The concept of picture archiving and communication systems (PACS) is now widely accepted in the medical community. In order to bring the concept to reality, however, innovative designs and implementations are needed. One such design is a fiber-optic star-based PACS. This PACS network is based on a multiplexed passive star local area network with wavelength-division multiplexing to provide separate logical channels for transfer of control and image data. The system consists of an image network (INET), for image transfer at a rate of 140 Mbps, and a control network (CNET), operating at 10 Mbps, for mediating the flow of image transfers. INET is a circuit switched network devoted solely to image transfer, while CNET employs the CSMA/CD protocol for bus arbitration. Before such a system can be deployed, an accurate evaluation study must be carried out to estimate its performance characteristics. Such evaluations are complicated both by the complexity of the PACS itself and the varied demands that are placed on such a system. A novel approach based on stochastic activity networks, a stochastic extension of Petri nets, is useful in this regard. Stochastic activity networks were used to develop a detailed model of the command and image channels. The performance of the system was then evaluated under realistic workload conditions. In particular, we were able to estimate a number of important performance variables including the image response time, command channel delay, and queue length at each type of node and the network supervisor. The results 1) show that stochastic activity networks are an appropriate model type for evaluating picture archiving and communication systems, 2) delineate the workload conditions under which PACS may effectively operate, and 3) show that even when these conditions are exceeded, the command channel load remains extremely light. Results of this type are useful both to designers of other PACS networks and those interested in this particular PACS design.
ASJC Scopus subject areas
- Radiological and Ultrasound Technology
- Computer Science Applications
- Electrical and Electronic Engineering