集装箱迁移用于工业互联网的边缘计算,同时减少延迟和提高可靠性
Xiaomin Jin1,2,3, Shengsheng He4,5,6, Yanping Chen4,5,6
1School of Computer Science and Technology, Xi'an University of Posts and Telecommunications, Xi'an, 710121, China. xmjin@xupt.edu.cn.
Scientific reports
|October 25, 2024
概括
本研究涉及工业互联网边缘计算中的容器迁移. 一个优化模型和一个改进的鱼优化算法减少了延迟,提高了可靠性,提高了超过15%的性能.
科学领域:
- 信息技术 信息技术 信息技术
- 边缘计算 边缘计算
- 工业互联网 工业互联网 工业互联网
背景情况:
- 边缘计算对于工业互联网至关重要,需要精确的容器迁移以实现速度和运营连续性.
- 边缘计算中的容器迁移挑战包括平衡延迟减少和可靠性增强.
研究的目的:
- 探索工业互联网边缘计算中的容器迁移.
- 为了减少延迟并提高集装箱迁移的可靠性.
- 建立一个系统的框架来平衡延迟和可靠性.
主要方法:
- 为容器迁移制定一个双目标优化模型.
- 基于改进的二进制优化算法的迁移算法的开发.
- 在算法的运算中纳入自适应概率和自适应位置权重.
主要成果:
- 建立的优化模型有效地降低了目标价值.
- 拟议的迁移算法显著提高了搜索效率.
- 实验结果显示,与现有算法相比,目标值的平均减少至少为15.59%.
结论:
- 拟议的模型和算法有效地解决了边缘计算中的容器迁移挑战.
- 该方法提供了一个系统的框架来优化延迟和可靠性.
- 改进的二进制鱼优化算法在集装箱迁移中表现出卓越的性能.
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