CONTENT

$\; \;$ $\;$What do we know about the Internet?

How can you learn more about it?

The main goal of this tutorial is to present what we know about modeling the Internet, and how we can learn more. The tutorial intends to bridge the gap between network researchers and datamining research.

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 eloquently the two main thrusts of this tutorial.

1. Scenario one (WHAT): You want to simulate your new protocol. What topology should you use? What is the distribution of sources and destinations? What is the traffic intensity of each connection? What kind of background traffic should we use?

2. Scenario two (HOW): You just obtained large measured data of round trip delays among several node pairs over a few hours. How can you characterize it? How do you compare the delays between different end-points? How do you cluster "similar" round-trip behavior? How can you identify abnormal behavior such as a Distributed Denial of Service Attack (DDoS)?