报告简介：
A copula is a function that links univariate marginals to their multivariate distribution. In practice, it is normally easy to find the univariate marginals, but it is hard to obtain the multivariate distribution. With a copula, one can capture the joint distribution of random variables once their marginal distributions are obtained. Copulas, while well known in the domain of quantitative finance and have been used widely in portfolio and risk management, are still nascent in network and communication research. Compared to other dependence measures, such as the correlation function, copula has its special advantages in network traffic modelling. For instance, the invariant property of copulas indicates that a copula of two random variables remains the same if both random variables are transformed with strictly increasing functions. This property implies that the dependence structure of two traffic flows, in the measure of copula, remains unchanged, even if the packet sizes of the two flows are scaled up differently. This talk will introduce copula analysis with a hope of triggering more research interest of applying copula analysis in the domain of computer networks, particularly in network applications involving nonlinear dependence modelling.报告人简介：
Prof. Kui Wu received the B.S. degree in Computer Science in 1990 and the Master's degree in Computer Engineering in 1993, both from Wuhan University, China, and the PhD degree in Computing Science from the University of Alberta, Canada, in 2002. He joined the Department of Computer Science, University of Victoria, Canada, in 2002, where he is currently a Full Professor. He was a visiting researcher at the Centre for Quantifiable Quality of Service in Communication Systems, Norwegian University of Science and Technology (NTNU) in 2008, and a Japan Society for the Promotion of Science (JSPS) visiting scholar at University of Tsukuba in 2009. His research interests include performance analysis and protocol design of computer networks, wireless sensor networks, online social networks, smart grid, and network security. Prof. Wu’s research has been supported by Canada Foundation of Innovation (CFI), the Natural Sciences and Engineering Research Council of Canada, and industrial sponsors such as Nokia, Ericsson, and Schneider Electric. His research output has been broadly reported by MIT Tech Review, ACM Tech News, Slashdot, The Atlantic Wire, Times Colonist, The Vancouver Sun, PC World, and many more.
