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    青年学者学术报告 《Machine Learning Assisted Network Slicing for Wireless Edge Computing System》
    发布时间:2020-12-23 15:11:26

    计算机软件新技术国家重点实验室 

    摘 要:

    5G and edge computing will serve various emerging use cases that have diverse requirements for multiple resources, e.g., radio, transportation, and computing. Network slicing is a promising technology for creating virtual networks that can be customized according to the requirements of different use cases. Provisioning network slices requires end-to-end resource orchestration which is challenging. This talk will discuss the challenges of end-to-end network slicing in wireless edge computing systems and present machine learning assisted network slicing solutions. First, the design of a new decentralized cross-domain resource orchestration solution will be presented. This solution optimizes the cross-domain resource orchestration while providing the performance and functional isolations among network slices. Second, a decentralized deep reinforcement learning algorithm will be designed to dynamically orchestrate resources for end-to-end network slicing. The system implementation and testbed design of the end-to-end network slicing system will also be discussed. Finally, future research directions in designing end-to-end network slicing solutions with machine learning will be shared.

    报告人简介:

    Tao Han (SM’20, M’15) is an Assistant Professor in the Department of Electrical and Computer Engineering at the University of North Carolina at Charlotte. He received his Ph.D. in Electrical Engineering from New Jersey Institute of Technology (NJIT) in 2015. Dr. Han was the recipient of IEEE International Conference on Communications (ICC) Best Paper Award 2019, IEEE Communications Society’s Transmission, Access, and Optical Systems (TAOS) Best Paper Award 2019, Newark College of Engineering Outstanding Dissertation Award 2016, NJIT Hashimoto Prize 2015, and New Jersey Inventors Hall of Fame Graduate Student Award 2014. He serves as an associate editor of IEEE Communications Letters and TPC member for numerous IEEE conferences. His research interest includes mobile edge networking, machine learning, mobile X reality, 5G system, Internet of Things, and smart grid.

    时间:12月29日 10:00-11:00

    腾讯会议ID:441 367 471

    上一篇:青年学者学术报告 《Efficient Document Exchange and Error Correcting Codes with Asymmetric Information》
    下一篇:青年学者学术报告 《实时网络正确性验证》
    友情链接:
    江苏省科学技术协会 中国计算机学会 南京大学 南京大学计算机科技与技术系 南京大学软件学院 东南大学计算机科学与工程学院 江苏经贸职业技术学院 南京信息职业技术学院 南京工业职业技术学院 江苏海事职业技术学院 常州信息职业技术学院 国网电力科学研究院 电子科技集团第28研究所 江南计算技术研究所 
       
     

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