豊橋技術科学大学

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Xun SHAO

Affiliation Department of Electrical and Electronic Information Engineering
Title Associate Professor
Fields of Research Computer Networks, Distributed Systems, Machine Learning
Degree Ph.D. (Osaka University)
Academic Societies IEEE, IEICE, IPSJ
E-mail shao.xun.ls@
Please append "tut.jp" to the end of the address above.
Laboratory website URL https://scholar.google.co.jp/citations?user=53ub8A4AAAAJ&hl=ja
Researcher information URL(researchmap) Researcher information

Research

当研究室では、スマート社会の実現に必要なエッジコンピューティング、情報ネットワーク、スマートシステムについての研究を行っています。研究手法としては、コンピューティング、コミュニケーション、人工知能の融合を重視し、持続可能な未来社会のための情報通信インフラと高度なアプリケーションの提供を目指して研究開発を行っています。

Theme1:Edge computing

Overview

In recent years, with the rapid growth of mobile computing and communications technologies, the shift to the IoT-edge paradigm, where cloud functions are distributed from data centers to edge servers at the edge of the Internet, is becoming clearer. However, most existing research is focused on specific services, and the large-scale general-purpose edge computing technology as required by smart cities, has yet to be established. Our laboratory is developing the optimal architecture and orchestration mechanism for large-scale general-purpose edge computing systems with state-of-the-art technology, aiming at providing efficient solutions with low cost to support the future smart society.

Selected publications and works

https://scholar.google.co.jp/citations?user=53ub8A4AAAAJ&hl=ja

Keywords

Edge computing, Orchestration, Online optimization

Theme2:Smart systems

Overview

In addition to the research and development of fundamental edge computing technologies, it is also necessary to research and develop a variety of advanced applications that take advantage of these technologies. We believe that advanced applications enabled by large-scale edge computing can contribute to the realization of smart cities. On the other hand, feedback from application usage to the edge computing systems will lead to improvement and refinement of the edge computing infrastructure. Therefore, our laboratory is developing data distribution systems, industrial IoT systems, renewable energy management systems, and other intelligent applications for a smart society.

Selected publications and works

https://scholar.google.co.jp/citations?user=53ub8A4AAAAJ&hl=ja

Keywords

Advanced applications, IoT-edge paradigm, smart society

Theme3:Transport network

Overview

Transport networks, located between edge clouds and smart terminals, play an important role in providing high-quality services to users. However, due to the highly dynamic mobile network environment and heterogeneity of physical resources, conventional optimization methods cannot achieve the expected results. To solve these problems, our laboratory uses the latest machine learning techniques to predict the dynamics of the network environment, and based on these predictions, solves the optimal network resource allocation and data transportation problems, aiming to provide high-quality data transmission services to the smart society.

Selected publications and works

https://scholar.google.co.jp/citations?user=53ub8A4AAAAJ&hl=ja

Keywords

Future prediction, dynamic path calculation, multipath data transportation

Title of class

For undergraduate students
・Embedded systems 
・Introduction to Communication Engineering
・Fundamental Numeric Analysis
For graduate students
・Advanced digital systems 2

Others (Awards, Committees, Board members)

Please refer to:
https://researchmap.jp/x-shao?lang=en


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