Recent advances in the modeling of network congestion control systems
have highlighted the importance of dynamic effects. In particular, many
empirically observed oscillations can be traced to instability, and
appear even at the level of averaged flow quantities. Designing a
stable alternative is non-trivial due to the decentralized nature of
the information, and the dependence on unknown network parameters.
In this talk we describe a congestion control system which is arbitrarily
scalable, in the sense that its stability is maintained for arbitrary
network topologies and arbitrary amounts of delay. Such a system
can be implemented in a decentralized way with information currently
available in networks plus a small amount of additional signaling.
References:
F. Paganini, J. Doyle, S. Low
Scalable Laws for Stable Network Congestion Control.
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