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Real-time systems require a formal guarantee of timing-constraints, not only for individual tasks but also for data-propagation. The timing behavior of data-propagation paths in a given system is typically described by its maximum reaction time and its maximum data age. This paper shows that they are equivalent. To reach this conclusion, partitioned job chains are introduced, which consist of one immediate forward and one immediate backward job chain. Such partitioned job chains are proven to describe maximum reaction time and maximum data age in a universal manner. This universal description does not only show the equivalence of maximum reaction time and maximum data age, but can also be exploited to speed up the computation of such significantly. In particular, the speed-up for synthesized task sets based on automotive benchmarks can be up to 1600. Since only very few non-restrictive assumptions are made, the equivalence of maximum data age and maximum reaction time holds for almost any scheduling mechanism and even for tasks which do not adhere to the typical periodic or sporadic task model. This observation is supported by a simulation of a ROS2 navigation system., LIPIcs, Vol. 262, 35th Euromicro Conference on Real-Time Systems (ECRTS 2023), pages 10:1-10:22

LIPIcs, Volume 262, ECRTS 2023, Complete Volume, LIPIcs, Vol. 262, 35th Euromicro Conference on Real-Time Systems (ECRTS 2023), pages 1-460

Front Matter, Table of Contents, Preface, Conference Organization, LIPIcs, Vol. 262, 35th Euromicro Conference on Real-Time Systems (ECRTS 2023), pages 0:i-0:xvi

This artifact provides the source code to validate and reproduce the numerical results of the associated paper "Unikernel-Based Real-Time Virtualization under Deferrable Servers: Analysis and Realization". Due to the nature of a close-source project with the company, i.e., EMVICORE GmbH, the source code of the case study in Section 6.2 is not included in this artifact., DARTS, Vol. 8, Special Issue of the 34th Euromicro Conference on Real-Time Systems (ECRTS 2022), pages 2:1-2:2

Constructing a complete control-flow graph (CGF) and computing upper bounds on loops of a computing system are essential to safely estimate the worst-case execution time (WCET) of real-time tasks. WCETs are required for verifying the timing requirements of a real-time computing system. Therefore, we propose an analysis using dynamic symbolic execution (DSE) that detects and computes upper bounds on the loops, and resolves indirect jumps. The proposed analysis constructs and initializes memory models, then it uses a satisfiability modulo theories (SMT) solver to symbolically execute the instructions. The analysis showed higher precision in bounding loops of the Mälardalen benchmarks comparing to SWEET and oRange. We integrated our analysis with the OTAWA toolbox for performing a WCET analysis. Then, we used the proposed analysis for estimating the WCET of functions in a use case inspired by an aerospace project., OASIcs, Vol. 103, 20th International Workshop on Worst-Case Execution Time Analysis (WCET 2022), pages 3:1-3:12

For cyber-physical systems, real-time virtualization optimizes the hardware utilization by consolidating multiple systems into the same platform, while satisfying the timing constraints of their real-time tasks. This paper considers virtualization based on unikernels, i.e., single address space kernels usually constructed by using library operating systems. Each unikernel is a guest operating system in the virtualization and hosts a single real-time task. We consider deferrable servers in the virtualization platform to schedule the unikernel-based guest operating systems and analyze the worst-case response time of a sporadic real-time task under such a virtualization architecture. Throughout synthesized tasksets, we empirically show that our analysis outperforms the restated analysis derived from the state-of-the-art, which is based on Real-Time Calculus. Furthermore, we provide insights on implementation-specific issues and offer evidence that the proposed scheduling architecture can be effectively implemented on top of the Xen hypervisor while incurring acceptable overhead., LIPIcs, Vol. 231, 34th Euromicro Conference on Real-Time Systems (ECRTS 2022), pages 6:1-6:22

LIPIcs, Volume 231, ECRTS 2022, Complete Volume, LIPIcs, Vol. 231, 34th Euromicro Conference on Real-Time Systems (ECRTS 2022), pages 1-470

The emergence of Real-Time Systems with increased connections to their environment has led to a greater demand in security for these systems. Memory corruption attacks, which modify the memory to trigger unexpected executions, are a significant threat against applications written in low-level languages. Data-Flow Integrity (DFI) is a protection that verifies that only a trusted source has written any loaded data. The overhead of such a security mechanism remains a major issue that limits its adoption. This article presents RT-DFI, a new approach that optimizes Data-Flow Integrity to reduce its overhead on the Worst-Case Execution Time. We model the number and order of the checks and use an Integer Linear Programming solver to optimize the protection on the Worst-Case Execution Path. Our approach protects the program against many memory-corruption attacks, including Return-Oriented Programming and Data-Only attacks. Moreover, our experimental results show that our optimization reduces the overhead by 7% on average compared to a state-of-the-art implementation., LIPIcs, Vol. 231, 34th Euromicro Conference on Real-Time Systems (ECRTS 2022), pages 18:1-18:24

Real-time containers are a promising solution to reduce latencies in time-sensitive cloud systems. Recent efforts are emerging to extend their usage in industrial edge systems with mixed-criticality constraints. In these contexts, isolation becomes a major concern: a disturbance (such as timing faults or unexpected overloads) affecting a container must not impact the behavior of other containers deployed on the same hardware. In this paper, we propose a novel architectural solution to achieve isolation in real-time containers, based on real-time co-kernels, hierarchical scheduling, and time-division networking. The architecture has been implemented on Linux patched with the Xenomai co-kernel, extended with a new hierarchical scheduling policy, named SCHED_DS, and integrating the RTNet stack. Experimental results are promising in terms of overhead and latency compared to other Linux-based solutions. More importantly, the isolation of containers is guaranteed even in presence of severe co-located disturbances, such as faulty tasks (elapsing more time than declared) or high CPU, network, or I/O stress on the same machine., LIPIcs, Vol. 231, 34th Euromicro Conference on Real-Time Systems (ECRTS 2022), pages 15:1-15:23

Front Matter, Table of Contents, Preface, Conference Organization, LIPIcs, Vol. 231, 34th Euromicro Conference on Real-Time Systems (ECRTS 2022), pages 0:i-0:x

Real-time containers are a promising solution to reduce latencies in time-sensitive cloud systems. Recent efforts are emerging to extend their usage in industrial edge systems with mixed-criticality constraints. In these contexts, isolation becomes a major concern: a disturbance (such as timing faults or unexpected overloads) affecting a container must not impact the behavior of other containers deployed on the same hardware. In this artifact, we propose a novel architectural solution to achieve isolation in real-time containers, based on real-time co-kernels, hierarchical scheduling, and time-division networking. The architecture has been implemented on Linux patched with the Xenomai co-kernel, extended with a new hierarchical scheduling policy, named SCHED_DS, and integrating the RTNet stack. Experimental results, presented in the related scholarly paper, are promising in terms of overhead and latency compared to other Linux-based solutions. More importantly, the isolation of containers is guaranteed even in presence of severe co-located disturbances, such as faulty tasks (elapsing more time than declared) or high CPU, network, or I/O stress on the same machine., DARTS, Vol. 8, Special Issue of the 34th Euromicro Conference on Real-Time Systems (ECRTS 2022), pages 1:1-1:12

Real-time object detection is crucial in autonomous driving. To avoid catastrophic accidents, an autonomous car should detect objects with multiple cameras and make decisions within a certain time limit. Object detection systems can meet the real-time constraint by dynamically downsampling input images to proper scales according to their time budget. However, simply applying the same scale to all the images from multiple cameras can cause unnecessary accuracy loss because downsampling can incur a significant accuracy loss for some images. To reduce the accuracy loss while meeting the real-time constraint, this work proposes RTScale, a new adaptive real-time image scaling scheme that applies different scales to different images reflecting their sensitivities to the scaling and time budget. RTScale infers the sensitivities of multiple images from multiple cameras and determines an appropriate image scale for each image considering the real-time constraint. This work evaluates object detection accuracy and latency with RTScale for two driving datasets. The evaluation results show that RTScale can meet real-time constraints with minimal accuracy loss., Leibniz International Proceedings in Informatics (LIPIcs), 231, ISSN:1868-8969, 34th Euromicro Conference on Real-Time Systems, ISBN:978-3-95977-239-6

LIPIcs, Volume 196, ECRTS 2021, Complete Volume, LIPIcs, Vol. 196, 33rd Euromicro Conference on Real-Time Systems (ECRTS 2021), pages 1-370

Front Matter, Table of Contents, Preface, Conference Organization, LIPIcs, Vol. 196, 33rd Euromicro Conference on Real-Time Systems (ECRTS 2021), pages 0:i-0:xii

Front Matter, Table of Contents, Preface, Conference Organization

LIPIcs, Volume 165, ECRTS 2020, Complete Volume

Over-estimation of worst-case execution times (WCETs) of real-time tasks leads to poor resource utilization. In a mixed-criticality system (MCS), the over-provisioning of CPU time to accommodate the WCETs of highly critical tasks may lead to degraded service for less critical tasks. In this paper, we present PAStime, a novel approach to monitor and adapt the runtime progress of highly time-critical applications, to allow for improved service to lower criticality tasks. In PAStime, CPU time is allocated to time-critical tasks according to the delays they experience as they progress through their control flow graphs. This ensures that as much time as possible is made available to improve the Quality-of-Service of less critical tasks, while high-criticality tasks are compensated after their delays. In this paper, we integrate PAStime with Adaptive Mixed-criticality (AMC) scheduling. The LO-mode budget of a high-criticality task is adjusted according to the delay observed at execution checkpoints. This is the first implementation of AMC in the scheduling framework Using LITMUS-RT, which is extended with our PAStime runtime policy and tested with real-time Linux applications such as object classification and detection. We observe in our experimental evaluation that AMC-PAStime significantly improves the utilization of the low-criticality tasks while guaranteeing service to high-criticality tasks., 24 pages