Design Space Exploration in Cyber-Physical Systems

Cyber physical systems (CPS) integrate a variety of engineering areas such as control, mechanical and computer engineering in a holistic design effort. While interdependencies between the different disciplines are key attributes of CPS design science, little is known about the impact of design decisions of the cyber part on the overall system qualities. To investigate these interdependencies, this paper proposes a simulation-based Design Space Exploration (DSE) framework that considers detailed cyber system parameters such as cache size, bus width, and voltage levels in addition to physical and control parameters of the CPS. We propose an exploration algorithm that surfs the parameter configurations in the cyber physical sub-systems, in order to approximate the Pareto-optimal design points with regards to the trade-os among the design objectives, such as energy consumption and control stability. We apply the proposed framework to a network control system for an inverted-pendulum application. The presented holistic evaluation of the identified Pareto-points reveals the presence of non-trivial trade-os, which are imposed by the control, physical, and detailed cyber parameters. For instance the identified energy and control optimal design points comprise configurations with a wide range of CPU speeds, sample times and cache configuration following non-trivial zig-zag patterns. The proposed framework could identify and manage those trade-os and, as a result, is an imperative rst step to automate the search for superior CSP configurations

Design Space Exploration for Distributed Cyber-Physical Systems: State-of-the-art, Challenges, and Directions

Computer Systems, Imagery and Medi

Digital and Analogue interactions:Process Chain Networks for the Design of Service Processes

Publisher PD

Task-driven Modular Co-design of Vehicle Control Systems

When designing autonomous systems, we need to consider multiple trade-offs at various abstraction levels, and the choices of single (hardware and software) components need to be studied jointly. In this work we consider the problem of designing the control algorithm as well as the platform on which it is executed. In particular, we focus on vehicle control systems, and formalize state-of-the-art control schemes as monotone feasibility relations. We then show how, leveraging a monotone theory of co-design, we can study the embedding of control synthesis problems into the task-driven co-design problem of a robotic platform. The properties of the proposed approach are illustrated by considering urban driving scenarios. We show how, given a particular task, we can efficiently compute Pareto optimal design solutions.Comment: 8 pages, 7 figures. Proceedings of the 2022 IEEE 61th Conference on Decision and Contro

CONTREX: Design of embedded mixed-criticality CONTRol systems under consideration of EXtra-functional properties

The increasing processing power of today’s HW/SW platforms leads to the integration of more and more functions in a single device. Additional design challenges arise when these functions share computing resources and belong to different criticality levels. CONTREX complements current activities in the area of predictable computing platforms and segregation mechanisms with techniques to consider the extra-functional properties, i.e., timing constraints, power, and temperature. CONTREX enables energy efficient and cost aware design through analysis and optimization of these properties with regard to application demands at different criticality levels. This article presents an overview of the CONTREX European project, its main innovative technology (extension of a model based design approach, functional and extra-functional analysis with executable models and run-time management) and the final results of three industrial use-cases from different domain (avionics, automotive and telecommunication).The work leading to these results has received funding from the European Community’s Seventh Framework Programme FP7/2007-2011 under grant agreement no. 611146

Data flow analysis from UML/MARTE models based on binary traces

The design of increasingly complex embedded systems requires powerful solutions from the very beginning of the design process. Model Based Design (MBD) and early simulation have proven to be capable technologies to perform initial design space analysis to optimize system design. Traditional MBD methods and tools typically rely on fixed elements, which makes difficult the evaluation of different platform configurations, communication alternatives or models of computation. Addressing these challenges require flexible design technologies able to support, from a high-level abstract model, full design space exploration, including system specification, binary generation and performance evaluation. In this context, this paper proposes a UML/MARTE based approach able to address the challenges mentioned above by improving design flexibility and evaluation capabilities, including automatic code generation, trace execution collection and trace analysis from the initial UML models. The approach focuses on the definition and analysis of the paths data follow through the different application components, as a way to understand the behavior or the different design solutions.This work has been funded by the EU and the Spanish MICINN/AEI through the ECSEL Comp4Drones and the TEC2017-86722-C4-3-R PLATINO projects

Mega-modeling of complex, distributed, heterogeneous CPS systems

Model-Driven Design (MDD) has proven to be a powerful technology to address the development of increasingly complex embedded systems. Beyond complexity itself, challenges come from the need to deal with parallelism and heterogeneity. System design must target different execution platforms with different OSs and HW resources, even bare-metal, support local and distributed systems, and integrate on top of these heterogeneous platforms multiple functional component coming from different sources (developed from scratch, legacy code and third-party code), with different behaviors operating under different models of computation and communication. Additionally, system optimization to improve performance, power consumption, cost, etc. requires analyzing huge lists of possible design solutions. Addressing these challenges require flexible design technologies able to support from a single-source model its architectural mapping to different computing resources, of different kind and in different platforms. Traditional MDD methods and tools typically rely on fixed elements, which makes difficult their integration under this variability. For example, it is unlikely to integrate in the same system legacy code with a third-party component. Usually some re-coding is required to enable such interconnection. This paper proposes a UML/MARTE system modeling methodology able to address the challenges mentioned above by improving flexibility and scalability. This approach is illustrated and demonstrated on a flight management system. The model is flexible enough to be adapted to different architectural solutions with a minimal effort by changing its underlying Model of Computation and Communication (MoCC). Being completely platform independent, from the same model it is possible to explore various solutions on different execution platforms.This work has been partially funded by the EU and the Spanish MICINN through the ECSEL MegaMart and Comp4Drones projects and the TEC2017-86722-C4-3-R PLATINO project

Product-Production-CoDesign: An Approach on Integrated Product and Production Engineering Across Generations and Life Cycles

Shorter product life cycles and high product variance nowadays require efficient engineering of products and production systems. Hereby a further challenge is that costs over the entire life cycle of the product and production system are defined early in the process. Existing approaches in literature and practice such as simultaneous engineering and design for manufacturing incorporate aspects of production into product engineering. However, these approaches leave potential for increasing efficiency unused because knowledge from past generations of products, production systems, and business models is not stored and reused in a formalized way and future generations are not considered in the respective current engineering process. This article proposes an approach for integrated product and production engineering across generations and life cycles of products and production systems. This includes the consideration of related business models to successfully establish the products on the market as well as the anticipation of future product and production system characteristics. The presented approach can reduce both development and manufacturing costs as well as time to market and opens the vast technological potential for product design to achieve additional customer benefits. Three case studies elaborate on aspects of the proposed approach and present its benefits