한국멀티미디어학회논문지 (Journal of Korea Multimedia Society)

  • 제25권8호
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  • Pages.1136-1140
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  • 2022
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  • 1229-7771(pISSN)
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  • 2384-0102(eISSN)
한국멀티미디어학회 (Korea Multimedia Society)
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엣지 컴퓨팅에서 트래픽 분산을 위한 흐름 예측 기반 동적 클러스터링 기법

Flow Prediction-Based Dynamic Clustering Method for Traffic Distribution in Edge Computing

  • 투고 : 2022.08.14
  • 심사 : 2022.08.24
  • 발행 : 2022.08.31
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초록

This paper is a method for efficient traffic prediction in mobile edge computing, where many studies have recently been conducted. For distributed processing in mobile edge computing, tasks offloading from each mobile edge must be processed within the limited computing power of the edge. As a result, in the mobile nodes, it is necessary to efficiently select the surrounding edge server in consideration of performance dynamically. This paper aims to suggest the efficient clustering method by selecting edges in a cloud environment and predicting mobile traffic. Then, our dynamic clustering method is to reduce offloading overload to the edge server when offloading required by mobile terminals affects the performance of the edge server compared with the existing offloading schemes.

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참고문헌

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