| Abstract: | It is expected that a significant part of the data flows of future multi‐service packet switched backbone networks will use low priority, non‐real‐time data transmission services of the networks. The common benefit for both user applications and network operators is that the data flows of the low priority services could use the free capacity of the networks, after the load of higher priority data flows. Congestion control methods are needed for these low priority data flows to reach an optimal utilisation level of the networks, high throughput and low packet loss ratios. This kind of low priority data transmission service which adjusts the data rates of the data flows according to the data rate changes of higher priority data flows, but does not guarantee any specific service for these data flows, is called a controlled load service. In this paper, we have compared the performance, efficiency and scalability of four different congestion control methods designed for the controlled load service. Two of these methods were based on very simple congestion control algorithms and the other two used relatively complex control algorithms based on control methods utilising computational intelligence. The principal aim of this study was to research how remarkable were the effects that the different complexities of the congestion control methods had on the achieved level of service. The simulation tests indicate that the complexity of the methods clearly affects the performance and efficiency of the methods. Copyright © 2001 John Wiley & Sons, Ltd. |
