Seong-Hyun Kim’s research while affiliated with Chungbuk National University and other places

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Publications (1)


Local Scheduling in KubeEdge-Based Edge Computing Environment
  • Article
  • Full-text available

January 2023

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223 Reads

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19 Citations

Sensors

Seong-Hyun Kim

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Taehong Kim

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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Citations (1)


... It automates container deployment, scaling, and monitoring, ensuring optimal resource use and reliability. Seong et al. [11] evaluated KubeEdge's resource distribution and latency performance, proposing a local scheduling scheme that showed improvements over standard load-balancing algorithms. Kjorveziroski et al. [12] compared Kubernetes, K3s, and MicroK8s in resource-constrained settings with 14 benchmarks, finding that K3s and MicroK8s generally offered better performance, although Kubernetes excelled under sustained loads. ...

Reference:

Edge System Design Using Containers and Unikernels for IoT Applications
Local Scheduling in KubeEdge-Based Edge Computing Environment

Sensors