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李振华 Zhenhua Li

Ph.D. student (3rd year / 4 years), Peking University, Beijing, China

Joint-Ph.D. student (2011.9 - 2012.9), University of Minnesota, Twin Cities, USA

Member, ACM & CCF

Address:	2428 Delaware St. SE, Solhaus APT, Room 504, Minneapolis, MN, USA 55414
Email:	lizhenhua1983@gmail.com, lzh@net.pku.edu.cn

My Light Blog

Brief CV:

2009.6 - 2013.6 PhD student @ Network Lab, School of EECS, Peking University, Supervisor: Prof. Yafei Dai

2011.9 - 2012.9 Joint-PhD student @ University of Minnesota, Twin Cities, Mentor: Qwest Chair Prof. Zhi-Li Zhang (IEEE Fellow)

2011.9 - now Bible Learning @ Connexions, Stadium Village Church, Minneapolis, Tutor: Robert & Joanne Kraftson

2010.6 - 2010.8 Research Intern @ Tencent Research (Shanghai), Coordinator: Yan Huang, Gang Liu, et al.

2008.6 - 2009.4 Software Engineer @ Marvell Technologies (Shanghai) Co. Ltd

2007.5 - 2007.10 Research Assistant @ Hong Kong Polytechnic University, Mentor: Chair Prof. Jiannong Cao

2001.9 - 2008.6 Bachelor & Master @ Dept. of Computer, Nanjing University, Supervisor: Prof. Guihai Chen

Research Summary:

☞ published over 15 papers on SCI journals (TPDS, TOMCCAP, JPDC, etc.) and EI conferences (ACM-MM, IPDPS, ICPP, ICCCN, P2P, ICPADS, etc.); besides, publised one book named Peer-to-Peer Network: Structure, Application and Design (《对等网络：结构、应用与设计》，清华大学出版社，中国大学出版社图书奖首届优秀学术著作一等奖！

☞ served as Web and Publicity Chair of HotPOST'11, and PC Member of EI conferences/workshops including ICPP'12, ICCCN'11, HotPOST'11, etc.

☀ *My PhD research topic is:* "Heavy-Cloud and Light-End" Internet Content Distribution ✎The most fundamental functionality of Internet is to distribute digital contents from source to end users. As the fast upsurge of powerful "heavy-weight clouds" (like Google, Amazon, YouTube, etc.) and mobile "light-weight end users" (like iPhone, iPad, Android phone/tablet, etc.), Internet content distribution has been largely reshaped. Therefore, ...
☆ Cloud Bandwidth Scheduler (FIFA)	✎efficiently schedules cloud bandwidth into end host peers to maximize the bandwidth multiplier effect with a fine-grained model and fast-convergent algorithm (FIFA). This work is simulated on the *QQXuanfeng* system trace and is implemented on the CoolFish* VoD streaming prototype.*
☆ Cloud Transcoder	✎helps Internet users (in particular mobile devices) to transcode videos to appropriate formats and resolustions in an energy-efficienct manner. The user only sends his video request to our cloud which does everything else: download, transcode, (cache,) and transfer back.
☆ CloudTracker	✎bridges the cloud-based content distribution and P2P content distribution, so as to accelerate the data transfer of peers as well as to facilitate load-balancing among cloud servers. Please try the huge-scale QQXuanfeng Cloud Tracking* system!*
★ **Cloud Download (or says Offline Download)**	✎achieves high-quality content distribution (especially for unpopular videos) by using cloud utilities to guarantee the data health and enhance the data transfer rate. Please try the large-scale QQXuanfeng Cloud Download system! ♨The corresponding paper was published in ACM-MM'11* as a Long Paper —— maybe the first published international paper of the Tencent company.*
★ *P2P Media Streaming Optimization*	✎optimizes several critical performance metrics (i.e., playback continuity, startup latency, media source switching time, overlay resilience, etc.) of P2P video streaming. ♨The corresponding papers were published in IPDPS'08, ICPP'08, 《软件学报》'08, ICPP'09, JPDC'10, ICPADS'10, ICCCN'11, TPDS'11, TOMCCAP'12, etc.