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.
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.
Today, we congratulate Yonghui Li on his first accepted journal article. The article is entitled “Architecture and Analysis of a Dynamically-Scheduled Real-Time Memory Controller” and has been accepted in the Real-Time Systems journal. The work extends his paper “Dynamic Command Scheduling for Real-Time Memory Controllers” that was presented at ECRTS 2014. The previous conference paper introduced a back-end architecture and scheduling algorithm for a dynamically scheduled SDRAM controller supporting variable transaction sizes and different degrees of bank interleaving. The properties of the back-end was extensively analyzed and worst-case execution times (WCET) of scheduled transactions was derived using two different methods with varying complexity and accuracy.
The newly accepted article extends this work by proposing a corresponding memory controller front-end, along with a complete response time analysis for memory transactions of variable sizes. A key feature of the front-end is that it features a non-work-conserving TDM arbiter, which provides static information about the order in which transactions of different sizes are scheduled, allowing the response time analysis to leverage the flexible WCET analysis of the back-end to provide tighter bounds. In addition, it is shown in which order memory clients with different request sizes should be served to minimize the total response time. The results demonstrate that dynamic command scheduling significantly outperforms our semi-static (pattern-based) approach in the average case, while it performs equally well or better in the worst-case with only a few exceptions.
The article proposes a unified framework to bound memory interference in multi-core platforms for a variety of different arbiters, such as time-division multiplexing (TDM), fixed priority, and an unspecified work-conserving arbiter. Our framework clearly demarcates the arbiter-dependent and independent stages in the analysis of interference. The arbiter-dependent phase takes the arbiter and the task memory-traffic pattern as inputs and produces a model of the availability of the bus to a given task. Then, based on the availability of the bus, the arbiter-independent phase determines the worst-case request-release scenario that maximizes the interference experienced by the tasks due to memory contention. We experimentally evaluate the quality of the analysis by comparison with a state-of-the-art TDM analysis approach and consistently showing a considerable reduction in maximum interference.
A journal article entitled “Unified overhead-aware schedulability analysis for slot-based task-splitting” has appeared in Real-Time Systems Journal. This article was first-authored by Paulo Baltarejo Sousa during my time at CISTER-ISEP Research Unit in Porto, Portugal and is the result of a collaboration from that time.
The main contribution of the article is a unified scheduling theory for two state-of-the-art slot-based semi-partitioned algorithms, S-EKG and NPS-F. This new theory is based on exact schedulability tests, thus also overcoming many sources of pessimism in existing analyses. Another benefit of the proposed analysis is that it captures overheads, such as interrupts, context switches, and caches, occurring when tasks are deployed on real multi-core platforms. Together, these advantages results in a new efficient and reliable schedulability analysis for slot-based task-splitting algorithms.