The massive increase in device connectivity and the data generated has resulted in the multiplication of intelligent processing services for creating information and exploiting data in various ways. Currently, the most powerful data processing operates centrally in the cloud, which provides scalability and efficient resource allocation on demand. Centralized processing and hosting in the cloud, however, binds and limits services and applications to operate with restricted resources, as it relies on large, singular computational entities for the provision of:
- Authentication
- Data Storage
- Data Processing and
- Connectivity for development and orchestration.
This significantly restricts the user from managing data as well as identity management. Similarly, existing solutions for controlling authentication in edge devices require a central entity to identify them and establish trust.
The project aims to create an open, decentralized, intelligent, and programmable edge framework for Swarm architectures and applications, leveraging the concept of Decentralized Autonomous Organization (DAO) and integrating Human-in-the-Loop (HITL) processes for effective decision-making. The vision of OASEES is to provide open tools and secure environments for programming and orchestration across multiple fields, with a fully decentralized approach. A key factor in this process is identity recognition and management, where OASEES targets the implementation of a portable multi-layer identity recognition system that safeguards personal privacy for edge devices and services, fully compliant with the guidelines and specifications of the GAIA-X federation and the IDSA.
This situation highlights the need for a comprehensive activation framework adapted to the extreme data processing requirements at the edge, utilizing various edge accelerators such as GPUs, NPUs, SNNs, and Quantum technologies.
