Resource allocation is necessary for a network which guarantees quality of service (QoS). In this paper we first present a definition for a traffic stream to be burstier than another traffic stream. The definition is based on the loss probability of a bufferless multiplexer and thus is appropriate for delay-sensitive traffic which cannot tolerate queueing delay caused by buffering. An optimum quantization algorithm is then derived for source characterization. The optimally quantized version achieves minimum loss rate for all possible allocated bandwidths under the condition that it is burstier than the real traffic. The quantized source is called a pseudosource and can be used by the network for resource allocation. Some numerical examples are studied. Results show that, for a bufferless multiplexer, the allocated bandwidth based on optimally quantized pseudosources is only slightly greater than the minimum bandwidth required to meet the requested QoS.

We present a definition of burstiness for delay sensitive traffic streams in terms of a function, i.e., the cell loss probability of a bufferless multiplexer at all non-negative link capacities. Some properties of the definition are proved. One property implies any definition of burstiness in terms of a real number may not be appropriate. The other property implies the commonly used moment matching method in approximating traffic sources may not be appropriate either. We also present a quantization algorithm for networks which provide only finitely many bit rates for describing traffic characteristics. Our proposed quantization algorithm guarantees the quantized version is always burstier than the original source and thus can be used to design call admission control scheme for an ATM network.

In this paper, we present a real-time computation algorithm based on the bufferless fluid flow model [Jabbari and Yegenolu, 1992] for call admission control (CAC) on one link of an asynchronous transfer mode (ATM) network with heterogeneous bursty traffic. Cell loss probability is adopted as the measure of quality-of-service (QoS). Our computation algorithm requires a constant memory size and needs only two multiplications and one division to determine whether a connection request can be accepted or not. It is known [Murase et al., 1991], that due to the interference between different types of traffic the individual cell loss probability may not meet the requirement even though the global one does. In this paper, we provide a close upper-bound for individual cell loss probability which can easily be obtained with our computation algorithm. Numerical examples using typical traffic parameters are studied to corroborate the upper-bound. We also compare the performance of the investigated CAC scheme with that of the effective bandwidth technique [Elwalid and Mitra, 1993].