Following the same trend of consumer electronics, safety-critical industries are starting to adopt Over-The-Air Software Updates (OTASU) on their embedded systems. The motivation behind this trend is twofold. On the one hand, OTASU offer several benefits to the product makers and users by improving or adding new functionality and services to the product without a complete redesign. On the other hand, the increasing connectivity trend makes OTASU a crucial cybersecurity demand to download latest security patches. However, the application of OTASU in the safety-critical domain is not free of challenges, specially when considering the dramatic increase of software complexity and the resulting high computing performance demands. This is the mission of UP2DATE, a recently launched project funded within the European H2020 programme focused on new software update architectures for heterogeneous high-performance mixed-criticality systems. This paper gives an overview of UP2DATE and its foundations, which seeks to improve existing OTASU solutions by considering safety, security and availability from the ground up in an architecture that builds around composability and modularity.

Critical real-time systems require strict resource provisioning in terms of memory and timing. The constant need for higher performance in these systems has led industry to recently include GPUs. However, GPU software ecosystems are by their nature closed source, forcing system engineers to consider them as black boxes, complicating resource provisioning. In this work we reverse engineer the internal operations of the GPU system software to increase the understanding of their observed behaviour and how resources are internally managed. This way, we allow system engineers to accurately determine the exact amount of resources required by their critical systems, avoiding underprovisioning. We first apply our methodology on a wide range of GPU hardware showing its generality in obtaining the properties of the GPU memory allocators. Next, we demonstrate the benefits of such knowledge in resource provisioning of two case studies from the automotive domain, where the actual memory consumption is up to 5.6× more than the memory requested by the application.

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This paper presents a hypervisor architecture tailored to low-power real-time applications. This architecture extends the capability of a hypervisor by providing power management techniques and power monitoring services. An implementation based on an existing hypervisor XtratuM that runs over the ARM of a Zynq-7000 SoC device is proposed as a proof of concept. Measurement results show that the extended hypervisor can obtain information on the power consumption and reduce it.

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