The Past and Future of Internet Research

As I've spent time studying pieces of the Internet research literature I've been surprised that the majority of it has been entirely based on empirical observation, and in the infancy of the Internet, observation on live systems. For instance, congestion avoidance algorithms came about after an episode that caused a portion of the network to drop its throughput one thousand-fold. Van Jacobsen, a noted researcher and the owner of an affected segment of the network, decided to analyze and fix the problem through a hands-on debugging session. Although it appears that over time people have began to use simulation software to test hypothesis more rigorously before deployment, these tests are still inherently observation-based.

This style of research contrasted greatly with that of Feng and Vanichpun on TCP Vegas. In their 2003 research paper they construct a mathematical model of Reno and Vegas connections competing with one another for bandwidth. With this model they could predict the probability that a particular packet would be dropped, the average window size and queue size of a connection, and most importantly, the ratio of throughput of the two connections. Using this model they were easily able to tweak Vegas parameters to cause the two connection types to be fair with one another, something that no one had accomplished previously. The empirical experiments that followed simply served the role to verify the correctness of the model. If the researchers did not perform this rigorous analysis of the two connections, they would have had only brute-force methods at their disposal to try to discover an optimal parameter set for TCP Vegas.

Because of this paper I believe that continued progress on Internet architecture research will become increasingly reliant on constructing such models and performing such analyses. Distributed concurrent autonomous systems are inherently complex and The Internet itself continues to grow in complexity over time. Discovering models that allow us to predict and understand aspects of this system more thoroughly will enable us to discover new ideas we would otherwise be unable to find.