Our goal is to understand the evolution of the Autonomous System (AS) ecosystem over the last decade. Instead of focusing on abstract topological properties, we classify ASes into a number of "species"' depending on their function and business type. Further, we consider the semantics of inter-AS links, in terms of transit versus peering relations.
After an exponential increase phase until 2001, the Internet now grows linearly in terms of both ASes and inter-AS links. The growth is mostly due to enterprise networks and content/access providers at the periphery of the Internet. The average path length remains almost constant mostly due to the increasing multihoming degree of transit and content/access providers. In recent years, enterprise networks prefer to connect to small transit providers, while content/access providers connect equally to both large and small transit providers. The AS species differ significantly from each other with respect to their rewiring activity; content/access providers are the most active. A few large transit providers act as "attractors" or "repellers" of customers.
For many providers, strong attractiveness precedes strong repulsiveness by 3-9 months. Finally, in terms of regional growth, we find that the AS ecosystem is now larger and more dynamic in Europe than in North America.
Dr. Constantine Dovrolis is an Associate Professor at the College of Computing of the Georgia Institute of Technology. He received the Computer Engineering degree from the Technical University of Crete (Greece) in 1995, the M.S. degree from the University of Rochester in 1996, and the Ph.D. degree from the University of Wisconsin-Madison in 2000. He joined Georgia Tech in August 2002, after serving at the faculty of the University of Delaware for about two years. He has held visiting positions at Thomson Research in Paris, Simula in Oslo, and FORTH in Crete.
His current research focuses primarily on the evolution of the Internet, intelligent route control mechanisms and performance-aware routing, automated performance problem diagnosis, and applications of network measurements.
