In this tutorial, we addresses these two questions: what and how. First, we present the state of the art of WHAT we know about modeling and simulating the Internet. Second, we present cutting edge techniques of HOW to further our understanding of the network. The motivation is that despite the significant research efforts, we know very little about the Internet. Furthermore, most network researchers are unaware of the wealth of analysis tools from the areas of data mining and statistics. Data analysis based on averages, standard deviation and Poisson processes has exhausted its capabilities. We present two scenarios that describe the two main thursts of this tutorial.
MICHALIS FALOUTSOS received the B.Sc. degree in Electrical Engineering (1993) from the National Technical University of Athens, Greece and the M.Sc. and Ph.D. degrees in Computer Science from the University of Toronto, Canada (1999). He is currently an assistant professor at the University of California Riverside. He has received the CAREER award from NSF (2000), and two major DARPA grants. He has co-authored with Christos and Petros Faloutsos the highly-cited paper "On Powerlaws of the Internet Topology" (SIGCOMM'99), which renewed the interest of the community in modeling the Internet topology. His interests include Internet measurements, multicast protocols, real-time communications, and wireless networks.
CHRISTOS FALOUTSOS received the B.Sc. degree in Electrical Engineering (1981) from the National Technical University of Athens, Greece and the M.Sc. and Ph.D. degrees in Computer Science from the University of Toronto, Canada. He is currently a professor at Carnegie Mellon University. He has received the Presidential Young Investigator Award by the National Science Foundation (1989), three ``best paper'' awards (SIGMOD 94, VLDB 97, KDD01 (runner-up)), and four teaching awards. He has published over 100 refereed articles, one monograph, and holds four patents. His research interests include data mining, network analysis, indexing in relational and multimedia databases.