SS10 - Edge-to-Cloud Data-driven Distributed Industrial Cyber Physical Systems
Special Session Organized by |
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Udayanto Dwi Atmojo, Dept. of Electrical Engineering and Automation, Aalto University, Finland, and Rui Pinto, FEUP University of Porto, Portugal, and Valeriy Vyatkin, Dept. of Electrical Engineering and Automation, Aalto University, Finland, and Pouria Sayyad Khodashenas, Huawei Technologies Sweden, Sweden, |
Download Call for Papers |
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Click here to download the session cfp.
Focus |
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Cloud and edge computing provide new opportunities in exploiting industrial data and decision-making within industrial cyber-physical systems. For industrial sectors with a high degree of safety and resilience, they require mechanisms and approaches that achieve the right balance in processing, analytics, and control/automation across the cloud, edge, and IoT computing continuum to fulfill real-time, reliability, and cybersecurity requirements. As such, computing, networking (such as 5G), and data storage technologies require novel enablers to establish a high level of flexibility, data governance that facilitate trustworthy data sharing, distributed intelligence, and autonomy. Increased challenges and complexity are foreseen as emerging scenarios are increasingly cross-sector.
Topics under this session include (but not limited to) |
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- Trustworthy (including, but not limited to: security, privacy, safety, etc) assurance mechanisms, methods for industrial cyber-physical systems
- Edge artificial intelligence / Edge AI for industrial cyber-physical systems
- Zero-touch resource allocation, orchestration, network management for edge-cloud enabled industrial cyber-physical systems
- Enhancements, novel middleware, deployment strategies for advanced connectivity technologies (e.g., 5G NPN, TSN integration to 5G, etc) in edge-cloud enabled industrial cyber-physical systems
- Interoperability measures (e.g., semantics, data model, etc) for industrial cyber-physical systems, also in cross-sector cases, e.g., Asset administration shell (AAS)
- Quantum-based algorithms, communications, methods, simulations across IoT-edge-cloud continuum for industrial cyber-physical systems
- Federated, distributed intelligence across IoT-edge-cloud continuum for industrial cyber-physical systems.
- Fault tolerance, resilience mechanisms across IoT-edge-cloud continuum for industrial cyber-physical systems
- Generative, foundational models and their applications across IoT-edge-cloud continuum for industrial cyber-physical systems
- Methods, mechanisms, technologies for trustworthy data sharing involving edge-cloud-IoT continuum of industrial cyber-physical systems.
- Edge-enabled analytics, decision making, control and automation for industrial cyber-physical systems
- Eco-aware, sustainability, energy efficiency technologies, methods, mechanisms for industrial cyber-physical systems utilizing edge-cloud computing continuum
- Testbeds, research and pilot infrastructures for testing, validation, demonstration of edge-cloud computing, edge AI considering industrial cyber-physical systems setting.
- Performance evaluation, testing, validation, demonstration of edge-cloud computing, edge AI considering industrial cyber-physical systems setting.
- Methods, mechanisms for self-X (self-healing, self-organization, self-repair, etc) considering edge-cloud computing continuum in industrial cyber-physical systems setting.
- Methods, approaches for engineering edge-cloud computing enabled industrial cyber-physical systems.
- Education on edge-cloud computing for industrial cyber-physical systems