Analysis of the Increase and Decrease Algorithms for Congestion Avoidance in Computer Networks

By mathematically characterizing the effect of different back-off schemes on achieving fairness and efficiency of a network system, Chiu and Jain are able to show that an additive increase and multiplicative decrease network traffic feedback/control scheme does the job of converging to both fairness and efficiency under any initial starting state. Chiu and Jane define fairness to be the degree (or percentage) to which nodes are utilizing an equal amount of network resources. Efficiency is defined in terms of the distance from the "knee" of the throughput x load curve, where being closer always means better efficiency. By using a simple two node example it is shown that additive increase and multiplicative increase always moves closer to the optimum point (i.e. 50% utilization of network resources by node 1 and node 2). The paper later generalizes this to n nodes, and shows that in fact for optimal convergence to fairness additive increase and multiplicative decrease is the best feedback policy. Nonlinear controls are considered but not explored much and possibilities for future work is presented.

The paper overall did an excllent job of characterizing the system mathematically and showing that the additive increase/multiplicative decrease was the best under the assumptions made. The paper however did not justify thoroughly the assumptions that it made about the system sending the same feedback response to both nodes and simplifying the system to be "turn-based" in that nodes react and then all nodes get feedback, etc.

Interesting dicussion topics would be how this work has influenced network design today, and how networks today implement feedback.