适应性容错机制,以确保分布式边缘计算系统中数字双胞胎的高可用性
Dinesh Sahu1, Nidhi1, Shiv Prakash2
1SCSET, Bennett University, Plot Nos 8, 11, TechZone 2, Greater Noida, Uttar Pradesh, 201310, India.
Scientific reports
|November 25, 2025
概括
本研究介绍了边缘计算中数字双胞胎 (DTs) 的自适应性故障耐受性框架. 它在动态环境中提高了DT的可靠性和可用性,确保了持续运行,降低了成本.
科学领域:
- 计算机科学 计算机科学
- 分布式系统 分布式系统
- 人工智能的人工智能
背景情况:
- 数字双胞胎 (DTs) 在边缘计算中越来越多地被采用,要求高可用性和可靠性.
- 边缘环境为DT运营带来了动态和资源受限的挑战.
- 现有的容错机制可能无法充分解决分布式边缘计算的复杂性.
研究的目的:
- 介绍一个适应性故障耐受性框架,以保持边缘计算中的连续数字双胞胎运行.
- 为了减轻边缘节点故障,最大限度地减少停机时间,并确保无的DT实例迁移.
- 在动态,资源有限的边缘环境中增强系统的弹性和性能.
主要方法:
- 开发了一种用于自适应故障耐受性 (HGPAFT) 的混合基因-PSO算法.
- 集成实时监控和预测性故障检测.
- 根据网络条件实施适应性资源重新分配和DT实例迁移策略.
主要成果:
- 实现了数字生实例的恢复概率超过98%.
- 与传统方法相比,重新分配和迁移成本减少了多达20%.
- 在边缘计算环境中优化能源消耗和资源利用.
结论:
- 拟议的自适应性容错框架确保了分布式边缘计算中数字双胞胎的可扩展和节能运行.
- HGPAFT算法有效地提高了系统的弹性和可靠性.
- 这项研究为异质边缘网络中的连续和可靠的数字双胞胎服务提供了强大的解决方案.
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