This paper concentrates on a detailed analysis of the increase/decrease algorithms for dealing with the problem of network congestion.
The main contribution of this paper is to abstractly characterize the wide class of increase/decrease algorithms and compare them using several different performance metrics.
(1) Congestion avoidance and congestion control are two different things.
Congestion avoidance attemnpts to keep the network from congesting by
"operating at the knee" whereas congestion control shemes help improve
performance after congestion has occurred.
(2) The criteria for selecting controls are efficiency, fairness, distributedness, and convergence. (3) What are all the possible solutions that converge to efficient and fair states? How do we compare those controls that converge.
I would give this paper a 4 because it seems to be a significant contribution to the series of papers on congestion [7,8,10,11]. This paper's analytical approach in describing how to characterize different controls really strengthens their results.
The authors of this study use analytical models to classify the set of possible solutions. The authors first characterize the set of all linear controls that converge and narrow this set down based on the distributedness criterion. Next, they try to find a subset that represents the optimal trade-off of responsiveness and smoothness. Finally, the authors discuss how to extend the results to nonlinear controls as well as discussing practical considerations.
The biggest limitation of this paper was the fact that the authors had to abstract away several details in order to classify a set of problems. Specifically, the model assumes that all users sharing the same bottleneck will receive the same feedback and react to it.
A simple additive increase and multiplicative decrease algorithm satisfiees the sufficient conditions for convergence to an efficient and fair state regardless of the starting state of the network.