TY - GEN
T1 - MEDAL: An AI-Driven Data Fabric Concept for Elastic Cloud-to-Edge Intelligence
AU - Theodorou, V.
AU - Gerostathopoulos, I.
AU - Alshabani, I.
AU - Abelló, A.
AU - Breitgand, D.
PY - 2021
Y1 - 2021
N2 - Current Cloud solutions for Edge Computing are inefficient for data-centric applications, as they focus on the IaaS/PaaS level and they miss the data modeling and operations perspective. Consequently, Edge Computing opportunities are lost due to cumbersome and data assets-agnostic processes for end-to-end deployment over the Cloud-to-Edge continuum. In this paper, we introduce MEDAL—an intelligent Cloud-to-Edge Data Fabric to support Data Operations (DataOps) across the continuum and to automate management and orchestration operations over a combined view of the data and the resource layer. MEDAL facilitates building and managing data workflows on top of existing flexible and composable data services, seamlessly exploiting and federating IaaS/PaaS/SaaS resources across different Cloud and Edge environments. We describe the MEDAL Platform as a usable tool for Data Scientists and Engineers, encompassing our concept and we illustrate its application though a connected cars use case.
AB - Current Cloud solutions for Edge Computing are inefficient for data-centric applications, as they focus on the IaaS/PaaS level and they miss the data modeling and operations perspective. Consequently, Edge Computing opportunities are lost due to cumbersome and data assets-agnostic processes for end-to-end deployment over the Cloud-to-Edge continuum. In this paper, we introduce MEDAL—an intelligent Cloud-to-Edge Data Fabric to support Data Operations (DataOps) across the continuum and to automate management and orchestration operations over a combined view of the data and the resource layer. MEDAL facilitates building and managing data workflows on top of existing flexible and composable data services, seamlessly exploiting and federating IaaS/PaaS/SaaS resources across different Cloud and Edge environments. We describe the MEDAL Platform as a usable tool for Data Scientists and Engineers, encompassing our concept and we illustrate its application though a connected cars use case.
U2 - 10.1007/978-3-030-75078-7_56
DO - 10.1007/978-3-030-75078-7_56
M3 - Conference contribution
SN - 9783030750770
VL - 3
T3 - Lecture Notes in Networks and Systems
SP - 561
EP - 571
BT - Advanced Information Networking and Applications
A2 - Barolli, Leonard
A2 - Woungang, Isaac
A2 - Enokido, Tomoya
PB - Springer Science and Business Media Deutschland GmbH
T2 - 35th International Conference on Advanced Information Networking and Applications, AINA 2021
Y2 - 12 May 2021 through 14 May 2021
ER -