Objectives
Cyber-Physical-Systems (CPS) harbor the potential for vast economic and societal impact in domains such as mobility, home automation and delivery of health. At the same time, if such systems fail they may harm people and lead to temporary collapse of important infrastructures with catastrophic results for industry and society. Thus, ensuring the dependability of such (CPS) systems is the key to unlocking their full potential and enabling European industries to confidently develop business models that will nurture their societal uptake.
The open and cooperative nature of CPS poses a significant new challenge in assuring dependability. The DEIS project addresses this important and unsolved challenge by developing technologies that form a science of dependable system integration. In the core of these technologies lies the concept of a Digital Dependability Identity (DDI) of a component or system. DDIs are composable and executable in the field facilitating (a) efficient synthesis of component and system dependability information over the supply chain and (b) effective evaluation of this information in-the-field for safe and secure composition of highly distributed and autonomous CPS. This concept shall be deployed and evaluated in four use cases:
> Automotive: development of a stand-alone system for intelligent physiological parameter monitoring
> Automotive: enhancement of an advanced driver simulator for evaluation of automated driving functions
> Railway: Plug-and-play environment for heterogeneous railway systems enabling dependable exchange of information between components and subsystems
> Healthcare enhancement of clinical decision app for oncology professional targeting higher degree of dependability for ad-hoc systems
Approach
The DEIS project relies on three technology stages and their respective application in four industrial use cases, see Figure 1. Consequently, the technical approach is divided into the four following steps
1. Setup of an Open Dependability Exchange (ODE) Metamodel as a universal format for specifying DDIs to support exchange of dependability information. This environment shall integrate (a) a metamodel defining an ontology for dependability, (b) syntax and semantics of DDIs as a metamodel and transformation rules to generate DDIs based on ODE, as well as (c) tooling support for the modeling and analysis of DDIs
2. Framework for the creation and modular synthesis of DDIs to support efficient dependability assurance across industries and value chains during design time. This framework comprises (a) tooling support for expressing existing dependability models in ODE-compliant format, and (b) algorithms and tooling support for synthesis of DDIs, integration into dependability assurance cases and supporting change-impact analyses
3. Framework for the in-the-field dependability assurance in CPS to enable dependable integration of systems in the field. This next framework has two objectives: (a) development of infrastructures for evaluation of integration of new systems in the field, and (b) development of algorithms for the on-board evaluation of DDIs
4. Development of autonomous and connected CPS use cases for different application domains, and validation of applicability and scalability of the DDIs. This last step targets the application of the different DDIs steps in different relevant industrial use cases
