2018 Fiscal Year Annual Research Report
Design and Evaluation of a Mobile Cloud Computing Terminal System
| Project/Area Number |
18J10020
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| Research Institution | Tohoku University |
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| Research Fellow |
Gama Rodrigues Tiago 東北大学, 情報科学研究科, 特別研究員(DC2)
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| Project Period (FY) |
2018-04-25 – 2020-03-31
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| Keywords | edge cloud / cloud computing / artificial intelligence / machine learning / computer networks / computation offloading |
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| Outline of Annual Research Achievements |
I developed a protocol that is capable of minimizing the number of necessary cloud servers in the Mobile Edge Cloud without hurting the quality given to users (more efficient resource usage and lower cost of deployment). I developed a power saving scheme for cloud access networks (less consumed energy with a high-quality service). I created a network deployment technique for post-disaster scenarios (cheapest and most efficient way to deploy communication equipment to connect victims). I presented a couple of conference works on how to optimize Machine Learning and customize it to work better with Mobile Edge Cloud. I completed a survey of research using Machine Learning and Mobile Edge Cloud (lists all existing works and gives detailed information and instructions for future research).
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| Current Status of Research Progress |
Current Status of Research Progress
1: Research has progressed more than it was originally planned.
Reason
The research followed the scheduled plan and the expected achievements were reached as planned.
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| Strategy for Future Research Activity |
Because of the potential of Machine Learning, I have decided to change my original research plan. For my last year of Doctor's Course and JSPS scholarship, I plan to use Machine Learning to solve the difficult problem of Edge Cloud Computing server placement. This is a complicated issue, especially with multiple users. Solving this problem will help using Edge Cloud Computing with 5G and Internet of Things arguably the most important network paradigms of the next generation. Finally, I plan to finish the year with my Doctor's Course thesis on how to use Machine Learning to solve the problems of Edge Cloud Computing, from dynamic scenarios to multiple users, finalizing with an overarching base on how to make this useful technology realistic and bring it to the public.
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Research Products
(4 results)
