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Integration of Imperfect Network Transfer and Computing Towards Low-Latency Systems

Research Project

Project/Area Number 20K21789
Research Category

Grant-in-Aid for Challenging Research (Exploratory)

Allocation TypeMulti-year Fund
Review Section Medium-sized Section 60:Information science, computer engineering, and related fields
Research InstitutionTokyo Institute of Technology

Principal Investigator

Yuko Hara  東京工業大学, 工学院, 准教授 (20640999)

Co-Investigator(Kenkyū-buntansha) 中山 悠  東京農工大学, 工学(系)研究科(研究院), 准教授 (80802058)
Project Period (FY) 2020-07-30 – 2023-03-31
Project Status Completed (Fiscal Year 2022)
Budget Amount *help
¥6,370,000 (Direct Cost: ¥4,900,000、Indirect Cost: ¥1,470,000)
Fiscal Year 2022: ¥1,950,000 (Direct Cost: ¥1,500,000、Indirect Cost: ¥450,000)
Fiscal Year 2021: ¥2,730,000 (Direct Cost: ¥2,100,000、Indirect Cost: ¥630,000)
Fiscal Year 2020: ¥1,690,000 (Direct Cost: ¥1,300,000、Indirect Cost: ¥390,000)
Keywords近似計算 / 低遅延システム / ネットワーク伝送 / 通信 / Internet of Things / Age of Information
Outline of Research at the Start

本研究では,高いリアルタイム性(低遅延性)を有するInternet of Things (IoT) システムの実現を目指す.IoTでは,コストや消費電力の制約からネットワークや計算リソースが限定される.近似計算は,ネットワーク接続されたIoTシステムで,若干の誤りを許容し高速処理する新たな計算手法として注目されている.本研究は,低遅延IoTシステム実現に向け,ネットワークを越えた近似計算の基本技術の確立に取り組む.受信データが誤りを含むことを許容し,IoT全体でアプリケーションを近似化しようとする,画期的な基盤技術となることが期待される.

Outline of Final Research Achievements

Internet of Things (IoT) systems have limited resources for networks and computations due to the design cost and power/energy consumption constraints. Recently, for such IoT systems, "approximate computing", which is a new computing paradigm, has been attractive to accelerate applications while accepting some errors. This research has addressed the fundamental studies on integrate imperfect network transfer and computing. By allowing the received data to include errors and approximating the applications all over the IoT system, low-latency IoT systems designs are enabled.

Academic Significance and Societal Importance of the Research Achievements

本研究で取り組んだACoNは、ネットワーク上の伝送誤りをアプリケーションに応じた水準で許容して低遅延化を実現する技術である。ネットワークとコンピューティングの2つの異なる技術を統合的に扱うことで初めて実現するコンセプトであり、新規性・挑戦性は高い。異分野研究領域からの大局的取り組みは、既存研究の前提・方向性を大きく転換する可能性を有する。本研究では、機械学習を用いた画像伝送システム等へACoNを適用し、その有効性を評価した。IoTにおいて機械学習ベースのアプリケーションは年々増大していることから、本研究成果はIoT社会における様々なアプリケーションを低遅延で実現できる可能性を実証したと言える。

Report

(4 results)
  • 2022 Annual Research Report   Final Research Report ( PDF )
  • 2021 Research-status Report
  • 2020 Research-status Report
  • Research Products

    (9 results)

All 2022 2021

All Journal Article (1 results) (of which Peer Reviewed: 1 results,  Open Access: 1 results) Presentation (8 results) (of which Int'l Joint Research: 6 results)

  • [Journal Article] Edge Computing-Assisted DNN Image Recognition System With Progressive Image Retransmission2022

    • Author(s)
      Nakahara Mutsuki、Nishimura Mai、Ushiku Yoshitaka、Nishio Takayuki、Maruta Kazuki、Nakayama Yu、Hisano Daisuke
    • Journal Title

      IEEE Access

      Volume: 10 Pages: 91253-91262

    • DOI

      10.1109/access.2022.3202172

    • Related Report
      2022 Annual Research Report
    • Peer Reviewed / Open Access
  • [Presentation] Hardware SAT Solver-based Area-efficient Accelerator for Autonomous Driving2022

    • Author(s)
      Yusuke Inuma, Yuko Hara-Azumi
    • Organizer
      International Conference on Field-Programmable Technology (ICFPT)
    • Related Report
      2022 Annual Research Report
    • Int'l Joint Research
  • [Presentation] Skip & Swap: Efficient Weight Spreading for Decentralized Machine Learning with Non-IID Data2022

    • Author(s)
      Asato Yamazaki, Takayuki Nishio, Yuko Hara-Azumi
    • Organizer
      Work-in-Progress of Asia Pacific Conference on Robot IoT System Development and Platform (APRIS)
    • Related Report
      2022 Annual Research Report
    • Int'l Joint Research
  • [Presentation] Stochastic Image Transmission with CoAP for Extreme Environments2022

    • Author(s)
      Erina Takeshita, Asahi Sakaguchi, Daisuke Hisano, Yoshiaki Inoue, Kazuki Maruta, Yuko Hara-Azumi, Yu Nakayama
    • Organizer
      IEEE 95th Vehicular Technology Conference (VTC-Spring) Workshop on ICA
    • Related Report
      2022 Annual Research Report
    • Int'l Joint Research
  • [Presentation] AmoebaSATを用いた効率的な自動運転アクセラレータ2022

    • Author(s)
      井沼 佑亮, 原 祐子
    • Organizer
      VLSI設計技術研究会 (VLD)
    • Related Report
      2021 Research-status Report
  • [Presentation] 超高遅延・ロス環境での遠隔物体検出のための確率的画像転送法2021

    • Author(s)
      坂口朝陽, 丸田一輝, 井上文彰, 中原睦貴, 久野大介, 原祐子, 中山悠
    • Organizer
      FIT2021 第20回情報科学技術フォーラム
    • Related Report
      2021 Research-status Report
  • [Presentation] Retransmission Edge Computing System Conducting Adaptive Image Compression Based on Image Recognition Accuracy2021

    • Author(s)
      Mutsuki Nakahara, Daisuke Hisano, Mai Nishimura, Yoshitaka Ushiku, Kazuki Maruta, Yu Nakayama
    • Organizer
      IEEE 94th Vehicular Technology Conference (VTC-Fall)
    • Related Report
      2021 Research-status Report
    • Int'l Joint Research
  • [Presentation] Image Size Reduction by Road-Side Edge Computing for Wireless Relay Transmission and Object Detection2021

    • Author(s)
      Weiran Yuan, Kazuki Maruta, Yu Nakayama, Daisuke Hisano, Kei Sakaguchi
    • Organizer
      IEEE 19th Annual Consumer Communications & Networking Conference (CCNC)
    • Related Report
      2021 Research-status Report
    • Int'l Joint Research
  • [Presentation] Deep Joint Source-Channel Coding and Modulation for Underwater Acoustic Communication2021

    • Author(s)
      Yoshiaki Inoue, Daisuke Hisano, Kazuki Murata, Yuko Hara-Azumi, Yu Nakayama
    • Organizer
      IEEE Global Communications Conference (GLOBECOM)
    • Related Report
      2021 Research-status Report
    • Int'l Joint Research

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Published: 2020-08-03   Modified: 2024-01-30  

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