OASEES: Leveraging DAO-Based Programmable Swarms for Optimized Edge-to-Cloud Data Processing

Abstract

As traditional linear models stagnate decision-making and data federation, there’s a pressing need for a novel, swarm-based cloud-edge computing approach to enhance European data sovereignty and foster a sustainable, circular economy across various market sectors. To that end, the EU-backed OASEES project identifies a need for an innovative, inclusive, and disruptive approach to the cloud-to-edge continuum, swarm programmability, and data federation over GAIA-X. This paper underscores the actual challenges associated with managing and orchestrating edge infrastructure and services, thereby harnessing the potential of edge processing and federated learning. Moreover, it delves into the core features of the OASEES approach, taking into account technological challenges anticipated in system development. We also explore the integration of multi-tenant, interoperable, secure, and trustworthy deployments into the cloud-to-edge paradigm, in line with the conference’s scope. Briefly, we discuss several vertical edge applications with substantial market impact, demonstrating how our approach partially addresses the existing gaps and contributes to a decentralized AI ecosystem.