报告人： Qun Li
Department of Computer Science College of William and Mary
时间：2008年6月23日 （周一） 下午 15：00
地点：蒙民伟楼109会议室
Abstract:
As RFID tags are increasingly attached to everyday items, it quickly becomes i
mpractical to collect data from every tag in order to extract useful informati
on. In this talk, I will discuss the problem of identifying popular categories
of RFID tags out of a large collection of tags, without reading all the tag d
ata. We propose two algorithms based on the idea of group testing, which allow
s us to efficiently derive popular categories of tags. We evaluate our solutio
ns using both theoretical analysis and simulation. In this talk, I will also s
ummarize our recent work in sensor network and RFID systems.
Bio: Qun Li is an assistant professor in the department of Computer Science at
College of William and Mary. He obtained his Ph.D. from Dartmouth College in
2004. His main research effort is on wireless networks and embedded systems, i
ncluding pervasive computing, cognitive radio, wireless LANs, mobile ad-hoc ne
tworks, sensor networks, and RFID systems. It involves designing and analyzing
algorithms, building and simulating prototype systems, and conducting real ne
twork experiments and measurements. He was a recipient of the NSF Career Award
2008.
