Understanding and Modeling Wi-Fi Users

Minkyong Kim
Department of Computer Science
Dartmouth College, Hanover, NH


Understanding user mobility is important in designing location-aware systems and wireless networks, and for simulations of mobile devices in a wireless network. I will start this presentation by providing a better understanding of user mobility. For example, we analyzed periodicities in real wireless network traces and found that 24% of users move in random patterns while the other users exhibit periodic patterns.

I will then describe our experiences in extracting user mobility characteristics from wireless network traces, and developing a mobility model based on these characteristics. I will present a method to extract the physical path of users from the sequence of access points recorded in network traces. Using this method, we were able to analyze mobility characteristics; we discovered that the distributions of speed and pause time each follow a log-normal distribution and that the direction of movements closely reflects the direction of roads and walkways. I will finally describe a mobility model that focuses on user movements among popular regions. I will conclude the talk with a discussion of remaining challenges in mobility modeling.

Short Bio

MINKYONG KIM is currently a postdoctoral research fellow in the Department of Computer Science at Dartmouth College, collaborating with Professor Kotz. Her research interests include wireless networks, mobile computing, pervasive computing, and distributed systems. In her Ph.D. work, she designed a file system for mobile clients and developed a filter that estimates network capacity for adaptive systems. She received her Ph.D. in Computer Science and Engineering from the University of Michigan in 2004. She completed her B.S. and M.S. in Computer Engineering at Seoul National University, Korea, in 1996 and 1998, respectively.

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