CS268 Reading Review

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

Dah-Ming Chiu and Raj Jain
Review by Feng Zhou
1/29/2003

The problem: The central part of congestion avoidance algorithm is the way to increase and descrease the load in face of congestion and normal transmission. Linear control methods (additive and multiplicative) are studied in this paper analytically.

Key points:

  1. The most significant conclusion is decrease must be multiplicative to ensure the system to converge to a fair stable state. This not-so-obvious conclusion is very clear in the vector representation graph used in the paper, which in my opinion is a pretty useful tool. Beside that, the increase policy must have an additive item and have a multiplicative factor >= 1.
  2. The second useful point is that in order for hosts to be able to make decisions without global knowledge. The increase policy should be additive, in the abscence of truncation. This, plus the first conclusion, leads to the AIMD rule that is widely in use now.
  3. Regarding optimal convergence to effectiveness and fairness. One useful result is by increasing "responsiveness", you always decrease "smoothness", with is natural for such a feed-back control system. For fairness, using additive increase always gives us fastest convergence.
  4. Although the conclusion is pretty reasonable and useful. The analysis process seems overly simplied to me. Basically the simplest case in which two hosts using the same policy is analyzed. However, in more complicated cases like many hosts with different parameters, what will happen will be interesting. And just as the authors pointed out, as the feedback is delayed and all hosts are acting asynchronously rather than synchronously, how these factors impact the convergence, efficiency and fairness of the system are still unsolved problems.