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2019 Fiscal Year Annual Research Report

Design and Evaluation of a Mobile Cloud Computing Terminal System

Research Project

Project/Area Number 18J10020
Research InstitutionTohoku University
Research Fellow Gama Rodrigues Tiago  東北大学, 情報科学研究科, 特別研究員(DC2)
Project Period (FY) 2018-04-25 – 2020-03-31
Keywordsedge cloud / cloud computing / computer networks / computation offloading / machine learning / artificial intelligence
Outline of Annual Research Achievements

The survey of research using Machine Learning and Mobile Edge Cloud I completed last year was accepted in the beginning of this year. I also created a Machine Learning-based protocol for deciding the best locations to deploy edge servers based on network architecture and user disposition. My solution is capable of improving performance 40% from what conventional research applies. This research resulted in a presentation in an esteemed international conference and a publication in a top ranked journal. I ended the year by working on my my Doctor’s thesis. I talked about how Machine Learning could be used to significantly improve the performance of Mobile Edge Cloud. In thesis I also combined all my previous solutions into one single overarching protocol.

Research Progress Status

令和元年度が最終年度であるため、記入しない。

Strategy for Future Research Activity

令和元年度が最終年度であるため、記入しない。

Research Products

(3 results)

All 2020 2019

All Journal Article (2 results) (of which Int'l Joint Research: 2 results,  Peer Reviewed: 2 results) Presentation (1 results) (of which Int'l Joint Research: 1 results)

  • [Journal Article] Machine Learning Meets Computation and Communication Control in Evolving Edge and Cloud: Challenges and Future Perspective2020

    • Author(s)
      Rodrigues Tiago Koketsu、Suto Katsuya、Nishiyama Hiroki、Liu Jiajia、Kato Nei
    • Journal Title

      IEEE Communications Surveys & Tutorials

      Volume: 22 Pages: 38~67

    • DOI

      10.1109/COMST.2019.2943405

    • Peer Reviewed / Int'l Joint Research
  • [Journal Article] Edge Cloud Server Deployment with Transmission Power Control through Machine Learning for 6G Internet of Things2020

    • Author(s)
      Koketsu Rodrigues Tiago、Suto Katsuya、Kato Nei
    • Journal Title

      IEEE Transactions on Emerging Topics in Computing

      Volume: 1 Pages: 1~1

    • DOI

      10.1109/TETC.2019.2963091

    • Peer Reviewed / Int'l Joint Research
  • [Presentation] Hyperparameter Study of Machine Learning Solutions for the Edge Server Deployment2019

    • Author(s)
      Koketsu Rodrigues Tiago
    • Organizer
      IEEE
    • Int'l Joint Research

URL: 

Published: 2021-01-27  

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