The accepted journal article extends the RTNS paper by generalizing the proposed schedulability analyses from a constrained-deadline task model to the more general, but also more complex, model with arbitrary deadlines. The corresponding optimal priority assignment for our schedulability analysis is also identified. In experiments with synthetic workloads, the proposed analyses are compared in terms of scheduling success ratio, against the frame-agnostic analyses for the corresponding variants of the Vestal model.
The paper addresses the problem of satisfying real-time requirements in industrial systems using unpredictable hardware and software, which limit or entirely prevent the application of established real-time analysis techniques. To this end, we propose PReGO, a generative methodology for satisfying real-time requirements in industrial commercial-off-the-shelf (COTS) systems. We report on our experience in applying PReGO to a use-case: a Search & Rescue application running on a fixed-wing drone with COTS components, including an NVIDIA Jetson board and a stock Ubuntu/Linux. We empirically evaluate the impact of each integration step and demonstrate the effectiveness of our methodology in meeting real-time application requirements in terms of deadline misses and energy consumption.
The article addresses the problem of generating a time-triggered schedule for a number of independently developed automotive applications on a number of shared resources, such that their control performance only suffers minimal degradation. The three main contributions are: 1) a constraint programming model that solves the problem optimally, exploiting properties of the problem to reduce the computation time; 2) a fast heuristic called Flexi that only has a minor impact on the optimality of the solution; and 3) an experimental evaluation of the scalability and efficiency of the proposed approaches on a case study, in addition to several synthetic datasets. The results show that the heuristic provides a solution on average 5 times faster, finding a feasible solution in 31% more problem instances than the optimal approach within a time limit, while only sacrificing 0.5% of the control performance quality for the largest dataset.
The paper describes applied research from an industrial ESI project with goal of enabling continuous evolution of software in service-oriented architectures through automatic detection and correction of service incompatibilities. Towards this, the paper has three main contributions: 1) the state-of-the-art in the areas of specification of service interfaces, and detection and correction of incompatible service interactions is surveyed, 2) directions for a methodology to detect and correct incompatible interactions that is currently under development are discussed, and 3) the methodology is discussed in the context of a simplified industrial case study from the defense domain.
This article addresses the problem of resource sharing in mixed-criticality systems through temporal isolation by extending the state-of-the-art Single-Core Equivalence (SCE) framework in three ways: 1) we extend the theoretical toolkit for the SCE framework by considering EDF and server-based scheduling, instead of partitioned fixed-priority scheduling, 2) we support uneven memory access budgets on a per-server basis, rather than just on a per-core basis, and 3) we formulate an Integer-Linear Programming Model (ILP) guaranteed to find a feasible mapping of a given set of servers to processors, including their execution time and memory access budgets, if such a mapping exists. Our experiments with synthetic task sets confirm that considerable improvement in schedulability can result from the use of per-server memory access budgets under the SCE framework.
Overall, I greatly appreciate that key conferences in the real-time community are starting to allow journal articles to be presented. This increases the exposure of these works that are often longer and better edited. It is also helpful for researchers at the institutes where conference publications are not considered a relevant KPI. You can argue the validity of this reasoning in areas of computer science where conferences are highly competitive with 20-30% acceptance rates, but it is reality for some researchers. An interesting thing with the MODELS conference is that they collaborate with the SOSYM journal such that some accepted articles in the journal gets a full slot at the conference. This is a nice way to highlight good articles and to appreciate the work done by both authors and reviewers.
The paper “Response Time Analysis of Multiframe Mixed-Criticality Systems” has been accepted at RTNS 2019. This work is the next in our mixed-criticality research line, in collaboration with my former colleagues at CISTER. It continues our work on the multi-frame task model, also considered in our RTCSA paper this year. The multi-frame model describes tasks that have different worst-case execution times for each job, following a known pattern, which can be exploited to reduce the cost of the system. Existing schedulability analyses fail to leverage this characteristic, potentially resulting in pessimism and increased system cost.
In this paper, we present a schedulability analysis for the multi-frame mixed-criticality model. Our work extends both the analysis techniques for Static Mixed-Cricality scheduling (SMC) and Adaptive Mixed-Criticality scheduling (AMC), on one hand, and the schedulability analysis for multi-frame task systems on the other. Our proposed worst-case response time (WCRT) analysis for multi-frame mixed-criticality systems is considerably less pessimistic than applying the SMC, AMC-rtb and AMC-max tests obliviously to the WCET variation patterns. Experimental evaluation with synthetic task sets demonstrates up to 63.8% higher scheduling success ratio compared to the best of the frame-oblivious tests.
A paper “Memory Bandwidth Regulation for Multiframe Task Sets” has been accepted at RTCSA 2018. This paper aims to reduce cost of real-time systems where the worst-case execution times of tasks vary from job to job, according to known patterns. This kind of execution behavior can be captured by the multi-frame task model. However, this model is optimistic and unsafe for multi-cores with shared memory controllers, since it ignores memory contention, and existing approaches to stall analysis based on memory regulation are very pessimistic if straight-forwardly applied.
This paper remedies this by adapting existing stall analyses for memory-regulated systems to the multi-frame model. Experimental evaluations with synthetic task sets show up to 85% higher scheduling success ratio for our analysis, compared to the frame-agnostic analysis, enabling higher platform utilization without compromising safety. We also explore implementation aspects, such as how to speed up the analysis and how to trade off accuracy with tractability.
This work is the result of an industrial ESI project addressing the need for new methodologies to reduce development time, simplify customization, and improve evolvability of complex software systems. The chapter explains how these challenges are addressed by an approach to model-based engineering (MBE) based on domain-specific languages (DSLs). However, applying the approach in industry has resulted in 5 technical research questions, namely how to: RQ1) achieve modularity and reuse in a DSL ecosystem, RQ2) achieve consistency between model and realizations, RQ3) manage an evolving DSL eco-system, RQ4) ensure model quality, RQ5) ensure quality of generated code. The five research questions are explored in the context of the published state-of-the-art, as well as practically investigated through a case study from the defense domain.
A paper entitled “Decoupling Criticality and Importance in Mixed-Criticality Scheduling” has been accepted at the 6th International Workshop on Mixed Criticality Systems (WMC).The paper addresses the need for more expressive task models for mixed-criticality systems by presenting an extension to the well-known mode-based adaptive mixed-criticality model by Vestal. The proposed model allows a task’s criticality and its importance to be specified independently from each other. A task’s importance is the criterion that determines its presence in different system modes. Meanwhile, the task’s criticality (reflected in its Safety Integrity Level (SIL) and defining the rules for its software development process), prescribes the degree of conservativeness for the task’s estimated WCET during schedulability testing.
We indicate how such a task model can help resolve some of the perceived weaknesses of the Vestal model, in terms of how it is interpreted, and demonstrate how the existing scheduling tests for the classic variant’s of Vestal’s model can be mapped to the new task model essentially without changes.
The paper aims to safely reduce the cost of mixed-criticality multi-core systems by addressing inefficient usage of memory bandwidth. This is achieved by combining per-core memory access regulation with the well-established Vestal model, which improves on the state-of-the-art in two respects: 1) We allow the memory access budgets of the cores to be dynamically adjusted, when the system undergoes a mode change, reflecting the different needs in each mode, for better schedulability. 2) We devise memory regulation-aware and stall-aware schedulability analysis for such systems, based on AMC-max. By comparison, the state-of-the-art offered no option of dynamic adjustment of core budgets, and only offered regulation-aware schedulability analysis based on AMC-rtb, which is inherently more pessimistic. Finally, 3) we consider different task assignment and bandwidth allocation heuristics, to assess the improvement from the dynamic memory budgets and new analysis. Our results show improvements in schedulability ratio of up to 9.1% over the state-of-the-art.