About

While most cloud services operate on a best-effort basis and provide no timing guarantees, there is a growing interest in cloud technologies for industrial and safety-critical applications.
Edge/Fog computing has emerged as a paradigm that brings computing and storage resources closer to the user, offering benefits such as low latency, high bandwidth, and enhanced privacy, while still maintaining the scalability of the cloud. Driven by the surge of AI/ML workloads and the need for intelligent, responsive systems, Edge/Fog computing is increasingly becoming extensions of the cloud continuum. By moving compute and storage closer to where data is generated, they enable real-time analytics, adaptive AI models, and secure and robust on-device intelligence, while maintaining the flexibility and scalability of traditional cloud environments.

All this makes it attractive for real-time and cyber-physical systems (CPS). However, a higher degree of determinism and timing failure resiliency is still desired for cloud/edge technologies to be fully embraced by the real-time/safety-critical industry. This calls for new methodologies and techniques to design predictable and reliable cloud/edge technologies and applications of the future. Indeed, all the above requirements should be covered in all layers of a cloud/edge stack:

• The compute layer, with a focus on virtualization technologies (e.g., VMM/hypervisors), must provide deterministic and robust behavior.
• The network layer has to provide bounded and controllable communication latencies. For example, in time-sensitive networks (TSN), this implies a need for a higher-level controller integrated with the cloud orchestrator.
• The storage layer, such as messaging and storage services, needs to guarantee latency bounds.
• The management and orchestration layer, which includes services like scaling, resource management, and orchestration, must be aware of the real-time requirements and use appropriate techniques.

The 5th International Workshop on Real-time and Cyber-Physical Cloud (RT-Cloud) aims to bring together industrial and academic researchers and become a forum for discussing topics (including ideas, open and upcoming challenges, use cases, initiatives, calls to action, and projects, regulations and standards, future research directions, etc.) related to real-time cloud/edge/fog computing and virtualization techniques.

Following the success of the first, second, third, and fourth editions, the fifth edition of the workshop will be held in Lund, Sweden, on July 7, 2026, as one of the ECRTS 2026 workshops.

Call for Papers

Topics covered by the RT-Cloud workshop are related to three pillars:

• Real-Time Computing & Virtualization
  • Designing predictable, time-sensitive systems through:
    • Real-time operating systems and mixed-criticality scheduling
    • Hardware-assisted virtualization for embedded platforms
    • Timing analysis, system partitioning, and formal verification
• Cloud Computing & Orchestration
  • Modern distributed architectures across cloud-edge infrastructures, including:
    • Containerization, microservices, and orchestration (e.g., Kubernetes)
    • Edge and fog computing for low-latency applications
    • Secure, scalable deployment strategies for industrial CPS
• Industrial Use Cases
  • Real-world applications and challenges in:
    • Automotive, aerospace, robotics, and manufacturing
    • Cyberphysical integration, digital twins, and IoT
    • Standards, safety certification, and innovation ecosystems

Original full and short papers on all aspects of real-time/safety-critical cloud/edge/fog and virtualization are welcome. Researchers are encouraged (but not limited) to submit papers regarding the following:

Use cases and applications for RT-cloud

• Use of cloud computing principles to improve performance/safety/security in existing real-time use cases
• Real-time cloud and edge applications and use cases
  • Real-time / safety-critical applications as a cloud-based service
  • Use case requirements, e.g., automation and cloud robotics systems
  • Experiments and experiences
  • Decomposition between the edge, fog, and cloud

Virtualization and cloud computing technologies/models for RT-cloud

• Deterministic hypervisors and cloud execution environments, including containers and WebAssembly
  • Real-time extension to existing cloud-computing technologies, e.g., Kubernetes
• Real-time Saas, PaaS, IaaS, and XaaS (anything as a service model)
• Execution and deployment models for RT-Cloud, including serverless compute
  • Modeling of network and cloud, execution stacks, and applications
• Microservices Architectures for real-time system
• Development Operations (DevOps) for RT-cloud
• Edge-cloud-IoT continuum and interaction/interfacing

Resource management (including monitoring, scheduling) and orchestration for RT-cloud

• Predictable orchestration and cloud operation, e.g., how to allocate and configure cloud resources within a bounded time
• Tools and techniques for resource sharing and isolation
• End-to-end resource management and resource scheduling in the edge-to-cloud continuum
• Co-scheduling of virtual network and compute resources
• QoS mechanisms, isolation guarantees
• Autonomous monitoring systems
• Adaptive SLAs for RT-cloud

Safety and Security for RT-cloud

• Assurance, deterministic scaling, fail-over, migration, etc.
• Trusted RT-Cloud/edge environment
  • Considering security and privacy together with safety

Further, this year, the workshop will have a focus on new frontiers like Edge AI, LLMs, Agentic Edge AI, in the field of real-time and cyber-physical cloud, including:

• Edge AI and on-device intelligence for time-critical systems.
• LLMs and Agentic AI in real-time and edge environments, exploring their use in autonomous orchestration, monitoring, and adaptive control of distributed systems.
• Security, Privacy, and Trustworthiness in Cyber-Physical Cloud Infrastructures.
• Integration of AI-based optimization with cloud/edge resource management under timing constraints.

The workshop also welcomes submissions that consider:

• Innovative approaches/ideas, including work-in-progress
• Open problems and upcoming challenges
• New technologies
• Regulations and standards
• Demos and tutorials, especially for open-source projects
• Call to actions
• Experimental reports on existing technologies, including negative experiences

Important Dates

• Submission Deadline: May 14, 2026 (AoE)
• Acceptance Notification: June 6, 2026
• Workshop: July 7, 2026

Information about early registration can be found at this link.

Submission Instructions

The RT-Cloud workshop aims to bring together industrial and academic researchers and serve as a forum for discussing topics related to real-time cloud/edge/fog computing and virtualization techniques. This year, the workshop will have a focus on new frontiers like Edge AI, LLMs, Agentic Edge AI, in the field of real-time and cyber-physical cloud, including:

• Innovative approaches/ideas, including work-in-progress
• Open problems and upcoming challenges
• New technologies
• Regulations and standards
• Demos and tutorials, especially for open-source projects
• Calls to action
• Experimental reports on existing technologies, including negative experiences

Manuscripts must present original work. They must be written in English, in IEEE format, and submitted via EasyChair. There are no strict rules about the number of pages, but the recommended length for full papers is 6 to 8 pages, and for short papers is 3-4 pages.

Submission link: https://easychair.org/conferences/?conf=rtcloud2026

All submissions will be reviewed by the technical program committee members, and accepted papers will be included in the workshop proceedings, which will be available online on the workshop website. Papers will not be assigned a DOI to enable authors to submit a full/extended paper later on to a conference or a journal. For every accepted paper, at least one author is expected to register for the workshop and present the paper.

Program (TBD)

Proceedings (TBD)

Workshop Chairs

• Luigi De Simone (Università degli Studi di Napoli Federico II, Italy)
• Schmidt Kevin (Bosch, Germany)

Technical Program Committee (to be completed)

• Allan Valle (TU Kaiserslautern, Germany)
• David Kozhaya (ABB Corporate Research, Switzerland)
• Harald Gustafsson (Ericsson Research, Sweden)
• Remo Andreoli (Sant’Anna School of Advanced Studies, Italy)
• Schahram Dustdar (Vienna University of Technology, Austria)
• Johan Eker (Ericsson Research, Sweden)
• Sanjoy Baruah (Washington University in St. Louis, USA)
• Mauro Marinoni Scuola Superiore Sant’Anna
• Gerhard Fohler (TU Kaiserslautern, Germany)
• Tilmann Unte (University of Augsburg, Germany)
• Isser Kadusale (TU Kaiserslautern, Germany)
• Paul Pop (Technical University of Denmark, Denmark)
• Dario Faggioli (SUSE, Italy)
• Luca Abeni (Sant’Anna School of Advanced Studies, Italy)