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边缘计算资源调度方法基于容器弹性缩放

Huaijun Wang1, Erhao Deng1, Junhuai Li1

  • 1School of Computer Science and Engineering, Xi'an University of Technology, Xi'an, Shaanxi, China.

PeerJ. Computer science
|December 9, 2024
PubMed
概括

本研究介绍了边缘计算的弹性容器扩展策略,提高了资源利用率和响应时间. 趋势增强时间卷积网络 (TE-TCN) 准确预测容器负载,优化边缘资源调度.

关键词:
容器弹性缩放容器的弹性缩放.卷积神经网络是一种卷积神经网络.负载预测的预测.强化学习是一种强化学习.

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