Performance Evaluation of Container Orchestration Tools in Edge Computing Environments.

Internet of Things (IoT) K3s KubeEdge Kubernetes container edge computing ioFog service orchestration service scheduling

Journal

Sensors (Basel, Switzerland)
ISSN: 1424-8220
Titre abrégé: Sensors (Basel)
Pays: Switzerland
ID NLM: 101204366

Informations de publication

Date de publication:
15 Apr 2023
Historique:
received: 21 02 2023
revised: 07 04 2023
accepted: 13 04 2023
medline: 28 4 2023
pubmed: 28 4 2023
entrez: 28 4 2023
Statut: epublish

Résumé

Edge computing is a viable approach to improve service delivery and performance parameters by extending the cloud with resources placed closer to a given service environment. Numerous research papers in the literature have already identified the key benefits of this architectural approach. However, most results are based on simulations performed in closed network environments. This paper aims to analyze the existing implementations of processing environments containing edge resources, taking into account the targeted quality of service (QoS) parameters and the utilized orchestration platforms. Based on this analysis, the most popular edge orchestration platforms are evaluated in terms of their workflow that allows the inclusion of remote devices in the processing environment and their ability to adapt the logic of the scheduling algorithms to improve the targeted QoS attributes. The experimental results compare the performance of the platforms and show the current state of their readiness for edge computing in real network and execution environments. These findings suggest that Kubernetes and its distributions have the potential to provide effective scheduling across the resources on the network's edge. However, some challenges still have to be addressed to completely adapt these tools for such a dynamic and distributed execution environment as edge computing implies.

Identifiants

pubmed: 37112349
pii: s23084008
doi: 10.3390/s23084008
pmc: PMC10143384
pii:
doi:

Types de publication

Journal Article

Langues

eng

Sous-ensembles de citation

IM

Subventions

Organisme : Croatian Science Foundation
ID : IP-2019-04-1986

Références

Sensors (Basel). 2023 Jan 30;23(3):
pubmed: 36772562
Sensors (Basel). 2022 Jan 08;22(2):
pubmed: 35062426
Sensors (Basel). 2019 Jul 05;19(13):
pubmed: 31284514
Sensors (Basel). 2019 May 14;19(10):
pubmed: 31091838
Sensors (Basel). 2023 Feb 16;23(4):
pubmed: 36850813
Sensors (Basel). 2022 Feb 23;22(5):
pubmed: 35270901
Sensors (Basel). 2018 Sep 04;18(9):
pubmed: 30181454

Auteurs

Ivan Čilić (I)

Faculty of Electrical Engineering and Computing, University of Zagreb, 10000 Zagreb, Croatia.

Petar Krivić (P)

Faculty of Electrical Engineering and Computing, University of Zagreb, 10000 Zagreb, Croatia.

Ivana Podnar Žarko (I)

Faculty of Electrical Engineering and Computing, University of Zagreb, 10000 Zagreb, Croatia.

Mario Kušek (M)

Faculty of Electrical Engineering and Computing, University of Zagreb, 10000 Zagreb, Croatia.

Classifications MeSH