Abstract. The determination of upper bounds on execution times, commonly called WorstCase Execution Times (WCETs), is a necessary step in the development and validation process for hard real-time systems. This problem is hard if the underlying processor architecture has components such as caches, pipelines, branch prediction, and other speculative components. This article describes different approaches to this problem and surveys several commercially available tools and research prototypes.
Real-time systems need time-predictable platforms to allow static analysis of the worst-case execution time (WCET). Standard multi-core processors are optimized for the average case and are hardly analyzable. Within the T-CREST project we propose novel solutions for time-predictable multi-core architectures that are optimized for the WCET instead of the average-case execution time. The resulting time-predictable resources (processors, interconnect, memory arbiter, and memory controller) and tools (compiler, WCET analysis) are designed to ease WCET analysis and to optimize WCET performance. Compared to other processors the WCET performance is outstanding.The T-CREST platform is evaluated with two industrial use cases. An application from the avionic domain demonstrates that tasks executing on different cores do not interfere with respect to their WCET. A signal processing application from the railway domain shows that the WCET can be reduced for computation-intensive tasks when distributing the tasks on several cores and using the network-on-chip for communication. With three cores the WCET is improved by a factor of 1.8 and with 15 cores by a factor of 5.7.The T-CREST project is the result of a collaborative research and development project executed by eight partners from academia and industry. The European Commission funded T-CREST.
Increasingly complex systems lead to an interweaving of security, safety, availability and reliability concerns. Most dependability analysis techniques do not include security aspects. In order to include security, a holistic risk model for systems is needed. In our novel approach, the basic failure cause, failure mode and failure effect model known from FMEA is used as a template for a vulnerability cause-effect chain, and an FMEA analysis technique extended with security is presented. This represents a unified model for safety and security cause-effect analysis. As an example the technique is then applied to a distributed industrial measurement system.
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