In this paper, a simplified practical method for dimensioning asynchronous transfer mode (ATM) systems is proposed. Packet switching services are classified into two categories: connection-oriented packet switching (COPS) with quality of service (QoS) guaranteed and connection-less packet switching (CLPS) on a best effort basis. A new control scheme is proposed for maintaining the cell-level QoS requirement for the COPS even in overload conditions. A dimensioning method is also proposed for the system where the COPS is served with nonpreemptive priority over the CLPS. The methods proposed are expected to contribute to the realization of robust and economical ATM systems.

In broadband ISDN with ATM, various kinds of traffic, such as voice, data and video, share the common transmission resource. For such multiclass traffic systems, it is necessary to evaluate the grade of service (GOS) for individual traffic. In particular, for the ATM networks integrating voice and video which are of bursty property and delay sensitive, the individual performance evaluation for the mixed bursty traffic an important problem. The authors propose a simplified evaluation of the individual mean waiting time for the bursty multiclass systems appearing in the ATM network and show numerical examples for voice/video system.>

The single-server general queuing model G1/G/1 is studied for a modified Erlangian input that covers a wide range of bursty and nonbursty input processes. The E/sub k//G/1 model is analyzed using spectral factorization, and explicit form performance is evaluated in terms of the mean and variance of the waiting time.>

An approximate evaluation is proposed for the individual mean waiting time, and loss probability for mixed delay and loss (nondelay) systems with renewal and Poisson inputs handled by servers with exponential service time. The approximation is based on the GI approximation previously proposed by H. Akimaru, et al. (1983, 1985), in which the mixed input process is regarded as renewal. The systems with mixed delay renewal and nondelay Poisson inputs, and ones with mixed nondelay renewal and delay Poisson inputs are analyzed. Approximate formulas for the mean waiting time and loss probability for the respective inputs are presented in simple closed form, and comparisons to simulations show good accuracy. The formulas are expected to be useful for analysis and optimum design of the mixed delay and loss systems.>

Telecommunications networks have been designed to maintain predetermined service levels for time-varying traffic loads. This inevitably causes redundant investments, and thus, there are possibilities for further economization by adaptively controlling the systems. In order to establish the optimum strategy of controlling telecommunications networks, it is essential to study time dependent traffic characteristics. This paper analyzes a system in which a time-dependent Poisson input is offered to a finite primary trunk group, and the overflow traffic is carried by an infinite secondary trunk group. Methods for calculating the mean and variance of the overflow traffic (the number of calls existing in the secondary group) are proposed, including an approximate evaluation for which accuracy is examined. Calculated examples are given for various time dependent inputs, and properties of the overflow traffic are discussed. The methods and results presented will be useful for analysis and optimum design of the network systems with time dependent traffic.

A simple approximate formula for estimating individual call losses in overflow systems is derived using the interrupted Poisson process. The formula presents good accuracy in the single-overflow model, and it is also applicable to the multioverflow model. It is expected that the present formula is useful for the optimization of systems under given service criteria.

This paper reveals the general structure of the asymptotic expansion for the Erlang loss function and its derivative. A recursive formula for the coefficients in the expansion is given and some of numerical examples are presented. The truncation error of the expansion is estimated and charts for calculation with the error less than 0.1 percent are shown. The present formula facilitates the calculation by saving the computation time, and it is useful for the optimization problems of switching systems and other applications.