A SURVEY OF STRAIGHTFORWARD STATISTICAL MULTIPLEXING MODELS FOR ATM NETWORKS

Connection Acceptance Control (CAC) is probably the most important fun ction in the preventive congestion control strategy to be implemented in ATM networks. The CAC function must decide, on the basis of the tra ffic descriptors provided by an incoming connection, whether the new c all can be accepted or not. A key factor in the access decision is the behaviour of the superposition of ATM VCs in a switch output buffer, and in particular the cell loss probability resulting from accepting t he connection. Many models have been proposed in the literature in ord er to investigate this issue. In this paper, we present a survey of th e queuing models used to estimate the cell loss probability in ATM net works with straightforward statistical multiplexing. The CAC policy un der consideration is based on the so-called Worst Case Traffic allocat ion corresponding to the traffic descriptor parameters submitted by a VC: its peak cell rate, cell delay variation tolerance, sustainable ce ll rate, and intrinsic burst tolerance parameters, when applicable. We plan to investigate the practical application of these models to the problem of CAC; in particular, the important issues of accuracy of the available models, their range of validity and their complexity deserv e more attention than they have received up to now. The present survey stands as a first step in that direction.