Admission control and resource management for multi‐service ATM networks

We propose a resource allocation scheme that takes into account both the QoS requirements and the characteristics of traffic streams. In our scheme, the decision to allocate buffer and bandwidth resources to a QoS class depends on whether buffering will be effective in reducing loss probability for this class. We present analytical techniques based on the theory of large deviations for estimating the small loss probability. Furthermore, we address the problem of accepting calls with incomplete traffic statistics. Existing proposals of traffic descriptors call for specification of only the first‐order statistics such as the peak rate and the sustainable cell rate. To guarantee QoS, the admission policy must be conservative by assuming the worst‐case distribution compliant to the traffic descriptor. We demonstrate that on–off sources exhibit such worst‐case behavior. However, a static conservative policy results in under‐utilization of network resources. We devise and analyze dynamic algorithms that improve the estimates of the actual bandwidth requirements for existing sources by collecting information on‐line. We show that a direct approach, where the quantity measured is the QoS of interest, combined with an extrapolation technique to speed up the estimation process, offers a promising solution.