The grand challenge of this project is to create the basis for a paradigm shift in the way music is performed and experienced, by leveraging the new creative possibilities offered by the emerging Musical Metaverse. The consortium aims to achieve this ambitious challenge by means of i) a socio-cognitive breakthrough, by gaining a deep understanding of the emerging needs and concerns of contemporary musicians and audiences via collaborative design activities and neuro-physiological measurements; ii) a technological breakthrough, by developing radically novel concert platforms and devices that can exchange information among each other via ultra-reliable low-latency wireless networks, with privacy and security constraints; iii) a musical breakthrough, by creating novel concert formats that exploit the technological and socio-cognitive breakthroughs. This project uses an interdisciplinary methodology that combines Human-Computer Interaction, Engineering, Cognition, and Music, drawing from the scientific excellence of the partners. Industrial partners will provide know-how for proof of concept prototypes. Through this disruptive approach, the project will provide a pipeline to the technological development of a new class of musical interfaces and Musical Metaverse ecosystems, whose features will go substantially beyond current systems. The proposed approach aspires to effect a step-change in the design of musical interfaces and systems to musically interact online, resulting in a potentially high economic impact on the music industry. The envisioned technological advancements for the musical domain will provide key solutions for true real-time collaborative activities in the Metaverse in general. The project involves theoretical and experimental aspects, and is a high-impact endeavour from which basic science, EU industry and society can benefit.

NebulOus will accomplish substantial research contributions in the realms of cloud and fog computing brokerage by introducing advanced methods and tools for enabling secure and optimal application provisioning and reconfiguration over the cloud computing continuum. NebulOus will develop a novel Meta Operating System and platform for enabling transient fog brokerage ecosystems that seamlessly exploit edge and fog nodes, in conjunction with multi-cloud resources, to cope with the requirements posed by low latency applications. The envisaged BRONCO solution includes the following main directions of work: i. Development of appropriate modelling methods and tools for describing the cloud computing continuum, application requirements, and data streams; these methods and tools will be used for assuring the QoS of the provisioned brokered services. ii. Efficient comparison of available offerings, using appropriate multi-criteria decision-making methods that are able to consider all dimensions of consumer requirements. iii. Intelligent applications, workflows and data streams management in the cloud computing continuum. iv. Addressing in a unified manner the security aspects emerging in of transient cloud computing continuums (e.g., access control, secure network overlay etc.). v. Conducting and monitoring smart contracts-based service level agreements.

Artificial Intelligence (AI), to become fully pervasive, needs resources at the edge of the network. The cloud can provide the processing power needed for big data, but edge computing is close to where data are produced and therefore crucial to their timely, flexible, and secure management. AI-SPRINT will define a framework for developing AI applications in computing continua, enabling a finely-tuned tradeoff between performance (e.g. in terms of end-to-end latency and throughput) and AI model accuracy, while providing security and privacy guarantees. AI-SPRINT outcomes are: i) simplified programming models to reduce the steep learning curves in the development of AI software in computing continua; ii) highly specialized building blocks for distributed training, privacy preservation and advanced machine learning models, to shorten time-to-market for AI applications; iii) automated deployment and dynamic reconfiguration to decrease the cost of operating AI software. Beneficiaries include end-users of AI systems, software developers, system integrators, and cloud providers. AI-SPRINT tools will make it possible to consider security and privacy early in the design stage and to seamlessly manage the time-varying conditions typical of real environments. Real-world scenarios are an integral part of AI-SPRINT as key to guiding requirements and development and validating results. Three heterogeneous use cases (farming 4.0, maintenance & inspection, and personalized healthcare) are built by industrial partners. Cutting-edge innovation is brought to the Consortium by four research partners with complementary expertise. Two system integrators provide vision on relevant verticals and technology insights, one cloud provider brings real-world implementation expertise, and two specialists in dissemination ensure impacts and uptake. AI-SPRINT will also pursue a sustainability path through the creation of an Alliance and Adopter Acceleration club as a marketplace for AI businesses

MORPHEMIC proposes a unique way of adapting and optimizing Cloud computing applications by introducing the novel concepts of polymorph architecture and proactive adaptation. The former is when a component can run in different technical forms, i.e. in a Virtual Machine (VM), in a container, as a big data job, or as serverless components, etc. The technical form of deployment is chosen during the optimization process to fulfil the user’s requirements and needs. The quality of the deployment is measured by a user defined and application specific utility. Depending on the application’s requirements and its current workload, its components could be deployed in various forms in different environments to maximize the utility of the application deployment and the satisfaction of the user. Proactive adaptation is not only based on the current execution context and conditions but aims to forecast future resource needs and possible deployment configurations. This ensures that adaptation can be done effectively and seamlessly for the users of the application. The MORPHEMIC deployment platform will therefore be very beneficial for heterogeneous deployment in distributed environments combining various Cloud levels including Cloud data centres, edge Clouds, 5G base stations, and fog devices. Advanced forecasting methods, including the ES-Hybrid method recently winning the M4 forecasting competition, will be used to achieve the most accurate predictions. The outcome of the project will be implemented in the form of the complete solution, starting from modelling, through profiling, optimization, runtime reconfiguration and monitoring. Then the MORPHEMIC implementation will be integrated as a pre-processor for the existing MELODIC platform extending its deployment and adaptation capabilities beyond the multi-cloud and cross-cloud to the edge, 5G, and fog. This approach allows for a path to early demonstrations and commercial exploitation of the project results.

MELODIC will enable data-intensive applications to run within defined security, cost, and performance boundaries seamlessly on geographically distributed and federated cloud infrastructures. Serving the user’s needs and constraints, MELODIC will realise the potential of Cloud computing for big data and data-intensive applications by transparently taking advantage of distinct characteristics of available private and public clouds, dynamically optimise resource utilisation, consider data locality, conform to the user’s privacy needs and service requirements, and counter vendor lock-in. These benefits are achieved by integrating and extending the results and the open source platforms available from three major European Cloud projects with the Hadoop and Spark big data frameworks: The PaaSage platform will be used for intelligent and autonomic cross-cloud deployment and is extended with data aware modelling and deployment configuration reasoning; the CACTOS platform is extended with support for Hadoop and Spark in cross-Cloud application deployment and management; and the PaaSword platform will ensure unified data security and cross-Cloud privacy. MELODIC will integrate with the existing open source development teams for these platforms and the contributions will be released back to the used platforms as open source. The integrated MELODIC platform will be maintained and exploited by a professional software house, and tested in several demanding real world applications: scalable Customer Relationship Management, real-time optimised traffic routing, and fast and scalable processing of genomic data.