Abstract
This paper describes an on-going effort in constructing a platform for developing distributed, embedded, real-time control systems which have high dependability and scalability requirements. Complex, embedded real-time control systems typically have a very large grain task model upon which hard and soft timing constraints are simultaneously imposed. Often, such systems are required to function in extremely hostile and unpredictable environments. This demands large dependability and availability in a continuous manner. We describe a new paradigm to build such systems which is based on the notion of {\it paths} - the granularity at which the notion of time is expressed in software. Further, the paper describes distributed middleware services that are being developed to provide dependable, adaptive dynamic resource management. To illustrate the approach, an automobile air bag control system is used as an application example. Path descriptions can be applied in system design or system maintenance and during run time optimization. Within this framework, model based evaluation is often required. Therefore, in the second part of the paper a modeling approach for paths based on Stochastic Petri Nets is described, and results of a performance evaluation are presented.