TiLA: Twin-in-the-Loop Architecture for Cyber-Physical Production Systems

Digital twin is a virtual replica of a real-world object that lives simultaneously with its physical counterpart. Since its first introduction in 2003 by Grieves, digital twin has gained momentum in a wide range of applications such as industrial manufacturing, automotive and artificial intelligence. However, many digital-twin-related approaches, found in industries as well as literature, mainly focus on modelling individual physical things with high-fidelity methods with limited scalability. In this paper, we introduce a digital-twin architecture called TiLA (Twin-in-the-Loop Architecture). TiLA employs heterogeneous models and online data to create a digital twin, which follows a Globally Asynchronous Locally Synchronous (GALS) model of computation. It facilitates the creation of a scalable digital twin with different levels of modelling abstraction as well as giving GALS formalism for execution strategy. Furthermore, TiLA provides facilities to develop applications around the twin as well as an interface to synchronise the twin with the physical system through an industrial communication protocol. A digital twin for a manufacturing line has been developed as a case study using TiLA. It demonstrates the use of digital twin models together with online data for monitoring and analysing failures in the physical system

Demo Abstract: Contract-based Hierarchical Resilience Framework for Cyber-Physical Systems

This demonstration presents a framework for building a resilient Cyber-Physical Systems (CPS) cyber-infrastructure through the use of hierarchical parametric assume-guarantee contracts. A Fischertechnik Sorting Line with Color Detection training model is used to showcase our framework.Comment: 2 pages, 5 figures, published in the Demo Session of IEEE International Conference on Cyber-Physical Systems 2019. Publication rights licensed to AC

Deterministic, Predictable and Light-Weight Multithreading Using PRET-C

International audienceWe present a new language called Precision Timed C called PRET-C, for predictable and lightweight multithreading in C. PRET-C supports synchronous concurrency, preemption, and a high-level construct for logical time. In contrast to existing synchronous languages, PRET-C offers C-based shared memory communications between concurrent threads, which is guaranteed to be thread safe via the proposed semantics. Mapping of logical time to physical time is achieved by a Worst Case Reaction Time (WCRT) analyser. To improve throughput while maintaining predictability, a hardware accelerator specifically designed for PRET-C is added to a soft-core processor. We then demonstrate through extensive benchmarking that the proposed approach not only achieves complete predictable execution, but also improves overall throughput when compared to the software execution of PRET-C. The PRET-C software approach is also significantly more efficient in comparison to two other light-weight concurrent C variants called SC and Protothreads, as well as the well-known synchronous language Esterel

Predictable Multithreading of Embedded Applications Using PRET-C

International audienceWe propose a new language called Precision Timed C (PRET-C), for predictable and lightweight multithreading in C. PRET-C supports synchronous concurrency, preemption, and a high-level construct for logical time. In contrast to existing synchronous languages, PRET-C offers C-based shared memory communications between concurrent threads that is guaranteed to be thread safe. Due to the proposed synchronous semantics, the mapping of logical time to physical time can be achieved much more easily than with plain C, thanks to a Worst Case Reaction Time (WCRT) analyzer (not presented here). Associated to the PRET-C programming language, we present a dedicated target architecture, called ARPRET, which combines a hardware accelerator associated to an existing softcore processor. This allows us to improve the throughput while preserving the predictability. With extensive benchmarking, we then demonstrate that ARPRET not only achieves completely predictable execution of PRET-C programs, but also improves the throughput when compared to the pure software execution of PRET-C. The PRET-C software approach is also significantly more efficient in comparison to two other light-weight concurrent C variants (namely SC and Protothreads), as well as the well-known Esterel synchronous programming language

Tight WCRT Analysis for Synchronous C Programs

Accurate estimation of the tick length of a synchronous program is essential for efficient and predictable implementations that are devoid of timing faults. The techniques to determine the tick length statically are classified as worst case reaction time (WCRT) analysis. While a plethora of techniques exist for worst case execution time (WCET) analysis of procedural programs, there are only a handful of techniques for determining the WCRT value of synchronous programs. Most of these techniques produce overestimates and hence are unsuitable for the design of systems that are predictable while being also efficient. In this paper, we present an approach for the accurate estimation of the exact WCRT value of a synchronous program, called its tight WCRT value, using model checking. For our input specifications we have selected a synchronous C based language called PRET-C that is designed for programming Precision Timed (PRET) architectures. We then present an approach for static WCRT analysis of these programs via an intermediate format called TCCFG. This intermediate representation is then compiled to produce the input for the model checker. Experimental results that compare our approach to existing approaches demonstrate the benefits of the proposed approach. The proposed approach, while presented for PRET-C is also applicable for WCRT analysis of Esterel using simple adjustments to the generated model. The proposed approach thus paves the way for a generic approach for determining the tight WCRT value of synchronous programs at compile time

Memory-aware embedded control systems design

Control applications are often implemented on highly cost-sensitive and resource-constrained embedded platforms, such as microcontrollers with a small on-chip memory. Typically, control algorithms are designed using model-based approaches, where the details of the implementation platform are completely ignored. As a result, optimizations that integrate platform-level characteristics into the control algorithms design are largely missing. With the emergence of cyber-physical systems (CPS)-oriented thinking, there has lately been a strong interest in co-design of control algorithms and their implementation platforms, leading to work on networked control systems and computation-aware control algorithms design. However, there has so far been no work on integrating the characteristics of a memory architecture into the design of control algorithms. In this paper we, for the first time, show that accounting for the impact of on-chip memory (or cache) reuse on the performance of control applications motivates new techniques for control algorithms design. This leads to significant improvement in quality of control for given resource availability, or more efficient implementations of embedded control applications. We believe that this paper opens up a variety of possibilities for memory-related optimizations of embedded control systems, that will be pursued by researchers working on computer-aided design for CPS

Precise timing analysis for direct-mapped caches

International audienceSafety-critical systems require guarantees on their worst-case execution times. This requires modelling of speculative hardware features such as caches that are tailored to improve the average-case performance, while ignoring the worst case, which complicates the Worst Case Execution Time (WCET) analysis problem. Existing approaches that precisely compute WCET suffer from state-space explosion. In this paper, we present a novel cache analysis technique for direct-mapped instruction caches with the same precision as the most precise techniques, while improving analysis time by up to 240 times. This improvement is achieved by analysing individual control points separately, and carrying out optimisations that are not possible with existing techniques