关于MEC计算卸载战略的研究,以共同优化延迟和能源消耗
Mingchang Ni1, Guo Zhang1, Qi Yang2
1Faculty of Information Engineering and Automation, Kunming University of Science and Technology, Kunming 650504, China.
Mathematical biosciences and engineering : MBE
|August 23, 2024
概括
这项研究介绍了用于移动边缘计算卸载决策的增强的正弦-弦算法 (SCAGA). 该SCAGA方案有效地减少了系统延迟,并优化了边缘端架构中的卸载实用程序.
科学领域:
- 计算机科学 计算机科学
- 人工智能的人工智能
- 网络工程 网络工程
背景情况:
- 计算卸载是移动边缘计算 (MEC) 的关键.
- 卸载决策严重影响系统延迟和能源消耗.
- 现有策略需要优化,以实现高效的边缘端架构.
研究的目的:
- 为边缘MEC架构提出一个优化的计算卸载方案.
- 引入一个增强的正弦-弦优化算法 (SCAGA),以改善卸载决策.
- 评估基于SCAGA的方案在减少延迟和增强卸载实用性的表现.
主要方法:
- 开发了边缘计算的计算资源和成本模型.
- 引入了SCAGA,整合了Levy飞行,轮盘选择和基因突变.
- 进行模拟实验,以评估SCAGA卸载方案.
主要成果:
- 基于SCAGA的卸载方案显著减少了系统延迟.
- 通过使用拟议的SCAGA实现了优化卸载效用.
- 对比分析显示,SCAGA在延迟,能源消耗和效用方面表现优于其他方案.
结论:
- 该SCAGA方案提供了一个有效的解决方案,用于边缘端MEC的计算卸载.
- 在平衡延迟,能量和效用方面,SCAGA表现出卓越的性能.
- 这项研究有助于在移动边缘计算环境中高效的资源管理.
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