This paper discusses the perspective of the H2020 TEACHING project on the next generation of autonomous applications running in a distributed and highly heterogeneous environment comprising both virtual and physical resources spanning the edge-cloud continuum. TEACHING puts forward a human-centred vision leveraging the physiological, emotional, and cognitive state of the users as a driver for the adaptation and optimization of the autonomous applications. It does so by building a distributed, embedded and federated learning system complemented by methods and tools to enforce its dependability, security and privacy preservation. The paper discusses the main concepts of the TEACHING approach and singles out the main AI-related research challenges associated with it. Further, we provide a discussion of the design choices for the TEACHING system to tackle the aforementioned challenges Index Terms-distributed neural networks, human-centred artificial intelligence, cyber-physical systems, ubiquitous and pervasive computing, edge artificial intelligence
EAST-ADL is an architecture description language (ADL) for model-based development of automotive embedded systems. The formalization of domain-specific engineering information and methodology brings a potential for a wide range of benefits for information management, system design and integration, tool interaction, documentation and communication. This paper describes the EAST-ADL language support for safety requirements, faults/failures, hazards and safety constraints in the context of ISO/DIS 26262 reference safety lifecycle. Based on the language support, the safety related information can be derived and managed seamlessly along with its target nominal system architecture model with multiple abstraction levels and view extensions. Through model transformation and tool integration, automated safety analysis is allowed.Integrierte Sicherheits-und Architekturmodelle fü r automotive eingebettete Systeme. EAST-ADL ist eine Architekturbeschreibungssprache (ADL) fü r die modellbasierte Entwicklung von eingebetteten Systemen im Bereich der Fahrzeugtechnik. Die Formalisierung von Domä nen-spezifischen Informationen und Methoden bringt einen Mehrwert fü r eine breite Palette von Anwendungen in den Bereichen Informationsmanagement, Systemdesign und Integration, Toolketten, Dokumentation und Kommunikation. Diese Publikation beschreibt die EAST-ADL-Unterstü tzung fü r Sicherheitsanforderungen und -bedingungen, Gefahren, Fehler und Stö rungen im Kontext des ISO 26262-Phasenmodells. Basierend auf dieser Sprachunterstü tzung kö nnen sicherheitsbezogene Informationen abgeleitet und nahtlos mit dem dazugehö rigen Architekturmodell verwaltet werden. Dieses berü cksichtigt verschiedene Abstraktionsebenen und Sichtweisen. Die Modelltransformation und Integration verschiedener Softwarewerkzeuge erlaubt so eine automatisierte Sicherheitsanalyse. Schlü sselwö rter: EAST-ADL; ISO/DIS 26262; funktionale Sicherheit; Fehlermodell
We present on-line tunable diagnostic and membership protocols for generic time-triggered (TT) systems to detect crashes, send/receive omission faults and network partitions. Compared to existing diagnostic and membership protocols for TT systems, our protocols do not rely on the single-fault assumption and also tolerate non fail-silent (Byzantine) faults. They run at the application level and can be added on top of any TT system (possibly as a middleware component) without requiring modifications at the system level. The information on detected faults is accumulated using a penalty/reward algorithm to handle transient faults. After a fault is detected, the likelihood of node isolation can be adapted to different system configurations, including configurations where functions with different criticality levels are integrated. All protocols are formally verified using model checking. Using actual automotive and aerospace parameters, we also experimentally demonstrate the transient fault handling capabilities of the protocols.
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