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报告主题：Measuring and Understanding Large-scale (Video) Content Delivery Systems报告主讲：Zhang，Zhi-li报告时间：2014-09-22（周一）15:00-17:00报告地点：机械工程楼东配楼D301

报告简介：Past few years have seen the explosive growth in online video content and the increasing popularity of video streaming services. Unlike other content, storing and delivering video require a vast and sophisticated infrastructure with huge computing, storage and network capacities. Therefore, design of large-scale video content delivery infrastructure is a highly challenging engineering task. In this talk, I will present our recent studies on “reverse-engineering” the YouTube and Netflix video delivery systems through passive and active measurements. The rational behind our studies are multi-fold: on the one hand we believe that YouTube and Netflix video delivery systems offer two interesting and contrasting examples of the b best practicesb in the design of an Internet-scale content delivery infrastructure. On the other hand, the design of both systems also poses some interesting and important questions regarding alternative architectural designs such as cache placement, content replication and load balancing strategies. Furthermore, as large-scale video content delivery requires (explicit or implicit) cooperation of various parties (content producers/providers, CDNs, ISPs and users), many of which have competing interests, the design and operations of such systems also raise many important issues in Internet economics and business models, which may significant socio-technical implications.

报告人简介：Professor Zhang is Qwest Chair Professor in Telecommunications and McKnight Distinguished University Professor at Department of Computer Science & Engineering, University of Minnesota. He received his B.S. degree in Computer Science from Nanjing University, China, and his M.S. and Ph.D. degrees in Computer Science from the University of Massachusetts, Amherst. He has held visiting positions at University of California, Berkeley, and Miller Institute of Basic Sciences; IMDEA Networks and Universitad Carlos III Madrid; AT&T Labs—Research; Sprint Advanced Technology Labs; IBM T.J. Watson Research Center; Microsoft Research; Fujitsu Labs of America and INRIA, Sophia-Antipolis, France. Dr. Zhang’s research interests lie broadly in computer communication and networks, Internet technology, multimedia and emerging applications. His past research was centered on the analysis, design and development of scalable Internet QoS solutions to support performance-demanding multimedia applications. His current research focuses on building highly scalable, resilient and secure Internet infrastructure and mechanisms to enhance Internet service availability, reliability and security, and on developing next generation, service-oriented, manageable Internet architectures to provide better support for creation, deployment, operations and management of value-added Internet services and underlying networks, including mobile, cloud and content delivery services and networks.

Dr. Zhang has served on the Editorial board of IEEE/ACM Transactions on Networking, Elsevier’s Computer Networks, Journal of Computational Social Networks, and Journal of Computer Science and Technology. He was Technical Program Co-chair of IEEE ICNP’13, IFIP Networking 2013, IEEE INFOCOM 2006, ACM/USENIX Internet Measurement Conference 2008 and IEEE/IFIP IWQoS Workshop. He has served on the Technical Program Committees of various conferences and workshops including ACM SIGCOMM, ACM SIGMETRICS, ACM/USENIX IMC, IEEE INFOCOM, IEEE ICNP and CoNext. He received the National Science Foundation CAREER Award, the Miller Visiting Professorship at Miller Institute for Basic Sciences, University of California, Berkeley, the University of Minnesota McKnight Distinguished University Professorship, the George Taylor Distinguished Research Award, and McKnight Land-Grant Professorship. He is co-recipient of four Best Paper Awards (ACM SIGMETRICS’96, IEEE ICNP’02 and IEEE INFOCOM’10, RAID’13). He is a member of IEEE and ACM, and a Fellow of IEEE