用边缘计算和低海拔平台站优化农业物联网 (IoT)
Deshan Yang1,2,3, Jingwen Wu2, Yixin He2
1School of Mechanical Engineering, Tianjin University, Tianjin 300072, China.
Sensors (Basel, Switzerland)
|November 9, 2024
概括
本研究介绍了一种使用低海拔平台站 (LAPS) 进行农业物联网 (IoT) 的新边缘计算架构. 拟议的系统大大减少了任务处理的延迟,以提高作物管理.
科学领域:
- 农业技术 农业技术
- 物联网 (IoT) 的物联网 (IoT) 的物联网.
- 边缘计算 边缘计算
背景情况:
- 低海拔平台站 (LAPS) 对于监测大型农业区至关重要.
- 将边缘计算与LAPS集成,可以实现实时数据处理,减少延迟.
- 当前的农业物联网系统面临着延迟和依赖远程云服务器的挑战.
研究的目的:
- 探索LAPS和边缘计算在农业物联网中的应用.
- 为高效的任务处理引入LAPS辅助的边缘计算架构.
- 尽量减少总任务处理延迟,同时考虑任务依赖性和能源消耗.
主要方法:
- 为农业物联网开发了一个LAPS辅助的边缘计算架构.
- 将任务分成相互依赖的子任务,用于分布式处理.
- 制定了一个任务处理延迟最小化问题,对依赖性,优先级和能量有限制.
- 利用定向非循环图来建模任务依赖关系.
- 设计了一个具有优先选择的启发式任务处理算法.
主要成果:
- 拟议的边缘计算方案在减少总任务处理延迟方面表现出卓越的性能.
- 该系统有效地管理相互依赖的子任务,并优先考虑关键操作.
- 数字结果证实了相对于最先进的和本地计算方法的显著改进.
结论:
- 在农业物联网应用中,LAPS辅助的边缘计算架构非常有效.
- 这种方法通过减少加工延迟,提高了作物管理的效率和精度.
- 开发的启发式算法为复杂约束下任务调度提供了最佳解决方案.
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