from 21 to 25 June 2021
co-located with STAF2021 Bergen, Norway
International workshop on MDE for Smart IoT Systems
How to submit
We solicit papers of two main types: research papers (10 pages) and position papers (5-9 pages)
The submissions must be in English and adhere to the CEUR style. Use this easychair link to submit your paper.
University of Nice Côte D'Azur (France)
Tellu AS (Norway)
A recent forecast from the International Data Corporation (IDC) envisions that 41 billion Internet-of-Things (IoT) endpoints will be in use by 2025, representing great business opportunities. The next generation IoT systems needs to perform distributed processing and coordinated behavior across IoT, edge and cloud infrastructures, manage the closed loop from sensing to actuation, and cope with vast heterogeneity, scalability and dynamicity of IoT systems and their environments.
Smart IoT Systems have - the potential to flourish innovations in many application domains. For instance, the typical components of a smart city include infrastructure, transportation, intelligent energy consumption, health-care, and technology. These ingredients are what make the cities smart, efficient and optimized respect to the citizen and administration needs. The Internet of Things is an emerging paradigms that can contribute to make smart cities efficient and responsive.
On the one hand, Model-driven engineering (MDE) techniques can support the design, deployment, and operation of smart IoT systems. For instance, to manage abstractions in IoT systems definition and to provide means to automate some of the development and operation activities of IoT systems, e.g., domain specific modeling languages can provide a way to represent different aspects of systems leveraging a heterogeneous software and hardware IoT infrastructure and to generate part of the software to be deployed on it. On the other hand, the application of modeling techniques in the IoT poses new challenges for the MDE community.
The International Workshop on Model-Driven Engineering for Smart IoT Systems is one of the most accurate venues to offer researchers a dedicated forum to discuss fundamental as well as applied research that attempts to exploit model-driven techniques in the IoT domain.
Topics of Interests
Runtime models and operation of smart IoT systems: The operation of large-scale and highly distributed IoT systems can easily overwhelm operation teams. Approaches based on runtime models can reduce the burden by automating typical operation activities.
Model-based Deployment and Orchestration IoT Systems: Given the increasing number of IoT and Edge devices running in various contexts, as well as the widely adopted continuous delivery practices, the automation and abstractions offered by MDE can help Smart IoT Systems developers in maintaining multiple application versions and frequently (re-)deploy them.
Model-based testing: Because of the intrinsic complexity of Smart IoT Systems, the use of model-based testing approaches provides a considerable improvement in their development, testing, and maintenance.
Multi-view modeling for IoT: Complex IoT systems often involve many domains. Specific views of the system help the experts with analysis and decision making in their sub-domain.
Code generation: Code generators simplify the developing tasks proving developers with a partial (even complete) source code automatically generated from the smart IoT system models.
Simulation of physical systems and things : analysis and validation using simulation is a helpful tool in systems engineering and MDE in its nature can contribute to this task applied to smart IoT system development, especially with the concept of Digital Twin.
DSMLs for Smart IoT systems : a tailored representation at the right level of abstraction streamlines the identification of the actors, processes, data, and the relations that can occur within smart IoT systems.
Trustworthiness of smart IoT systems: The engineering of Smart IoT Systems tends to lack an integration with security engineering. Model-based analysis, verification and validation techniques can also play a key role in ensuring the trustworthiness of Smart IoT Systems.
Integration of IoT, Fog, and Cloud Computing spaces: As the Smart city system scales up, it is critical to provide interoperability among different services and devices. Model transformations can be used core ingredients for the interoperability of the systems.
Modeling techniques that enable Multi-Criteria Decision Making (MCDM) to migrate to the Edge and IoT spaces.
Megamodeling: points at integrating different scales of the system. For instance, in a smart city that could include: Buildings, Areas, districts, up to the City or Country level.