WMC 2023

PURPOSE OF THE WORKSHOP

WMC’s goal is to promote sharing of new ideas, results, experiences, and information about research and development of mixed-criticality real-time systems. 

The workshop aims to bring together researchers working in fields relating to real-time systems with a focus on the challenges brought about by the integration of mixed-criticality applications onto singlecore, multicore, and manycore architectures. These challenges are cross-cutting. 

To advance rapidly, closer interaction is needed between the sub-communities involved in real-time scheduling, real-time operating systems/runtime environments, and timing analysis. The workshop aims to promote understanding of the fundamental problems that affect Mixed-Criticality Systems (MCS) at all levels in the software/hardware stack and crucially the interfaces between them. 

The workshop will promote lively interaction, cross fertilization of ideas, synergies, and closer collaboration across the breadth of the real-time community, as well as attracting industrialists from the aerospace, automotive and other industries with a specific interest in MCS.

The WMC aims to promote a holistic approach to solving the problems of MCS. The scope of the workshop will cover all aspects of real-time systems that deal with more than one criticality level, including but not limited to:

• Task and system models for MCS on single-core, multi-core, and many-core platforms.

• Scheduling schemes and analyses for MCS, including the integration of appropriate models of overheads and delays.

• Run-time environments and support for MCS, including data exchange and synchronization across criticality levels, and issues relating to consistency of the criticality mode. 

• Analysis of worst-case execution times (WCET) relating to MCS on multicore and many core platforms, including cache-related preemption and migration delays.

• Discussions and analysis of extending the properties of a mixed-criticality system to embrace a broader and more comprehensive concept of a multi-model specification.

• Mixed-criticality communication mechanisms and analysis, including Network-on-Chip support.

• Probabilistic analysis techniques and randomized approaches for MCS.

• Security aspects only as they affect real-time behaviors of MCS.

• Machine Learning workload support and learning-based decision-making in MCS.

• Creation of open benchmarks in MCS that allow practitioners to perform comparative evaluations.

• Empirical assessments give insight into research problems and the challenges of gathering evidence for assurance of MCS on multicore and many core platforms.

• Emerging challenges from modern applications and systems (e.g., AI-enhanced systems) and new considerations from industry (e.g., automotive, avionic, and aerospace industry) with real-time mixed-criticality features.