The classical M/G/1 system with vacations has been used to estimate the mean waiting time of individual priority classes of homogeneous FDDI networks. To faithfully model the FDDI network using M/G/1 system, the vacation interval of the server (token) as seen by individual priority classes must be evaluated. The expressions for the mean waiting time of individual priority classes are functions of first and second moments of the vacation intervals of that class. It can be shown that the expression derived for the first and second moments of the vacation intervals of the respective classes are functions of the mean and variance of number of messages transmitted by each priority class per token rotation. These expressions are evaluated using an iterative procedure that utilizes the prior knowledge of the throughput characteristics of the FDDI network. Simulation results show that the model provides accurate estimates for the mean waiting time of individual priority classes of a homogeneous FDDI network.

A three dimensional (3-D) reconstruction algorithm utilizing both linear interpolation and linear extrapolation was developed for the study of human prostatic cancer. The algorithm was validated by comparing the volumes and shapes of original to reconstructed objects. Synthetic objects of known geometry and wax models with shapes characteristic of prostatic carcinomas were assessed with standard planimetry and by the digital interpolation-extrapolation method. Volume and multifocality measurements obtained by reconstructing excised prostate glands using histologic maps obtained from whole-mount sections were tested. The new algorithm provided greater accuracy in determining tumor volumes than conventional methods. This model provides a basis for mathematical analysis of prostate cancer lesions.

The fiber distributed data interface (FDDI) standard supports synchronous and asynchronous data transmissions. It allows each station to have multiple classes of asynchronous data, and meets the requirements of different classes by means of a timer-based priority scheme. The performance of a FDDI network carrying multiple classes of traffic is considered. An analytical model is presented to evaluate the throughput of synchronous traffic and asynchronous traffic. The model can be used to evaluate the throughput of individual priority classes and the mean token-cycle time of the network, when the network offered load varies from very low values to high values. The governing equations for the throughput characteristics and mean token-cycle time are strictly functions of network parameters. Simulations are used to verify the analytical model. Simulation results are also used to examine the variation of the mean access delay characteristics of various classes and the token-cycle time distribution of the priority scheme. Limitations of the model are outlined.>

The performance of the timer-based priority scheme of the fiber distributed data interface (FDDI) network is investigated. The token-cycle time distribution illustrating the mechanics of the priority scheme is presented. Analytical expressions are given to evaluate the first and the second moments of the token-cycle time for FDDI networks with multiple classes of traffic. An iterative procedure that uses the knowledge of the throughput characteristics is utilized to solve these analytical expressions. The worst case confidance intervals are given. Simulation results are presented for homogeneous and heterogeneous networks with multiple classes of traffic highlighting the token-cycle time variation when the network load changes from a low value to a substantially high value.

An analytical model is presented to evaluate the throughput of synchronous traffic and asynchronous traffic. This model can be used to evaluate the throughput of individual priority classes and the mean token-cycle time of the network. A method of selecting timers to support integrated synchronous and asynchronous traffic in FDDI (fiber distributed data interface) is presented. Simulations are used to verify the analytical model. Simulation results are also used to examine the variation of the mean message-delay characteristics of various classes. Limitations of the model are outlined.>