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Traditional embedded systems and recent platforms used in emerging computing paradigms (e.g., fog computing) have resource limits and require their applications and services to be dynamically added (i.e., deployed) and removed at run-time. These applications often have non-functional (quality) requirements (e.g., end-to-end latency) which are only satisfied when sufficient resources are allocated to them. Hence, a run-time decision-maker is needed to optimize the deployments, in terms of resource budgets that are allocated to applications. Additionally, computing platforms have become heterogeneous in terms of their resources and the applications they execute. However, the existing deployment solutions are limited to specific resources and services. In this paper, we propose a run-time deployment framework that is more flexible in defining constraints and optimization goals and works with more heterogeneous resources and resource models than existing solutions. The framework is implemented on an embedded platform as a proof of concept.

Robot Operating System (ROS) is a de-facto standard robot middleware in many academic and industrial use cases. However, utilizing ROS/ROS2 in safety-critical embedded applications with real-time requirement is challenging because of C1) Non-real-time underlying hardware, C2) No control on the host OS scheduler, C3) Unpredictable dynamic memory allocation, C4) High resource requirement, and C5) Unpredictable execution model for ROS nodes. In this paper, we address these limiting factors by proposing a hardware-software architecture -CompROS- for ROS2 based robotic development in a Multi-Processor System on Chip (MPSoC) platform that. The proposed hardware architecture consists of a Hard Real-Time (HRT) RISC-V based subsystem implemented in the Programmable Logic (PL) part of the MPSoC platform, a Soft Real-Time (SRT) ARM-based subsystem in the Processing System (PS) part of the MPSoC platform, and a Non-Real-Time (NRT) PC. While the proposed hardware architecture along with a partitioning layer overcomes the first two limiting factors, the rest are managed by the proposed multi-layer software architecture. We make a bare-metal implementation of XRCE-DDS standard for PL-PS communication, while peer-to-peer PL-PL communication is done through a proposed real-time publish-subscribe approach. The reliable communication for PS-PLL communication is done through utilizing C-HEAP protocol. Further, we integrate ROS2 software layers on top of the proposed hardware and software layers. Finally, with respect to C5, we present a real-time execution model of ROS2 nodes by a mapping of ROS2 entities to CompROS entities, which is validated through experimental results. We run ROS2 middleware with an executable size of less than 200 KB on an MPSoC platform.

This paper presents a model-based PIL simulation framework targeting multi-core multi-application FPGA-based embedded platforms. The process from model-based simulations to implementing on the platform requires a target specified code generation, compile and execution. The presented framework is able to automatically go through this process and perform the PIL simulation starting from a model-based environment in particular Simulink. It is also able to consider the multi-application nature of the target platform, executing the PIL simulation without interfering other applications. We validate the functionality of the PIL framework by testing a control systems application, using various PIL configurations.

From model-based design to implementation on an embedded platform requires target-specific code generation, compilation, and execution. Processor-in-the-loop (PIL) simulation is an intermediate step meant for detailed testing and debugging in the development process. This paper presents a PIL simulation framework targeting multi-core FPGA-based embedded platforms. The presented framework allows for a fully automated process of performing PIL simulations on an FPGA-based embedded platform - CompSOC - starting from a Simulink model. The framework includes two PIL configurations - one configuration executes only the controller code on the target platform while other configuration executes both the controller and the plant code on the target platform. It considers scheduling of multiple applications and interference-free execution on the target platform under the PIL configurations. Further, the framework allows for logging various measurements of parameters such as execution time, memory usage and so on in the PIL configurations which can be used for testing and debugging purposes.