在低功率广域网 (LPWAN) 中,以自然为灵感的方法进行节能继电器选择
Anna Strzoda1, Krzysztof Grochla1
1Institute of Theoretical and Applied Informatics, Polish Academy of Science, Bałtycka 5, 44-100 Gliwice, Poland.
Sensors (Basel, Switzerland)
|June 19, 2024
概括
本研究介绍了一种以自然为灵感的算法,以提高低功率广域网 (LPWAN) 覆盖率. 节能继电器选择方法解决了盲点,并扩大了物联网 (IoT) 设备的网络范围.
科学领域:
- 无线通信网络是无线通信网络.
- 物联网 (IoT) 的物联网 (IoT) 的物联网.
- 算法设计的设计算法
背景情况:
- 低功率广域网 (LPWAN) 面临覆盖盲点,限制了它们的有效性.
- 扩展网络范围和保持能源效率是LPWAN的关键挑战,特别是电池驱动物联网设备.
研究的目的:
- 为基于LoRa的LPWANs提出一个创新的,节能的,以自然为灵感的中继选择算法.
- 解决LPWAN部署中信号范围差和覆盖盲点的挑战.
- 提高网络能源效率,扩大无线电信号覆盖范围.
主要方法:
- 一个群体行为启发的方法被用于网络中中继本地化.
- 该算法考虑了LoRa特定的因素,如扩散因子和设备能源预算.
- 模拟实验在各种多网关网络拓中进行,涉及数千个设备.
主要成果:
- 拟议的算法有效地弥合了沟通差距,减少了覆盖盲点的影响.
- 它在防止继电器电池耗尽方面明显优于参考方法.
- 启发式方法证明了精确方法的两倍以上的速度,准确性损失微不足道 (<2%).
结论:
- 开发的算法为扩大LPWAN覆盖范围和提高能源效率提供了有效的解决方案.
- 它对于在具有挑战性的环境中为电池驱动的物联网设备实现可靠通信至关重要.
- 这种以自然为灵感的方法为大规模LPWAN中中继选择提供了可扩展和高效的方法.
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