AORTA: Advanced Offloading for Real-time Applications
Balador, Ali ; Eker, Johan ; Ul Islam, Raihan ; Mini, Raquel ; Nilsson, Klas ; Ashjaei, Mohammad ; Mubeen, Saad ; Hansson, Hans and Årzén, Karl-Erik LU
(2023)
Real-Time Cloud (RT-CLOUD), 2023
- Abstract
- We are currently witnessing the second wave of cloud services that go beyond web storefronts and IT systems, aiming for digitalization of industrial systems. Automation and time-sensitive systems are now taking their first steps toward the cloud. The AORTA project aims to facilitate this transition by providing key technology components needed for real-time services running in the cloud. The ambition is to support a future robotics ecosystem that enables a new level of flexible productivity in industrial production. AORTA will develop technologies that allow offloading of real-time services/functions to the edge and cloud. We will build upon recent advances in 5G, cloud, and networking technologies. The AORTA framework will support a fluid... (More)
- We are currently witnessing the second wave of cloud services that go beyond web storefronts and IT systems, aiming for digitalization of industrial systems. Automation and time-sensitive systems are now taking their first steps toward the cloud. The AORTA project aims to facilitate this transition by providing key technology components needed for real-time services running in the cloud. The ambition is to support a future robotics ecosystem that enables a new level of flexible productivity in industrial production. AORTA will develop technologies that allow offloading of real-time services/functions to the edge and cloud. We will build upon recent advances in 5G, cloud, and networking technologies. The AORTA framework will support a fluid compute model where functionality will be dynamically deployed locally, in the edge, or in the cloud and support integration and real-time performance irrespective of where it executes. Results of the project will be demonstrated in a real-world robotics manufacturing and construction scenarios operating via a 5G network with real-time edge and large-scale cloud service. The AORTA technologies will provide opportunities for automation enterprises and system integrators by adding real-time capabilities needed to evolve beyond the currently closed ecosystem. They will also add value to telecom providers and operators that may host these new automation services in addition to their current portfolio. (Less)
Please use this url to cite or link to this publication:
https://lup.lub.lu.se/record/8fc5c69a-25e1-4ce8-9b4d-2211923e36a0
- author
- Balador, Ali
; Eker, Johan
; Ul Islam, Raihan
; Mini, Raquel
; Nilsson, Klas
; Ashjaei, Mohammad
; Mubeen, Saad
; Hansson, Hans
and Årzén, Karl-Erik
LU
- organization
- publishing date
- 2023-07-11
- type
- Contribution to conference
- publication status
- published
- subject
- conference name
- Real-Time Cloud (RT-CLOUD), 2023
- conference location
- Vienna, Austria
- conference dates
- 2023-07-11 - 2023-07-11
- project
- AORTA: Advanced Offloading for Real-Time Applications
- language
- English
- LU publication?
- yes
- id
- 8fc5c69a-25e1-4ce8-9b4d-2211923e36a0
- date added to LUP
- 2023-10-13 14:59:27
- date last changed
- 2023-10-16 09:15:45
@misc{8fc5c69a-25e1-4ce8-9b4d-2211923e36a0,
abstract = {{We are currently witnessing the second wave of cloud services that go beyond web storefronts and IT systems, aiming for digitalization of industrial systems. Automation and time-sensitive systems are now taking their first steps toward the cloud. The AORTA project aims to facilitate this transition by providing key technology components needed for real-time services running in the cloud. The ambition is to support a future robotics ecosystem that enables a new level of flexible productivity in industrial production. AORTA will develop technologies that allow offloading of real-time services/functions to the edge and cloud. We will build upon recent advances in 5G, cloud, and networking technologies. The AORTA framework will support a fluid compute model where functionality will be dynamically deployed locally, in the edge, or in the cloud and support integration and real-time performance irrespective of where it executes. Results of the project will be demonstrated in a real-world robotics manufacturing and construction scenarios operating via a 5G network with real-time edge and large-scale cloud service. The AORTA technologies will provide opportunities for automation enterprises and system integrators by adding real-time capabilities needed to evolve beyond the currently closed ecosystem. They will also add value to telecom providers and operators that may host these new automation services in addition to their current portfolio.}},
author = {{Balador, Ali and Eker, Johan and Ul Islam, Raihan and Mini, Raquel and Nilsson, Klas and Ashjaei, Mohammad and Mubeen, Saad and Hansson, Hans and Årzén, Karl-Erik}},
language = {{eng}},
month = {{07}},
title = {{AORTA: Advanced Offloading for Real-time Applications}},
url = {{https://lup.lub.lu.se/search/files/161851101/AORTA_RT_Cloud_2023_4_.pdf}},
year = {{2023}},
}