ABSTRACT

In the light of TCP's scalability issues in high bandwidth-delay networks, explicit-feedback congestion control has gained renewed interest in the last several years. Sometimes referred to as Active Queue Management (AQM) congestion control, these algorithms rely on the routers to provide the various types of congestion feedback including changes to the congestion window, packet loss, single-bit congestion indication, queuing delay, and link prices. This information helps end-flows converge their sending rates to some social optimum and achieve a certain optimization objective. Unlike some of the largely ineffective AQM aimed at improving the performance of TCP, properly designed explicit congestion control promises to provide scalability to arbitrary bandwidth (i.e., terabits and petabits per second), tunable link utilization, low delay, zero loss, oscillation-free steady state, and exponential convergence to fairness/efficiency. Such algorithms, once deployed successfully in the Internet, may remain in service for many years to come.

This proposal does not aim to settle the debate of whether or when explicit congestion control can/will be adopted by the Internet, but to explore the various properties of the existing AQM methods (such as XCP, RCP, MKC, AVQ, and MaxNet), propose a new controller that improves the performance of existing approaches in highly heterogeneous network conditions, and evaluate its performance in a network of software and hardware routers.

Broader Impact: Aside from theoretical contributions to delayed and discontinuous stability analysis of congestion control, this project will deliver a low-overhead implementation of the studied methods, educate graduate and undergraduate students, and disseminate the various findings to the public.

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