EPEW and ASMTA are flagship conferences for academic and industrial researchers from diverse fields with common interest on the performance modelling, analysis and design of stochastic systems. This year, the two conference join again (and also join with the International ECMS conference on Modelling and Simulation, ECMS 2023), and solicit papers on the development of broadly applicable analytic, simulation and measurement-based methods on all aspects of performance engineering.

The European Performance Engineering Workshop is an annual event that aims to gather researchers from both the academia and industrial world working on all aspects of performance modelling and analysis.

The concept of performance in EPEW 2023 is considered in its broadest sense including the notions of Quality of Service, scalability as well as reliability, availability and systems management, among the others. Therefore, of particular interest are the ideas introducing new methods for evaluating complex systems, as well as innovative applications of methodologies and known techniques to the latest generation of systems, networks and computer-based services. EPEW 2023 seeks papers based on performance evaluation of systems from theoretical and practical viewpoint. Application of performance evaluation techniques to emerging technologies, like cyber-physical systems ranging from mobile devices and Internet-of-Things (IoT), fog and edge computing, applications to large-scale cloud computing systems, smart grids, security infrastructures, are among the topics of interest to EPEW 2023.

Topics of interest include but are not limited to the following topic areas:

- Theoretical advances in performance modeling and evaluation, e.g.

    Probabilistic, stochastic, or performability models, such as Queueing Networks, Petri Nets, and Process Calculi;
    Specification of quantitative properties,
    Analytical and numerical solution techniques and simulation techniques,
    Quantitative model checking, equivalence checking, and static analysis
    Context-aware modelling and analysis techniques
    Machine learning and deep learning-based approaches for performance evaluation and analysis
    Multiformalism and Multiparadigm modelling approaches

- System, software, and network performance engineering, e.g.

    Performance-oriented design, architecture, implementation, deployment, monitoring, and maintenance
    Constraint-based and model-driven system design
    Performance analysis, simulation, and experimental design
    Benchmark design and benchmark-based evaluation and monitoring
    Automated interpretation of analysis results
    Quality of service, and trade-offs between security, performance, dependability, energy consumption, usability, etc.
    Software performance modeling languages, model composition and tool interoperability
    6G and beyond

- Case studies, e.g.

    Cloud systems, Hybrid Cloud, and Fog Computing Internet of Things
    Cyber-physical systems
    E-health systems
    Blockchain and Cryptocurrency applications
    Sharing services such as carshare and rideshare
    Electric vehicles and battery modelling
    Large-scale systems and scalability analysis of systems, robustness analysis of systems, resilience analysis of systems
    Industrial case studies, experience reports and tools, with a solid analysis and theoretical background