Knowledge Centric Networking:Challenges and Opportunities

报告人:吴大鹏教授 (美国佛罗里达大学教授)





吴大鹏博士,美国佛罗里达大学教授,国际电气电子工程师学会会士(IEEE Fellow),2003年于美国卡内基梅隆大学获得博士学位。他的研究兴趣涵盖网络、通信、视频编码、图像处理、计算机视觉、信号处理和机器学习。他获得了2009年佛罗里达大学研究基金教授奖、2007年美国自然科学基金委职业奖、2001年IEEE视频电路与系统汇刊最佳论文奖、2011年Globecom国际会议最佳论文奖等。现在他担任IEEE通信汇刊、网络信号与信息处理汇刊、信号处理杂志等期刊编委,是IEEE网络科学与工程汇刊主编, 并担任多个国际会议的大会主席等学术职务。

Prof. DapengOliver Wu received Ph.D. in Electrical and Computer Engineering from CarnegieMellon University, Pittsburgh, PA, in 2003. Since 2003, he has been on thefaculty of Electrical and Computer Engineering Department at University of Florida,Gainesville, FL, where he is currently Professor. His research interests are in the areas ofnetworking, communications, video coding, image processing, computer vision,signal processing, and machine learning.

He received University of Florida Term Professorship Award in 2017,University of Florida Research Foundation Professorship Award in 2009, AFOSRYoung Investigator Program (YIP) Award in 2009, ONR Young Investigator Program(YIP) Award in 2008, NSF CAREER award in 2007, the IEEE Circuits and Systemsfor Video Technology (CSVT) Transactions Best Paper Award for Year 2001, theBest Paper Award in GLOBECOM 2011, and the Best Paper Award in QShine2006. Currently, he serves asEditor-in-Chief of IEEE Transactions on Network Science and Engineering, andAssociate Editor of IEEE Transactions on Communications, IEEE Transactions onSignal and Information Processing over Networks, and IEEE Signal ProcessingMagazine. He was the foundingEditor-in-Chief of Journal of Advances in Multimedia between 2006 and 2008, andan Associate Editor for IEEE Transactions on Circuits and Systems for VideoTechnology, IEEE Transactions on Wireless Communications and IEEE Transactionson Vehicular Technology. He has served as Technical Program Committee (TPC)Chair for IEEE INFOCOM 2012. He was elected as a Distinguished Lecturer by IEEE Vehicular Technology Society in 2016. Heis an IEEE Fellow.


In the creation ofa smart future information society, Internet of Things (IoT) and ContentCentric Networking (CCN) break two key barriers for both the front-end sensingand back-end networking. However, we still observe the missing piece of theresearch that dominates the current design, i.e., lacking of the knowledgepenetrated into both sensing and networking to glue them holistically. In thistalk, I will introduce and discuss a new networking paradigm, called KnowledgeCentric Networking (KCN), as a promising solution. The key insight of KCN is toleverage emerging machine learning or deep learning techniques to createknowledge for networking system designs, and extract knowledge from collecteddata to facilitate enhanced system intelligence and interactivity, improvedquality of service, communication with better controllability, and lower cost.This talk presents the KCN design rationale, the KCN benefits and the potentialresearch opportunities.

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