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...
| Main Authors: | , |
|---|---|
| Format: | Article |
| Language: | English |
| Published: |
MDPI AG
2023-01-01
|
| Series: | Sensors |
| Subjects: | |
| Online Access: | https://www.mdpi.com/1424-8220/23/3/1522 |
| _version_ | 1797623167138660352 |
|---|---|
| author | Seong-Hyun Kim Taehong Kim |
| author_facet | Seong-Hyun Kim Taehong Kim |
| author_sort | Seong-Hyun Kim |
| collection | DOAJ |
| description | 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. |
| first_indexed | 2024-03-11T09:24:49Z |
| format | Article |
| id | doaj.art-17a88a01ce8142c4ad924e606c36cbb7 |
| institution | Directory Open Access Journal |
| issn | 1424-8220 |
| language | English |
| last_indexed | 2024-03-11T09:24:49Z |
| publishDate | 2023-01-01 |
| publisher | MDPI AG |
| record_format | Article |
| series | Sensors |
| spelling | doaj.art-17a88a01ce8142c4ad924e606c36cbb72023-11-16T18:02:18ZengMDPI AGSensors1424-82202023-01-01233152210.3390/s23031522Local Scheduling in KubeEdge-Based Edge Computing EnvironmentSeong-Hyun Kim0Taehong Kim1School of Information and Communication Engineering, Chungbuk National University, Cheongju 28644, Republic of KoreaSchool of Information and Communication Engineering, Chungbuk National University, Cheongju 28644, Republic of KoreaKubeEdge 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.https://www.mdpi.com/1424-8220/23/3/1522edge computingKubernetesKubeEdgeEdgeMeshload balancermicroservice |
| spellingShingle | Seong-Hyun Kim Taehong Kim Local Scheduling in KubeEdge-Based Edge Computing Environment Sensors edge computing Kubernetes KubeEdge EdgeMesh load balancer microservice |
| title | Local Scheduling in KubeEdge-Based Edge Computing Environment |
| title_full | Local Scheduling in KubeEdge-Based Edge Computing Environment |
| title_fullStr | Local Scheduling in KubeEdge-Based Edge Computing Environment |
| title_full_unstemmed | Local Scheduling in KubeEdge-Based Edge Computing Environment |
| title_short | Local Scheduling in KubeEdge-Based Edge Computing Environment |
| title_sort | local scheduling in kubeedge based edge computing environment |
| topic | edge computing Kubernetes KubeEdge EdgeMesh load balancer microservice |
| url | https://www.mdpi.com/1424-8220/23/3/1522 |
| work_keys_str_mv | AT seonghyunkim localschedulinginkubeedgebasededgecomputingenvironment AT taehongkim localschedulinginkubeedgebasededgecomputingenvironment |