自然启发物联网网络的优化,用于耐延迟和节能应用
Gagandeep Kaur1, Vipin Balyan2, Sindhu Hak Gupta1
1Department of Electronics and Communication Engineering, Amity University, Sector-125, Noida, India.
Scientific reports
|March 23, 2025
概括
本研究为LoRaWAN网络引入了一种新的低使用周期MAC算法,通过使用黄金比率方法来优化性能. 拟议的方法显著降低了延迟和功耗,同时延长了网络寿命.
科学领域:
- 物联网 (IoT) 的物联网 (IoT) 的物联网.
- 无线通信网络 无线通信网络
- 网络协议 网络协议
背景情况:
- 洛拉万是物联网应用程序的流行的开放标准,提供低功耗,长距离和可扩展性.
- 然而,LoRaWAN的工作周期的限制和设备密度的增加降低了网络性能,阻碍了低延迟和长寿命的应用程序.
- 现有的方法难以平衡网络效率与设备限制.
研究的目的:
- 提出一种以自然为灵感的MAC算法,使用黄金比率 (GR) 方法优化LoRaWAN工作周期.
- 为需要低延迟和延长运行寿命的物联网应用程序增强网络性能.
- 验证拟议的算法的有效性与现有的方法和PSO算法相比.
主要方法:
- 开发一种新的低功率周期MAC算法,采用黄金比 (GR) 概念.
- 在LoRaWAN框架内优化工作周期.
- 使用粒子集群优化 (PSO) 算法和DC约束方法进行比较性能分析.
主要成果:
- 拟议的基于GR的算法显著降低了26%的网络延迟.
- 与直流约束方法相比,功耗减少了12%.
- 通过优化工作周期管理,网络寿命延长了14%.
结论:
- 拟议的基于黄金比的MAC算法有效地优化LoRaWAN工作周期,以提高网络性能.
- 这种方法为需要低延迟和延长网络寿命的物联网部署提供了可行的解决方案.
- 在关键指标上,GR算法在PSO和DC约束方法上表现出优越的性能.
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