As other complex systems in social and natural sciences as well as in
engineering, the Internet is hard to understand from a technical point
of view. Packet switched networks defy analytical modeling. The Internet
is an outstanding and challenging case because of its fast development,
unparalleled heterogeneity and the inherent lack of measurement and
monitoring mechanisms in its core conception.
This monograph deals with applications of computational intelligence
methods, with an emphasis on fuzzy techniques, to a number of current
issues in measurement, analysis and control of traffic in the Internet.
First, the core building blocks of Internet Science and other related
networking aspects are introduced. Then, data mining and control
problems are addressed. In the first class two issues are considered:
predictive modeling of traffic load as well as summarization of traffic
flow measurements. The second class, control, includes active queue
management schemes for Internet routers as well as window based
end-to-end rate and congestion control. The practical hardware
implementation of some of the fuzzy inference systems proposed here is
also addressed. While some theoretical developments are described, we
favor extensive evaluation of models using real-world data by simulation
and experiments.