• Title/Summary/Keyword: Streamable execution

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Low-Power Streamable AI Software Runtime Execution based on Collaborative Edge-Cloud Image Processing in Metaverse Applications (에지 클라우드 협동 이미지 처리기반 메타버스에서 스트리밍 가능한 저전력 AI 소프트웨어의 런타임 실행)

  • Kang, Myeongjin;Kim, Ho;Park, Jungwon;Yang, Seongbeom;Yun, Junseo;Park, Daejin
    • Journal of the Korea Institute of Information and Communication Engineering
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    • v.26 no.11
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    • pp.1577-1585
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    • 2022
  • As the interest in the 4th industrial revolution and metaverse increases, metaverse with multi edge structure is proposed and noted. Metaverse is a structure that can create digital doctor-like system through a large amount of image processing and data transmission in a multi edge system. Since metaverse application requires calculating performance, which can reconstruct 3-D space, edge hardware's insufficient calculating performance has been a problem. To provide streamable AI software in runtime, image processing, and data transmission, which is edge's loads, needs to be lightweight. Also lightweight at the edge leads to power consumption reduction of the entire metaverse application system. In this paper, we propose collaborative edge-cloud image processing with remote image processing method and Region of Interest (ROI) to overcome edge's power performance and build streamable and runtime executable AI software. The proposed structure was implemented using a PC and an embedded board, and the reduction of time, power, and network communications were verified.