RTAS is a top-tier conference with a focus on systems research related to embedded systems and time-sensitive systems. RTAS’23 invites papers describing original systems, applications, case studies, methodologies, and algorithms that contribute to the state of practice in design, implementation, verification, and validation of embedded systems or time-sensitive systems. RTAS’23 consists of two tracks:
- Track 1. Systems and Applications;
- Track 2. Applied Methodologies and Foundations.
The broad scope of RTAS’23 ranges from traditional hard real-time systems to embedded systems without explicit timing requirements. In both tracks, the timing requirements of interest include not only classical hard real-time constraints, but also time-sensitive applications in a broader sense, including applications subject to probabilistic, soft real-time, quality-of-service (QoS), or latency requirements. The application area can be either resource-constrained embedded systems or other time-sensitive systems of any size, including (but are not limited to): time-sensitive cloud/edge/fog computing systems, time-sensitive applications in the Internet of Things (IoT), time-sensitive mobile computing apps, timing aspects in robotics middleware and frameworks, machine learning in or for time-sensitive systems, real-time control in smart cities and other large cyber-physical systems (CPS), signal processing algorithms that must execute in real time, and real-time healthcare solutions.
RTAS welcomes both papers backed by formal proofs as well as papers that focus exclusively on empirical validation of timing requirements. Track 1 further welcomes applied systems papers that focus on practical issues other than timing, such as security, energy-awareness, and fault tolerance, in the broader field of embedded/CPS/IoT systems and applications.
RTAS’23 follows a double-blind peer reviewing process: author identities and affiliations will not be revealed to reviewers. Authors will have the opportunity to provide a rebuttal of reviews before acceptance decisions are made, solely to provide clarifications and correct misconceptions. The rebuttal will not allow authors to introduce new material beyond the original submission, or promise such material for the camera-ready version. There will be an optional evaluation process for accepted papers that assesses the reproducibility of the work.
Track 1: Systems and Applications
This track focuses on research of an empirical nature pertaining to applications, runtime software, and hardware architectures for time-sensitive or embedded systems. Applied systems papers that target embedded systems do not necessarily need to consider timing issues. Topics relevant to this track include, but are not limited to:
- real-time and embedded operating systems,
- hypervisors and runtime frameworks,
- hardware architectures, memory hierarchies, FPGAs, GPUs and accelerators,
- time-sensitive networks, CPS/IoT infrastructure,
- latency-sensitive cloud and edge computing,real-time artificial intelligence and machine learning,
- WCET analysis, compilers, tools, benchmarks and case-studies.
Papers discussing design and implementation experiences on real industrial systems are especially encouraged. Papers submitted to this track should focus on specific systems and implementations. Authors must include a section with experimental results performed on a real implementation, or demonstrate applicability to an industrial case study or working system. The experiment or case study discussions must highlight the key lessons learned. Simulation-based results are acceptable for architectural simulation, or other cases where authors clearly motivate why it is not feasible to develop and evaluate a real system.
Track 2: Applied Methodologies and Foundations
This track focuses on fundamental models, techniques, methods, and analyses that are applicable to time-sensitive systems to solve specific problems. Submissions to this track must consider some form of timing requirements. Topics relevant to this track include, but are not limited to:
- scheduling and resource allocation,
- specification languages and tools,
- system-level optimization and co-design techniques,
- design space exploration,
- verification and validation methodologies.
Papers must describe the main context or use-case for the proposed methods giving clear motivating examples based on real systems. The system models and any assumptions used in the derivation of the methods must be applicable to real systems, and reflect actual needs. Papers must include a section on experimental results, preferably including a case study based on information from a real system. The use of synthetic workloads and models is acceptable if appropriately motivated and used to provide a systematic evaluation.