Events Calendar

Network Science: Power Grids, Wireless Communication, and Epidemics

Speaker: Edmund Yeh,
Yale UniversityAbstract: Over the past decade, there has been a concerted effort to develop a network science for studying physical, biological, social, and information networks within a common framework. Of particular interest is the understanding of connectivity, robustness, and information/epidemic dynamics in large-scale networks with spatial location and mobility. In this talk, we discuss a number of recent results from the application of network science ideas to electrical power grids, wireless communication networks, and the spread of epidemics.The security and stability of the electrical power grid is one of the major challenges facing society today. In power networks carrying load, the failure of one network node can result in redistribution of the load onto other nearby nodes. If these nodes fail due to excessive load, then this process can result in a cascading failure causing widespread power outage. Using the theory of percolation, we characterize the resilience of the power network in terms of whether correlated node failures lead to a large connected component of failed nodes or not. With this approach, we obtain analytic conditions on the existence or non-existence of correlated and cascading failures in power grids.Next, we study connectivity and information dissemination in large-scale wireless networks modelled by random geometric graphs with dynamic on-off links. Using a percolation-based perspective, we show that the delay for information dissemination exhibits two behavioral regimes, corresponding to a phase transition of the underlying network connectivity. When the dynamic network is in the subcritical phase, ignoring propagation delays, the dissemination delay scales linearly with the Euclidean distance between the sender and the receiver. When the dynamic network is in the supercritical phase, the delay scales sublinearly with the distance.Mobility is an essential aspect of information and epidemic networks. In these settings, the details of the mobility process is often not as essential as the pattern of network connectivity that the mobility induces. We develop a new framework for studying mobility which maps a network of mobile nodes to a network of stationary nodes with dynamic links. Using this framework, we characterize the rate of epidemic spread (e.g. H1N1) in mobile geometric networks (e.g. human contact networks).Joint work with Zhenning Kong.Biography: Edmund Yeh received his B.S. in Electrical Engineering with Distinction from Stanford University in 1994, his M.Phil in Engineering from the University of Cambridge in 1995, and his Ph.D. in Electrical Engineering and Computer Science from MIT in 2001. Since 2001, he has been on the faculty at Yale University, where he is currently an Associate Professor of Electrical Engineering (with joint appointments in Computer Science and Statistics).Host: Giuseppe Caire, caire@usc.edu, EEB 528, x04683

Location: Hughes Aircraft Electrical Engineering Center (EEB) - 248

Audiences: Everyone Is Invited

Contact: Gerrielyn Ramos