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一种用于低功耗广域网(LPWAN)中节能中继选择的受自然启发的方法。

A Nature-Inspired Approach to Energy-Efficient Relay Selection in Low-Power Wide-Area Networks (LPWAN).

作者信息

Strzoda Anna, Grochla Krzysztof

机构信息

Institute of Theoretical and Applied Informatics, Polish Academy of Science, Bałtycka 5, 44-100 Gliwice, Poland.

出版信息

Sensors (Basel). 2024 May 23;24(11):3348. doi: 10.3390/s24113348.

Abstract

Despite the ability of Low-Power Wide-Area Networks to offer extended range, they encounter challenges with coverage blind spots in the network. This article proposes an innovative energy-efficient and nature-inspired relay selection algorithm for LoRa-based LPWAN networks, serving as a solution for challenges related to poor signal range in areas with limited coverage. A swarm behavior-inspired approach is utilized to select the relays' localization in the network, providing network energy efficiency and radio signal extension. These relays help to bridge communication gaps, significantly reducing the impact of coverage blind spots by forwarding signals from devices with poor direct connectivity with the gateway. The proposed algorithm considers critical factors for the LoRa standard, such as the Spreading Factor and device energy budget analysis. Simulation experiments validate the proposed scheme's effectiveness in terms of energy efficiency under diverse multi-gateway (up to six gateways) network topology scenarios involving thousands of devices (1000-1500). Specifically, it is verified that the proposed approach outperforms a reference method in preventing battery depletion of the relays, which is vital for battery-powered IoT devices. Furthermore, the proposed heuristic method achieves over twice the speed of the exact method for some large-scale problems, with a negligible accuracy loss of less than 2%.

摘要

尽管低功耗广域网能够提供更远的传输距离,但它们在网络覆盖盲区方面面临挑战。本文针对基于LoRa的低功耗广域网提出了一种创新的节能且受自然启发的中继选择算法,作为解决覆盖有限区域信号范围不佳相关挑战的方案。采用一种受群体行为启发的方法来选择网络中中继的定位,以提高网络能效并扩展无线电信号。这些中继有助于弥合通信差距,通过转发与网关直接连接性差的设备的信号,显著降低覆盖盲区的影响。所提出的算法考虑了LoRa标准的关键因素,如扩频因子和设备能量预算分析。仿真实验验证了所提方案在涉及数千个设备(1000 - 1500个)的多种多网关(多达六个网关)网络拓扑场景下在能效方面的有效性。具体而言,验证了所提方法在防止中继电池耗尽方面优于参考方法,这对于电池供电的物联网设备至关重要。此外,对于一些大规模问题,所提启发式方法的速度比精确方法快两倍以上,精度损失可忽略不计,小于2%。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/238c/11174430/9592f33e359a/sensors-24-03348-g001.jpg

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