The AUTOSAR consortium proposed the AUTOSAR Adaptive standard to tackle the challenges introduced by the design of modern automotive systems. It consists of a service-oriented architecture (SoA) implemented in C++ and built on top of POSIX operating systems. However, unlike the previous AUTOSAR Classic specifications, this novel standard does not address non-functional requirements, including determinism, which is of key importance to guarantee the system's functional safety. This paper proposes a modeling extension to the AUTOSAR Adaptive standard aiming at guaranteeing a deterministic execution by leveraging the System-Level Logical Execution Time (SL-LET) paradigm, already used in the context of AUTOSAR Classic. A prototype implementation is also proposed, which is used to experimentally corroborate the feasibility of the proposed model extension with an evaluation based on a realistic automotive application built on the official AUTOSAR Adaptive Platform Demonstrator (APD).

The automotive software industry is facing a paradigm shift driven by the need to develop more and more advanced functionality distributed on multiple electronic control units. The AUTOSAR Adaptive standard has been designed as a service-oriented architecture on top of a general-purpose operating system to tackle this paradigm shift. Nevertheless, it does not provide means to ensure deterministic communication, as required in safety-related components. This paper studies the integration of the System-Level Logical Execution Time (SL-LET) paradigm in AUTOSAR Adaptive. The key design challenges and requirements to support SL-LET in AUTOSAR Adaptive are described, highlighting how to overcome the considerable differences between the AUTOSAR Classic and Adaptive domains. Then, a meta-protocol named AP-LET is presented, together with two concrete instances: one based on high-priority tasks and another leveraging timestamps in the message payload to handle communications and ensure determinism. A complete implementation of both protocols is also described. AP-LET was finally evaluated with a realistic automotive application, showing its feasibility and effectiveness.

Modern autonomous systems integrate diverse soft-ware solutions to manage tightly communicating functionalities. These applications commonly communicate using frameworks implementing the publish/subscribe paradigm, such as the Data Distribution Service (DDS). However, these frameworks are real-ized with a multi-threaded software architecture and implement internal policies for message dispatching, posing additional chal-lenges for guaranteeing timing constraints. This work addresses the problem of optimizing a DDS-based interconnected real-time systems, proposing analysis-driven algorithms to set a vast range of parameters, ranging from classical thread priorities to other DDS-specific configurations. We evaluate our approaches on the Autoware Reference System, a realistic testbed from the Autoware autonomous driving framework.

The industry has recently shown a growing interest in running non-critical activities (e.g., design tools) together with real-time control tasks on open-source COTS platforms.In this paper, we present a modular platform for industrial automation based on open-source components. Thanks to the isolation provided by a hypervisor, the same platform can run both the real-time control code and the design tools, reducing the overall hardware costs.Besides illustrating the software architecture and describing the various open-source components, we illustrate extensions needed for convenient applicability, and we address the problem of interference on hardware resources shared by multiple operating systems, which undermines the performance of the real-time control. A set of experimental results show the effectiveness and the performance of the proposed solution.

The high-performance requirements needed to implement the most advanced functionalities of current and future Cyber-Physical Systems (CPSs) are challenging the development processes of CPSs. On one side, CPSs rely on model-driven engineering (MDE) to satisfy the non-functional constraints and to ensure a smooth and safe integration of new features. On the other side, the use of complex parallel and heterogeneous embedded processor architectures becomes mandatory to cope with the performance requirements. In this regard, parallel programming models, such as OpenMP or CUDA, are a fundamental brick to fully exploit the performance capabilities of these architectures. However, parallel programming models are not compatible with current MDE approaches, creating a gap between the MDE used to develop CPSs and the parallel programming models supported by novel and future embedded platforms.The AMPERE project will bridge this gap by implementing a novel software architecture for the development of advanced CPSs. To do so, the proposed software architecture will be capable of capturing the definition of the components and communications described in the MDE framework, together with the non-functional properties, and transform it into key parallel constructs present in current parallel models, which may require extensions. These features will allow for making an efficient use of underlying parallel and heterogeneous architectures, while ensuring compliance with non-functional requirements, including those on real-time performance of the system.

Summary During the last decade, there has been a considerable interest in using Linux in real‐time systems, especially for industrial control. The simple and elegant design of Linux guarantees reliability and very good performance, while its open‐source license allows to modify and change the source code according to the user needs. However, Linux has been designed to be a general‐purpose operating system. Therefore, it presents some issues like unpredictable latencies and limited support for real‐time scheduling. In this paper, we present our experience in the design and implementation of the real‐time scheduler that has been recently included in the Linux kernel. The scheduler is based on the Resource Reservation paradigm, which allows to enforce temporal isolation between the running tasks. We describe the genesis of the project, the challenges we have encountered, the implementation details and the API offered to the programmers. Then, we show the experimental results measured on a real hardware. Copyright © 2015 John Wiley & Sons, Ltd.

People and objects will soon share the same digital network for information exchange in a world named as the age of the cyber-physical systems. The general expectation is that people and systems will interact in real-time. This poses pressure onto systems design to support increasing demands on computational power, while keeping a low power envelop. Additionally, modular scaling and easy programmability are also important to ensure these systems to become widespread. The whole set of expectations impose scientific and technological challenges that need to be properly addressed. The AXIOM project (Agile, eXtensible, fast I/O Module) will research new hardware/software architectures for cyber-physical systems to meet such expectations. The technical approach aims at solving fundamental problems to enable easy programmability of heterogeneous multi-core multi-board systems. AXIOM proposes the use of the task-based OmpSs programming model, leveraging low-level communication interfaces provided by the hardware. Modular scalability will be possible thanks to a fast interconnect embedded into each module. To this aim, an innovative ARM and FPGA-based board will be designed, with enhanced capabilities for interfacing with the physical world. Its effectiveness will be demonstrated with key scenarios such as Smart Video-Surveillance and Smart Living/Home (domotics).

The advent of next-generation many-core embedded platforms has the chance of intercepting a converging need for predictable high-performance coming from both the High-Performance Computing (HPC) and Embedded Computing (EC) domains. On one side, new kinds of HPC applications are being required by markets needing huge amounts of information to be processed within a bounded amount of time. On the other side, EC systems are increasingly concerned with providing higher performance in real-time, challenging the performance capabilities of current architectures. This converging demand, however, raises the problem about how to guarantee timing requirements in presence of parallel execution. This paper presents the approach of project P-SOCRATES for the design of an integrated framework for the execution of workload-intensive applications with real-time requirements on top of next-generation commercial-off-the-shelf (COTS) platforms based on many-core accelerated architectures. The time-criticality and parallelisation challenges are addressed by merging techniques coming from both HPC and EC domains, identifying the main sources of indeterminism and proposing efficient mapping and scheduling algorithms, along with the associated timing and schedulability analysis, to guarantee the real-time and performance requirements of the applications.

In current-day embedded systems design, one is faced with cut-throat competition to deliver new functionalities in increasingly shorter time frames. This is now achieved by incorporating processor cores into embedded systems through (re-)programmability. However, this is not always beneficial for the performance or energy consumption. Therefore, adaptable embedded systems have been proposed to deal with these negative effects by reconfiguring the critical sections of an embedded system. In these proposals, we are clearly witnessing a trend that is moving from static configurations to dynamic (re)configurations.

Resource reservations are an effective technique to support hard and soft real-time applications in open systems. However, they generally focus on providing guarantees to real-time applications, without paying too much attention to the performance of non-real-time activities. In this paper, the main limitations encountered when using a conventional reservation-based scheduler for serving non-real-time tasks are described and formally analyzed. Then, a novel algorithm that overcomes these problems (called HGRUB) is proposed, and both theoretical and experimental evidence of its effectiveness is provided.

Power consumption is an important issue in the design of real-time embedded systems. As many embedded systems are powered by batteries, the goal is to extend the autonomy of the system as much as possible. To reduce power consumption, modern processors can change their voltage and frequency at runtime. A power-aware scheduling algorithm can exploit this capability to reduce power consumption while preserving the timing constraints of real-time tasks. In this paper, we present GRUB-PA, a novel power-aware scheduling algorithm based on a resource reservation technique. In addition to providing temporal isolation and time guarantees and, unlike most of the power-aware algorithms proposed in the literature, GRUB-PA can efficiently handle systems consisting of both hard and soft, aperiodic, sporadic, and periodic tasks. We compared our algorithm with existing power-aware scheduling algorithms on an extensive set of simulation experiments on synthetic task sets. The results show that the performance of our algorithm is in line with the state-of-the-art power-aware algorithms. We also present the implementation of our algorithm in the Linux operating system and discuss practical implementation issues like switching overhead and power models. Finally, we show the results of experiments performed on a real testbed application

Minimizing energy consumption is an important issue in the design of real-time embedded systems. As many embedded systems are powered by rechargeable batteries, the goal is to extend, as much as possible, the autonomy of the system.Recently, many scheduling algorithms have been proposed in the literature to exploit the capability of some processor to dynamically change its operating voltage and frequency. The goal of the scheduling algorithm is to select not only the task to be scheduled, but also the operating frequency, so minimizing the energy consumed without jeopardizing the schedulability of the real-time tasks.In this paper we present GRUB-PA, a new scheduling algorithm for power-aware systems. The algorithm can efficiently handle systems consisting of hard and soft real-time tasks. In addition, tasks can be periodic, sporadic or aperiodic. The algorithm reclaims the spare bandwidth caused by periodic tasks that execute less than expected or by sporadic tasks that arrive less frequently, and use this information to lower the processor frequency. We show the effectiveness of the GRUB-PA algorithm in scheduling hard and soft real-time tasks with a set of simulations. Finally, we present the implementation of GRUB-PA in the Linux OS.