RTAS 2021 - 27th IEEE Real-Time and Embedded Technology and Applications Symposium

RTAS is a top-tier conference with a focus on systems research related to embedded systems and time-sensitive systems. RTAS’21 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’21 consists of two tracks:
Systems, Architecture and Applications
Applied Methodologies and Foundations
The broad scope of RTAS’21 ranges from traditional hard real-time systems to embedded systems without explicit timing requirements. RTAS’21 welcomes both papers backed by formal proofs as well as papers that focus exclusively on empirical validation of timing requirements.
Track 1: Systems, Architecture and Applications
Track 1 focuses on research of an empirical nature pertaining to systems, architecture and applications for time-sensitive or embedded systems. Track 1 also welcomes applied systems papers that focus on practical issues other than timing in the broader field of embedded/CPS/IoT systems and applications. Topics relevant to this track include, but are not limited to:
real-time and embedded operating systems,
middleware and runtime systems for real-time and embedded systems,
CPS and IoT infrastructure,
hardware architectures for real-time/embedded systems, and
WCET analysis and WCET-oriented software design.
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. Evaluations must be free of “benchmarking crimes”. Simulation-based results are acceptable for architectural simulation, or other cases where authors need to clearly motivate why it is not feasible to develop and evaluate a real system.
Track 2: Applied Methodologies and Foundations
Track 2 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, which includes both classical hard or soft real-time systems as well as latency-sensitive systems in domains such as (but not limited to) CPS, IoT or the Cloud. 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, and
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.
For submissions addressing timing issues to 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 (e.g., characterized by a focus on tail latency),
time-sensitive applications in the Internet of Things (IoT),
time-sensitive distributed event processing systems,
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.