Article (Scientific journals)
A Cloud-Edge Continuum Experimental Methodology applied to a 5G Core Study
Rac, Samuel; Sanyal, Rajarshi; Brorsson, Mats Hakan
2022In Transactions on Computational Science and Computational Intelligence
Peer reviewed
 

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Keywords :
edge computing; experimental methodology; 5G
Abstract :
[en] There is an increasing interest in extending traditional cloud-native technologies, such as Kubernetes, outside the data center to build a continuum towards the edge and between. However, traditional resource orchestration algorithms do not work well in this case, and it is also difficult to test applications for a heterogeneous cloud infrastructure without actually building it. To address these challenges, we propose a new methodology to aid in deploying, testing, and analyzing the effects of microservice placement and scheduling in a heterogeneous Cloud environment. With this methodology, we can investigate any combination of deployment scenarios and monitor metrics in accordance with the placement of microservices in the cloud-edge continuum. Edge devices may be simulated, but as we use Kubernetes, any device which can be attached to a Kubernetes cluster could be used. In order to demonstrate our methodology, we have applied it to the problem of network function placement of an open-source 5G core implementation.
Research center :
- Interdisciplinary Centre for Security, Reliability and Trust (SnT) > SEDAN - Service and Data Management in Distributed Systems
Disciplines :
Computer science
Author, co-author :
Rac, Samuel  ;  University of Luxembourg > Interdisciplinary Centre for Security, Reliability and Trust (SNT) > SEDAN
Sanyal, Rajarshi;  Proximus Luxembourg SA
Brorsson, Mats Hakan  ;  University of Luxembourg > Interdisciplinary Centre for Security, Reliability and Trust (SNT) > SEDAN
External co-authors :
no
Language :
English
Title :
A Cloud-Edge Continuum Experimental Methodology applied to a 5G Core Study
Publication date :
2022
Journal title :
Transactions on Computational Science and Computational Intelligence
Publisher :
Springer Cham
Peer reviewed :
Peer reviewed
FnR Project :
FNR16327771 - Accelerated Cloud Edge In 5g, 2021 (01/02/2022-31/01/2025) - Mats Brorsson
Name of the research project :
ACE5G
Funders :
Fonds National de la Recherche - FnR ; Proximus Luxembourg SA
Available on ORBilu :
since 27 January 2023

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