Random early detection gateways for congestion avoidance
IEEE/ACM Transactions on Networking (TON)
An Immunological Approach to Change Detection: Algorithms, Analysis and Implications
SP '96 Proceedings of the 1996 IEEE Symposium on Security and Privacy
A conceptual framework for bio-inspired congestion control in communication networks
Proceedings of the 1st international conference on Bio inspired models of network, information and computing systems
Equation-based congestion control in the internet biologic environment
Transactions on computational systems biology VIII
Predator-prey system: an optimiser that solves a linear programming
International Journal of Bio-Inspired Computation
On the use of a full information feedback to stabilize RED
Journal of Network and Computer Applications
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Congestion in the Internet is the main reason for reduced performance and poor quality of service; therefore, a good congestion control system is essential. The current work proposes that the congestion control problem in the Internet can be inspired from natural population control tactics. Toward this idea, the congestion window size of each connection is viewed as population size of a species and then congestion control problem is redefined as population control of these windows species (W). This paper defines a three-trophic food chain and gives a model to control population size of W species within this food chain. Simulation results show that the proposed algorithm leads to a fair, stable and high-performance congestion control scheme.