An analysis of impacts of long-term traffic correlations on congestion control in ATM-based local computer networks

We analyse the impacts of the long-term correlations discovered in data and video traffic on congestion control in ATM-based local area networks based on catastrophe theory. Our work shows that long-term correlations may cause the network performance to degrade catastrophically even if the cell rate of the traffic source can be adjusted dynamically according to the network load and the peak cell rate can be bounded effectively. Experimental evidence exists supporting our analytical results. Therefore, without taking traffic correlations into account, congestion control and quality-of-service guarantees may not be effective.