魏 博 (ギ ハク)

写真a

所属

理工学術院 基幹理工学部

職名

助教

学歴 【 表示 / 非表示

  • 2015年04月
    -
    2019年02月

    早稲田大学   大学院基幹理工学研究科  

  • 2012年09月
    -
    2015年01月

    天津大学   計算機科学技術研究科  

  • 2008年09月
    -
    2012年06月

    天津大学   電子情報工学部  

経歴 【 表示 / 非表示

  • 2019年04月
    -
    継続中

    早稲田大学   理工学術院   助教

  • 2020年02月
    -
    2020年03月

    ワシントン大学

所属学協会 【 表示 / 非表示

  •  
     
     

    IEEE

  •  
     
     

    電⼦情報通信学会

 

研究分野 【 表示 / 非表示

  • 高性能計算

  • 知覚情報処理

  • 情報ネットワーク

研究キーワード 【 表示 / 非表示

  • 量子コンピューティング

  • 深層学習

  • IoT

  • マルチメディア通信

  • コンピュータネットワーク

論文 【 表示 / 非表示

  • High-QoE DASH live streaming using reinforcement learning

    Bo Wei, Hang Song, Jiro Katto

    2021 IEEE/ACM International Symposium on Quality of Service (IWQoS)    2021年06月

  • FRAB: A Flexible Relaxation Method for Fair, Stable, Efficient Multi-user DASH Video Streaming

    Bo Wei, Hang Song, Jiro Katto

    2021 IEEE International Conference on Communications (ICC)    2021年06月

  • Performance Analysis of Adaptive Bitrate Algorithms for Multi-user DASH Video Streaming

    Bo Wei, Hang Song, Shangguang Wang, Jiro Katto

    2021 IEEE Wireless Communications and Networking Conference (WCNC)    2021年03月

  • Blockchain-based data collection with efficient anomaly detection for estimating battery state-of-health

    Ruochen Jin, Bo Wei, Yongmei Luo, Tao Ren, Ruoqian Wu

    IEEE Sensors Journal    2021年

     概要を見る

    The number of electric vehicles in various countries has shown exponential growth so that the related industries to face the tremendous pressure of power batteries disposal. Efficient secondary use and recycling of power batteries require effective collection of battery data and reasonable estimation of battery state-of-health (SOH). In this paper, we propose a framework to collect battery charging data from different stakeholders with an anomaly detection method based on Isolation Forest with two features. Besides a score-based mechanism is adopted to do data screening and capture the data with good quality. Unlike prior works, our proposed method can exploit crowdsourced data to reduce the significant effort of battery data sensing and provide a data source scoring mechanism based on blockchain to improve the data quality and meet the requirement of reasonable estimation. In order to verify the effectiveness of the proposed collection method, a charge data test set is constructed based on the NASA battery data set. The simulation results indicate that the method increases the F-measure criteria up to 25.65% compared to the well-known anomaly detection algorithms. In addition, the proposed collection method outperforms the traditional method up to 10.9% in reducing the relative error when being used for SOH estimation.

    DOI

  • WiEps: Measurement of Dielectric Property with Commodity WiFi Device - An Application to Ethanol/Water Mixture

    Hang Song, Bo Wei, Qun Yu, Xia Xiao, Takamaro Kikkawa

    IEEE Internet of Things Journal   7 ( 12 ) 11667 - 11677  2020年12月

     概要を見る

    WiFi signal has become accessible everywhere, providing high-speed data transmission experience. Besides the communication service, channel state information (CSI) of the WiFi signals is widely employed for numerous Internet-of-Things (IoT) applications. Recently, most of these applications are based on the analysis of the microwave reflections caused by the physical movement of the objective. In this article, a novel contactless wireless sensing technique named WiEps is developed to measure the dielectric properties of the material, exploiting the transmission characteristics of the WiFi signals. In WiEps, the material under test is placed between the transmitter antenna and receiver antenna. A theoretical model is proposed to quantitatively describe the relationship between CSI data and dielectric properties of the material. During the experiment, the phase and amplitude of the transmitted WiFi signals are extracted from the measured CSI data. The parameters of the theoretical model are calculated using measured data from the known materials. Then, WiEps is utilized to estimate the dielectric properties of unknown materials. The proposed technique is first applied to the ethanol/water mixtures. Then, additional liquids are measured for further verification. The estimated permittivities and conductivities show good agreement with the actual values, with the average error of 4.0% and 8.9%, respectively, indicating the efficacy of WiEps. By measuring the dielectric property, this technique is promising to be applied to new IoT applications using ubiquitous WiFi signals, such as food engineering, material manufacturing process monitoring, and security check.

    DOI

全件表示 >>

受賞 【 表示 / 非表示

  • 世界経済フォーラムGlobal Future Council

    2019年   フェロー  

  • Women Techmakers Scholar

    2018年   Google  

  • 情報通信マネジメント英語セッション奨励賞

    2016年   電子情報通信学会  

  • 公益信託大槻記念アジア・アフリカ留学生奨学基金

    2016年   日本  

  • 情報通信マネジメント英語セッション奨励賞

    2015年   電子情報通信学会  

全件表示 >>

共同研究・競争的資金等の研究課題 【 表示 / 非表示

  • Adaptive bitrate control strategy for ensuring high-QoE and fair video streaming in multi-user networks

特定課題研究 【 表示 / 非表示

  • Adaptive bitrate control strategy for ensuring high-QoE and fair video streaming in multi-user networks

    2020年   Jiro Katto

     概要を見る

    With the increasing video demand in dailynetwork traffic, it is an urgent task to develop effective algorithms tofacilitate high-quality content delivery service. Recently, numerous adaptivestreaming algorithms have been proposed to improve the user perceivedexperience. We tested the performance of current adaptation methods inmulti-user network. It is found that current algorithms perform inconsistentlyin various network scenarios. In the excessive user and limited bandwidthcases, machine learning and scheduling techniques show superiority in providinghigh and equal QoE for all users. While in the high-delay case, thebuffer-based approaches show robust performance. We also proposed a new client-sideABR control method, flexible relaxation assisted by buffer (FRAB), to achievefair, stable and efficient video streaming among different users. FRAB isevaluated in real experiments under different network conditions and comparedwith conventional multi-user ABR algorithms. The experiment resultsdemonstrated that the proposed method has superior performances in multi-userDASH video streaming.

 

委員歴 【 表示 / 非表示

  • 2021年03月
    -
    継続中

    IEEE CTSoc MDT Technical Committee  Member

学術貢献活動 【 表示 / 非表示

  • IEEE Internet of Things Journal

  • IEEE Transactions on Vehicular Technology

  • China Communications

  • IEEE Access