TY - GEN
T1 - OASEES
T2 - 21st International Symposium on Distributed Computing and Artificial Intelligence, DCAI 2024
AU - Kourtis, M. A.
AU - Gutierrez, I.
AU - Areizaga, E.
AU - Alexandridis, G.
AU - Tavernier, W.
AU - Imeri, A.
AU - Tcholtchev, N.
AU - Xilouris, G.
AU - Trakadas, P.
AU - Chochliouros, I.
AU - Koufos, I.
N1 - Publisher Copyright:
© The Author(s), under exclusive license to Springer Nature Switzerland AG 2025.
PY - 2025
Y1 - 2025
N2 - 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.
AB - 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.
KW - AI
KW - DAO
KW - blockchain
KW - cloud hosting
KW - compute continuum
KW - decentralized applications
KW - edge computing
KW - edge processing
UR - https://www.scopus.com/pages/publications/105005935883
U2 - 10.1007/978-3-031-76459-2_29
DO - 10.1007/978-3-031-76459-2_29
M3 - Conference contribution
AN - SCOPUS:105005935883
SN - 9783031764585
T3 - Lecture Notes in Networks and Systems
SP - 311
EP - 318
BT - Distributed Computing and Artificial Intelligence, Special Sessions I, 21st International Conference
A2 - Mehmood, Rashid
A2 - Hernández, Guillermo
A2 - Praça, Isabel
A2 - Wikarek, Jaroslaw
A2 - Loukanova, Roussanka
A2 - Monteiro dos Reis, Arsénio
A2 - Skarmeta, Antonio
A2 - Lombardi, Eleonora
PB - Springer Science and Business Media Deutschland GmbH
Y2 - 25 June 2024 through 27 June 2024
ER -
