Local Scheduling in KubeEdge-Based Edge Computing Environment

KubeEdge is an open-source platform that orchestrates containerized Internet of Things (IoT) application services in IoT edge computing environments. Based on Kubernetes, it supports heterogeneous IoT device protocols on edge nodes and provides various functions necessary to build edge computing inf...

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Veröffentlicht in:Sensors (Basel, Switzerland) Jg. 23; H. 3; S. 1522
Hauptverfasser: Kim, Seong-Hyun, Kim, Taehong
Format: Journal Article
Sprache:Englisch
Veröffentlicht: Switzerland MDPI AG 30.01.2023
MDPI
Schlagworte:
Accuracy
Artificial intelligence
Cloud computing
Communication
Containerization (Freight)
edge computing
EdgeMesh
Internet of Things
KubeEdge
Kubernetes
load balancer
microservice
Performance evaluation
Quality of service
Scheduling
Software
load balancer
EdgeMesh
KubeEdge
edge computing
microservice
Kubernetes
ISSN:1424-8220, 1424-8220
Online-Zugang:Volltext
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Beschreibung
Zusammenfassung:KubeEdge is an open-source platform that orchestrates containerized Internet of Things (IoT) application services in IoT edge computing environments. Based on Kubernetes, it supports heterogeneous IoT device protocols on edge nodes and provides various functions necessary to build edge computing infrastructure, such as network management between cloud and edge nodes. However, the resulting cloud-based systems are subject to several limitations. In this study, we evaluated the performance of KubeEdge in terms of the computational resource distribution and delay between edge nodes. We found that forwarding traffic between edge nodes degrades the throughput of clusters and causes service delay in edge computing environments. Based on these results, we proposed a local scheduling scheme that handles user traffic locally at each edge node. The performance evaluation results revealed that local scheduling outperforms the existing load-balancing algorithm in the edge computing environment.
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ISSN:1424-8220
1424-8220
DOI:10.3390/s23031522