A Holistic Approach to Functional Safety for Networked Cyber-Physical Systems

Functional safety is a significant concern in today's networked cyber-physical systems such as connected machines, autonomous vehicles, and intelligent environments. Simulation is a well-known methodology for the assessment of functional safety. Simulation models of networked cyber-physical systems are very heterogeneous relying on digital hardware, analog hardware, and network domains. Current functional safety assessment is mainly focused on digital hardware failures while minor attention is devoted to analog hardware and not at all to the interconnecting network. In this work we believe that in networked cyber-physical systems, the dependability must be verified not only for the nodes in isolation but also by taking into account their interaction through the communication channel. For this reason, this work proposes a holistic methodology for simulation-based safety assessment in which safety mechanisms are tested in a simulation environment reproducing the high-level behavior of digital hardware, analog hardware, and network communication. The methodology relies on three main automatic processes: 1) abstraction of analog models to transform them into system-level descriptions, 2) synthesis of network infrastructures to combine multiple cyber-physical systems, and 3) multi-domain fault injection in digital, analog, and network. Ultimately, the flow produces a homogeneous optimized description written in C++ for fast and reliable simulation which can have many applications. The focus of this thesis is performing extensive fault simulation and evaluating different functional safety metrics, \eg, fault and diagnostic coverage of all the safety mechanisms

Conservative Behavioural Modelling in SystemC-AMS

SystemC has recently been extended with the Analogue and Mixed Signal (AMS) library, with the ultimate goal of providing simulation support to analogue electronics and continuous time behaviours. SystemC-AMS allows modelling of systems that are either conservative and extremely low level or continuous time and behavioural, which is limited compared to other AMS HDLs. This work faces up this challenge, by extending SystemCAMS support to a new level of abstraction, called Analogue Behavioural Modelling (ABM), covering models that are both behavioural and conservative. This leads to a methodology that uses SystemC-AMS constructs in a novel way. Full automation of the methodology allows proof of its effectiveness both in terms of accuracy and simulation performance, and application of the overall approach to a complex industrial Micro Electro- Mechanical System (MEMS) case study. The effectiveness of the proposed approach is further highlighted in the context of virtual platforms for smart systems, as adopting a C++-based language for MEMS simulation reduces the simulation time by about 2x, thus enhancing the design and integration flo