2019年05月06日 00:00 发布人: 学科科研 阅读次数:    
主讲人: Kui Wu
主题: Network Performance Tomography: A Revisit of an Old Problem
时间: 2019年5月10日(星期五)下午 2:30
地点: C2-504
       Network performance tomography infers performance metrics on internal network links with end-to-end measurements. Existing results in this domain are mainly Boolean-based, i.e., they check whether or not a link is identifiable, and return the exact values for identifiable links. If a link is not identifiable, however, Boolean-based solution gives no performance result for the link. We extended Boolean-based network tomography to bound-based network tomography where the lower and upper bounds are derived for unidentifiable links. We develop efficient algorithms to minimize the total error bound across the network. We also present two methods that can significantly reduce the total number of measurement paths required for deriving the tightest bound.  At the end of the talk, open research problems and the potential applications of network performance tomography will be introduced. 
        Kui Wu received the Ph.D. degree in Computing Science from the University of Alberta, Canada, in 2002, and in the same year joined the Department of Computer Science at the University of Victoria, Canada, where he is currently a Full Professor. During his sabbatical leaves, he was a Visiting Professor at the Centre for Quantifiable Quality of Service in Communication Systems, Norwegian University of Science and Technology (NTNU), 2008, a Visiting Scholar of Japan Society for the Promotion of Science (JSPS) at University of Tsukuba, 2009, and now a Visiting Professor at the City University of Hong Kong. His current research interests include network calculus, dependence modelling, network tomography, and computational sustainability (covering green computing and computing for green). He likes various racket sports, including badminton, tennis, and ping-pong, in the decreasing order of playtime. At weekends, he enjoys hiking along the beautiful coastline on Vancouver Island.


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