CAPE is a European-funded project targeting to reshape edge-cloud computing by defining edge micro data centers as a new unit of computing. Fully committing to open source, CAPE develops a fully Composable Infrastructure (CI) for high-performance edge server hardware platforms grounded in open, forward-looking standards. Together with an open-source software stack covering the Edge-Cloud Continuum, this holistic approach boosts power and energy efficiency while reducing resource overprovisioning. Completely based on open standards, CAPE strengthens the digital sovereignty Europe needs in a challenging future. This work gives an overview of the current architectural blueprint of the project, focusing on integrating game-changing technologies like Compute Express Link (CXL) for compute and memory disaggregation, pushing open source cluster management, and AI-assisted deployment software stacks using Infrastructure from Code (IfC). The proposed approaches and benefits for future Edge-Cloud data centers are demonstrated within three use cases, ranging from Smart Grid and Edge-AI to Satellite Data Processing.

The EU-funded EMPYREAN project (empyrean-horizon.eu) aims to establish a hyper-distributed computing paradigm, leveraging collaborative, heterogeneous IoT devices and federated resources. EMPYREAN focuses on developing technologies for efficient AI workload processing, secure distributed edge storage and cloud-native application development. It will offer open and standardised APIs and use open-source platforms. EMPYREAN's capabilities will be demonstrated through three use cases: advanced manufacturing, smart agriculture, and warehouse automation.

Advances in internetworking technology and the decreasing cost-performance ratio of commodity computing components have enabled Volunteer Computing (VC). VC platforms aggregate tens or hundreds of thousands of hosts. These hosts are typically volatile, which raises difficult research questions. Most research in this area relies on simulation. The main issue when developing VC simulators is scalability: How to perform simulations of large-scale VC platforms with reasonable amounts of memory and reasonably fast? To achieve scalability, state-of-the-art VC simulators employ simplistic simulation models and/or target on narrow platform and application scenarios. In this paper we enable VC simulations using the general-purpose SimGrid simulation framework, which provides significantly more realistic and flexible simulation capabilities than the aforementioned simulators. Our key contribution is a set of improvements to SimGrid so that it brings these benefits to VC simulations while achieving good scalability.