한국정보통신학회논문지 (Journal of the Korea Institute of Information and Communication Engineering)

  • 제26권5호
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  • Pages.786-792
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  • 2022
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  • 2234-4772(pISSN)
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  • 2288-4165(eISSN)
한국정보통신학회 (The Korea Institute of Information and Commucation Engineering)
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빈발도와 가중치를 적용한 엣지 디바이스의 최적 이동패턴 추출

Extraction of Optimal Moving Patterns of Edge Devices Using Frequencies and Weights

  • Lee, YonSik (School of Computer Info. & Comm., Kunsan National University) ;
  • Jang, MinSeok (School of Computer Info. & Comm., Kunsan National University)
  • 투고 : 2022.03.20
  • 심사 : 2022.04.14
  • 발행 : 2022.05.31
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초록

최근 클라우드 환경의 서비스 지연문제 해결을 위하여 응용서비스의 사용자 근접성 확보 및 계산 오프로딩을 위한 FEC (Fog/Edge Computing) 패러다임에 대한 연구가 활발하다. 엣지 디바이스 (이동객체)들의 동적 위치변화 패턴 예측방법은 FEC 환경에서 컴퓨팅 리소스의 효율적 분배 및 배치를 위하여 중요한 역할을 한다. 본 논문은 엣지 디바이스들의 이동 빈발패턴에 대한 지지도의 임계값을 적용하여 선택된 경로들을 대상으로 임의의 가중치 (거리, 시간, 혼잡도)를 추가적으로 적용한 최적 이동패턴 추출방법을 제안한다. 실험을 통하여 제안 알고리즘은 빈발도만을 적용한 OPE_freq [8] 알고리즘과 A* 및 Dijkstra 알고리즘 등과 비교한 결과, 수행시간과 노드 접근횟수를 감소시키고 보다 정확한 경로를 추출함을 알 수 있다.

In the cloud computing environment, there has been a lot of research into the Fog/Edge Computing (FEC) paradigm for securing user proximity of application services and computation offloading to alleviate service delay difficulties. The method of predicting dynamic location change patterns of edge devices (moving objects) requesting application services is critical in this FEC environment for efficient computing resource distribution and deployment. This paper proposes an optimal moving pattern extraction algorithm in which variable weights (distance, time, congestion) are applied to selected paths in addition to a support factor threshold for frequency patterns (moving objects) of edge devices. The proposed algorithm is compared to the OPE_freq [8] algorithm, which just applies frequency, as well as the A* and Dijkstra algorithms, and it can be shown that the execution time and number of nodes accessed are reduced, and a more accurate path is extracted through experiments.

키워드

과제정보

This work was supported by the National Research Foundation of Korea(NRF) grant funded by the Korea government(MSIT) (No. 2021R1F1A 1047768) and a grant (22RITD-C161698-02) from Regional Innovation Technology Development Program funded by Ministry of Land, Infrastructure and Transport of Korean government.

참고문헌

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