The main goal is to design an Extreme near-data platform to enable consumption, mining and processing of dis- tributed and federated data without needing to master the logistics of data access across heterogeneous data locations and pools. We go beyond traditional passive or bulk data ingested from storage systems towards next generation near-data processing platforms both in the Cloud and in the Edge. In our platform, Extreme Data in- cludes both metadata and trustworthy data connectors enabling advanced data management operations like data discovery, mining, and filtering from heterogeneous data sources. The three core objectives are: O-1 Provide high-performance near-data processing for Extreme Data Types: The first objective is to create a novel intermediary data service (XtremeDataHub) providing serverless data connectors that optimize data management operations (partitioning, filtering, transformation, aggregation) and interactive queries (search, discovery, matching, multi-object queries) to efficiently present data to analytics platforms. Our data connectors facilitate a elas- tic data-driven process-then-compute paradigm which significantly reduces data communication on the data interconnect, ultimately resulting in higher overall data throughput. O-2 Support real-time video streams but also event streams that must be ingested and processed very fast to Object Storage: The second objective is to seamlessly combine streaming and batch data processing for analytics. To this end, we will develop stream data connectors deployed as stream operators offering very fast stateful computations over low-latency event and video streams. O-3 The third objective is to create a Data Broker service enabling trustworthy data sharing and confidential orchestration of data pipelines across the Compute Continuum. We will provide secure data orchestration, transfer, processing and access thanks to Trusted Execution Environments (TEEs) and federated learning architectures.

SMARTY invokes a cloud-edge continuum, made from heterogeneous systems, that protects data-in-transit and data-in-process in order to offer a trustful fabric to run AI processes. The securitization occurs by employing novel accelerators for quantum resilient communications, confidential computing, software defined perimeters and swarm formation, offering multiple layers of security. Semantic programmability and graph-management open the door to drag-and-drop approaches in deploying services in a fast and reliable manner. SMARTY is proposed within the context of different key sectors in Europe : automotive, fintech, telco and industrial settings; the technology proposed in SMARTY will be matured within the lifetime of the project and tested through five use cases. SMARTY is supported by large European industry players and well as by 13 SMEs which will seek a visible platform to develop their products and gain visibility towards high-growth. SMARTY’s major suppliers and OEMs and reputable academic partners provide a great opportunity for these 13 SMEs to mature their technologies in a challenging but safe environment. The results of SMARTY are applicable to different vertical sectors and can be transported to different use cases. Strong synergies with existing efforts in the area of edge computing, European processors and trustworthy AI are envisioned and planned within SMARTY.