在边缘计算中优化能量和延迟,通过博尔兹曼驱动的贝叶斯框架来实现自适应性资源调度.
Dinesh Sahu1, Nidhi1, Rajnish Chaturvedi1
1SCSET, Bennett University, Plot Nos 8, 11, TechZone 2, Greater Noida, Uttar Pradesh, 201310, India.
Scientific reports
|August 19, 2025
概括
本研究介绍了一种新的节能资源分配方法,用于边缘计算,使用博尔兹曼分布和贝叶斯优化. 该方法显著降低了能源消耗和延迟,超过了现有的算法,并节省了高达25%的能源.
科学领域:
- 边缘计算 边缘计算
- 资源分配 资源分配
- 优化技术 优化技术
背景情况:
- 能源效率是边缘计算的一个关键挑战.
- 现有的资源分配算法往往难以有效地平衡能源消耗和延迟.
研究的目的:
- 为边缘计算环境开发一种新的,节能资源配置战略.
- 通过先进的优化技术,尽量减少能源消耗和延迟.
主要方法:
- 一种混合方法,结合了博尔兹曼分布和贝叶斯优化.
- 使用贝叶斯优化进行代参数优化,以获得最小的能量和延迟.
- 一个博尔兹曼驱动的概率行动选择机制,具有动态温度调整以优先考虑任务.
主要成果:
- 与循环罗宾和基于值的算法相比,提出的方法显著降低了能源消耗和平均延迟.
- 与基线方法相比,实现了高达25%的累积能源节约.
- 在不同的负载条件下,经过证明的适应性和最佳调度行动的实现.
结论:
- 概率选择和参数优化的集成为节能资源调度提供了一个新的基准.
- 开发的框架适用于实时,节能边缘计算应用程序.
- 这项研究通过混合优化推进分布式系统中的可持续计算解决方案.
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