paper focuses on analyzing the ADR and Gaussian ADR performance of LoRaWAN. We have performed NS3 simulation under a static scenario by varying the antenna height. The simulation results showed that antenna height has a significant impact on the packet delivery ratio. Higher antenna height (e.g., 50 m) has shown an improved packet success ratio when compared with lower antenna height (e.g., 10 m) in static and mobility scenarios. Based on the results, it is suggested to use the antenna at higher allevation for successful packet delivery
      번역하기

      Long Range Wide Area Network (LoRaWAN) is a widely adopted Internet of Things (IoT) protocol due to its high range and lower energy consumption. LoRaWAN utilizes Adaptive Data Rate (ADR) for efficient resource (e.g., spreading factor and transmission...

      Long Range Wide Area Network (LoRaWAN) is a widely adopted Internet of Things (IoT) protocol due to its high range and lower energy consumption. LoRaWAN utilizes Adaptive Data Rate (ADR) for efficient resource (e.g., spreading factor and transmission power) management. The ADR manages these two resource parameters on the network server side and end device side. This paper focuses on analyzing the ADR and Gaussian ADR performance of LoRaWAN. We have performed NS3 simulation under a static scenario by varying the antenna height. The simulation results showed that antenna height has a significant impact on the packet delivery ratio. Higher antenna height (e.g., 50 m) has shown an improved packet success ratio when compared with lower antenna height (e.g., 10 m) in static and mobility scenarios. Based on the results, it is suggested to use the antenna at higher allevation for successful packet delivery

      더보기

      참고문헌 (Reference)

      1 A. Farhad, "R-ARM : Retransmission-Assisted Resource Management in LoRaWAN for the Internet of Things" 9 (9): 7347-7361, 2022

      2 A. Farhad, "Mobility-aware resource assignment to IoT applications in long-range wide area networks" 8 : 186111-186124, 2020

      3 A. Farhad, "Mobility Adaptive Data Rate Based on Kalman Filter for LoRa-Empowered IoT Applications" 321-324, 2023

      4 S. Corporation, "LoRaWAN® Mobile Applications: Blind ADR" 2019

      5 A. Farhad, "LoRaWAN Meets ML : A Survey on Enhancing Performance with Machine Learning" 23 (23): 1-36, 2023

      6 Moysiadis, V., "Extending ADR mechanism for LoRa enabled mobile end-devices" 113 (113): 2021

      7 Farhad, A., "Enhanced lorawan adaptive data rate for mobile internet of things devices" 20 (20): 1-21, 2020

      8 A. Farhad, "Enhanced LoRaWAN Adaptive Data Rate for Mobile Internet of Things Devices" 20 (20): 1-21, 2020

      9 N. Benkahla, "Enhanced ADR for LoRaWAN networks with mobility" 514-519, 2019

      10 J. Finnegan, "Analysis and Enhancement of the LoRaWAN Adaptive Data Rate Scheme" 7 (7): 7171-7180, 2020

      1 A. Farhad, "R-ARM : Retransmission-Assisted Resource Management in LoRaWAN for the Internet of Things" 9 (9): 7347-7361, 2022

      2 A. Farhad, "Mobility-aware resource assignment to IoT applications in long-range wide area networks" 8 : 186111-186124, 2020

      3 A. Farhad, "Mobility Adaptive Data Rate Based on Kalman Filter for LoRa-Empowered IoT Applications" 321-324, 2023

      4 S. Corporation, "LoRaWAN® Mobile Applications: Blind ADR" 2019

      5 A. Farhad, "LoRaWAN Meets ML : A Survey on Enhancing Performance with Machine Learning" 23 (23): 1-36, 2023

      6 Moysiadis, V., "Extending ADR mechanism for LoRa enabled mobile end-devices" 113 (113): 2021

      7 Farhad, A., "Enhanced lorawan adaptive data rate for mobile internet of things devices" 20 (20): 1-21, 2020

      8 A. Farhad, "Enhanced LoRaWAN Adaptive Data Rate for Mobile Internet of Things Devices" 20 (20): 1-21, 2020

      9 N. Benkahla, "Enhanced ADR for LoRaWAN networks with mobility" 514-519, 2019

      10 J. Finnegan, "Analysis and Enhancement of the LoRaWAN Adaptive Data Rate Scheme" 7 (7): 7171-7180, 2020

      11 D. Y. Kim, "Adaptive data rate control in low power wide area networks for long range IoT services" 22 : 171-178, 2017

      12 R. Kufakunesu, "A survey on adaptive data rate optimization in lorawan : Recent solutions and major challenges" 20 (20): 1-25, 2020

      더보기

      분석정보

      View

      상세정보조회

      0

      Usage

      원문다운로드

      0

      대출신청

      0

      복사신청

      0

      EDDS신청

      0

      동일 주제 내 활용도 TOP

      더보기

      주제

      연도별 연구동향

      연도별 활용동향

      연관논문

      연구자 네트워크맵

      공동연구자 (7)

      유사연구자 (20) 활용도상위20명

      이 자료와 함께 이용한 RISS 자료

      나만을 위한 추천자료

      해외이동버튼