The ACM has selected Vern Paxson as the recipient of the 2007 Grace Hopper Award for his research on how to measure Internet behavior. His techniques are used to assess new communications concepts, improve network performance, and prevent network intrusion. They provide both the research community and Internet operators with the tools to improve the operation of this increasingly diverse, decentralized communications infrastructure. Paxson is an Associate Professor of Computer Science at the University of California, Berkeley, Senior Scientist with the International Computer Science Institute (ICSI) Center for Internet Research, and a staff scientist at the Lawrence Berkeley National Lab. The award carries a $35,000 prize. Funding is provided by Google.
Paxson's research on Internet measurement brought the scientific process to the measurement of the Internet's behavior and the conditions under which it operates, raising the practice of Internet measurement to a higher level. As a result, the research community is able to evaluate new ideas and technologies and identify problems and priorities that are needed for increased efficiency. In addition, Internet operators are able to alleviate traffic congestion, detect attacks, and improve communications reliability.
Through a series of papers, Paxson's findings revealed the mismatches between reality and the common assumptions made in analytical and simulation models. By combining the extensive collection of data from many locations with sophisticated statistical techniques, he provided a wealth of useful information about the nature of the Internet and ways to improve its operation.
Paxson was named an ACM Fellow in 2006. His 1996 research paper titled End-to-end routing behavior in the Internet won the first "Test of Time" award given by ACM's Special Interest Group on Data Communication (SIGCOMM). The award, presented in 2006, is given to the most influential networking paper published 10-12 years before. His current research continues to focus on Internet measurement as well as network intrusion detection and large-scale Internet attacks.