Advances in real-time systems
TimeNET: a toolkit for evaluating non-Markovian stochastic Petri nets
Performance Evaluation - Special issue: performance modeling tools
Advances in Real-Time Systems
A Characterization of the Stochastic Process Underlying a Stochastic Petri Net
IEEE Transactions on Software Engineering
Exploiting parallelism in high performance embedded system scheduling
HIPC '96 Proceedings of the Third International Conference on High-Performance Computing (HiPC '96)
Discrete Time Stochastic Petri Nets for the Modeling and Evaluation of Real-Time Systems
IPDPS '01 Proceedings of the 15th International Parallel & Distributed Processing Symposium
Towards a Middleware Approach for a Self-configurable Automotive Embedded System
SEUS '08 Proceedings of the 6th IFIP WG 10.2 international workshop on Software Technologies for Embedded and Ubiquitous Systems
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This paper describes an on-going effort in constructing a platfonnfor 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 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 perfonnance evaluation are presented.