Globally stable and high-performance Internet congestion control through a computational inspiration from nature

There are many reasons to worry that the current congestion control schemes in the Internet may be reaching its limits. Since the nature is a source of excellent solutions for complex problems, this work attempts to solve the congestion control problem, by adopting some biological principles and mechanisms. The current work proposes that the congestion problem in the Internet can be addressed through an inspiration from the population control tactics in nature. Toward this idea, each flow (W) in the network is viewed as a species whose population size matches congestion window size of the flow. By this assumption, congestion control problem is redefined as population control of flow species. This paper defines a three-trophic food chain analogy in congestion control area, and gives a model to control population size of W species within this food chain. We call this model BICCTT and show mathematically, it is stable and efficient regardless of the link capacity, the round-trip delay, and number of flows. Extensive packet-level simulations in ns-2, show that BICCTT operates better than TCP/RED and XCP in both typical and high bandwidth-delay environments. BICCTT achieves fair bandwidth allocation, high utilization, small queue size, and near-zero packet drops. It does not maintain any per-flow state in routers and have low computational loads per packet, which makes it scalable.