The last years have witnessed a permanent change of vision of cloud systems. Nowadays, the most important stakeholders such as private companies, public agencies, research communities and citizens rely on the cloud for a number of purposes, stemming from sharing hardware infrastructures to software, data, and sensing services.

The services designed for complex scenarios like MEC, Internet of Things, smart cities, and the upcoming Industry 4.0, pave the path for a new era of the cloud. The complexity of human dynamics in a city can be better analyzed by decentralizing the infrastructure, integrating and opening the data and sharing the services.

The MEC paradigm, standardized by ETSI, is a key enabling technology for upcoming 5G networks, whereby applications and network functions are hosted in edge cloud data centers.

By being closer to the end-user, besides better supporting low-latency applications, MEC systems are a candidate architecture for such a decentralized, context-aware infrastructure. Despite such a rapid (re-)evolution of edge-cloud systems, the extremely heterogeneous smart city applications (sensing as a service, crowd sensing, etc.) makes the satisfactions of all the requirements a big challenge.

In this context, emergent paradigms like artificial intelligence (AI), machine learning (ML), privacy-enhancing technologies (PET) and blockchain (BC) are key enablers for edge systems to shape the development of autonomic orchestration and networking.

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

• Application of cloud and MEC systems to smart cities services.

• Models for context-aware crowdsensing techniques at urban-level scale.

• Human-enabled Edge Computing (HEC) paradigm.

• Cloud to Edge continuum.

• Edge data center deployment in urban environments.

• Cloud quantum service model.

• Hybrid quantum for smart city systems.

• ML- and AI-based approaches cloud/edge-based smart city applications.

• AI-driven models, architectures, and frameworks for edge computing.

• Experiences on the (re)use of open platforms for cloud-integrated smart cities services.

• Design and evaluation tools for scalability and efficient resource allocation in smart cities.

• Design and application of cloud/edge technologies to Intelligent Transport Systems (ITS).

• Vehicular cloud architectures for provisioning of smart cities services.

• Models and paradigms for the management of cloud/MEC services within/between data.

• Data-driven approaches for smart transportation in urban areas.

• Blockchain solutions for secure and reliable transactions between the counterparts in data sharing/trading.

• Security and privacy techniques to cloud/edge-based smart city applications.

• Post-quantum security and privacy for smart city applications.

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