Real-Time Systems - Call for Papers: Resource Partitioning for Modern Multicore Systems
Motivations
Safety-critical and timing-aware systems must deal with increasingly challenging requirements. Where once it was possible to dedicate specific hardware resources to timing-critical components, the increasing density of such components combined with their expanded resource requirements mean that this is no longer feasible. Contemporary systems must share multicore computing and communications resources between the tasks of the system, in a way which can predictably support the timing behaviour of the system. Additionally, the use of AI and machine learning components necessitate the sharing of powerful dedicated hardware accelerators between tasks.
Objectives
Resource partitioning is a long-established technique for building functionally-safe, timing-aware systems, but the proliferation of complex hardware features mean that this is a challenging and constantly-evolving research area. The goal of this special issue is to collect new ideas, methodologies, and techniques for increasing the time predictability of resource partitioning techniques over the hardware architectures that are being built today.
Submissions to this special issue must address some form of hardware or software resource sharing with the aim of providing guarantees, which may be hard real-time, probabilistic, or softer quality-of-service requirements. Theoretical papers, and papers considering exclusively empirical validation of timing requirements are welcome. Authors are invited to submit original manuscripts on topics including, but not limited to:
- Predictable software partitioning for timing correctness
- Hardware partitioning to support predictability
- Problem identification and solutions for the management of hardware or software contention
- Techniques for probabilistic, soft realtime, and quality-of-service requirements
- Development and analysis of hypervisors to increase predictability
- Sharing of communications resources on complex realtime platforms
- Hardware support and middleware for predictable partitioning and resource sharing
- Surveys and practical investigations into modern hardware resources, and resource partitioning techniques
Dates
Open: Immediately
Deadline: January 15, 2024
Guest Editors
Ian Gray is an associate professor / senior lecturer with the Department of Computer Science, University of York. His research interests include real-time systems and their programming models, embedded systems, FPGAs and re-configurable computing, and many/multi-core distributed systems, and has paid particular focus on applying this work to industry through a range of EU Horizon projects and industrial collaborations. He has published over 30 papers in a range of real-time systems, embedded systems, and robotics venues. He serves on the programme committees of the key conferences in the real-time systems fields such as RTSS and RTAS, and reviews for a range of significant journals.
Xiaotian Dai is a Lecturer (Assistant Professor) in the Real-Time and Distributed Systems Research Group, University of York, UK. He received a Ph.D. degree from the University of York in 2019. His research interest is in real-time and cyber-physical systems, including flexible and adaptive task scheduling, control scheduling co-design, mixed-criticality, and timing analysis of multicores. His research applies to high-performance embedded computing, robotic systems, and safety-critical autonomous systems. He serves as a reviewer and a TPC member of many prestigious real-time and design automation conferences.
Submission Guidelines
Authors should prepare their manuscript according to the Instructions for Authors available from the Real-Time Systems website (this opens in a new tab). Authors should submit through the online submission site at https://www.editorialmanager.com/time/default2.aspx (this opens in a new tab) and select “SI Resource Partitioning for Modern Multicore Systems" when they reach the “Article Type” step in the submission process. Submitted papers should present original, unpublished work, relevant to one of the topics of the special issue. All submitted papers will be evaluated on the basis of relevance, significance of contribution, technical quality, scholarship, and quality of presentation, by at least three independent reviewers. It is the policy of the journal that no submission, or substantially overlapping submission, be published or be under review at another journal or conference at any time during the review process. Please note that the authors of selected papers presented at RTAS 2023 are invited to submit an extended version of their contributions by taking into consideration both the reviewers’ comments on their conference paper, and the feedback received during presentation at the conference. It is worth clarifying that the extended version is expected to contain a substantial scientific contribution, e.g., in the form of new algorithms, experiments or qualitative/quantitative comparisons, and that neither verbatim transfer of large parts of the conference paper nor reproduction of already published figures will be tolerated. The extended versions of RTAS papers will undergo the standard, rigorous journal review process and be accepted only if well-suited to the topic of this special issue and meeting the scientific level of the journal. Final decisions on all papers are made by the Editor in Chief.