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Local Scheduling in KubeEdge-Based Edge Computing Environment
1School of Information and Communication Engineering, Chungbuk National University, Cheongju 28644, Republic of Korea.
Sensors (Basel, Switzerland)
|February 11, 2023
Summary
KubeEdge
Area of Science:
- Edge Computing
- Internet of Things (IoT)
Background:
- KubeEdge is an open-source platform for orchestrating containerized IoT services in edge computing.
- It supports diverse IoT protocols and network management but faces limitations in cloud-based systems.
Purpose of the Study:
- To evaluate KubeEdge performance regarding resource distribution and delay in edge computing.
- To address limitations of cloud-based systems in KubeEdge.
Main Methods:
- Evaluated KubeEdge performance on computational resource distribution and inter-edge node delay.
- Proposed and evaluated a local scheduling scheme for edge nodes.
Main Results:
- Forwarding traffic between edge nodes reduces cluster throughput and increases service delay.
- The proposed local scheduling scheme improved performance over existing load-balancing algorithms.
Conclusions:
- Traffic forwarding in KubeEdge negatively impacts edge computing performance.
- Local scheduling is a more effective approach for optimizing KubeEdge in edge environments.
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