自动气象站网络中蜂窝上行链路鲁棒性的基准测试

Emmanuel Kondela, A. Nungu, J. W. Matiko, J. S. Otim, B. Pehrson
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引用次数: 1

摘要

我们提出了在自动气象站(AWS)测试平台中对蜂窝上行链路的鲁棒性进行基准测试的问题。基于这个问题,我们进行了一个小规模的鲁棒性测量研究,其中AWS配备了四(4)个蜂窝调制解调器用于天气数据传输。上行链路的有效性具有挑战性,因为存在重叠的时空因素,例如导致多路径效应、干扰、网络负载或其他原因的良好反射器的存在。我们认为,有一个强烈的需要独立评估他们的稳健性,执行端到端网络测量。然而,从一个特定的测量到对整个网络的评估仍然很困难。我们广泛测量无线电信号强度(RSSI)的可变性,作为蜂窝调制解调器上的链路度量。RSSI是重要的链路指标之一,可以确定接收到的RF信号的鲁棒性,并探索它们在特定位置和瞬间如何彼此不同。我们还应用统计分析,通过考虑鲁棒性来量化稳定性水平,参考短期变化,并确定与弱链路相比良好的上行链路。结果表明,蜂窝上行链路的鲁棒性存在一段不可预测的时间,并且低于人们的期望。超过50%的上行链路是间歇性的。因此,我们计划通过探索RSSI阈值来扩展我们的工作,以开发一个支持决定链接是否间歇的分类方案。这将有助于规范稳定性水平,为天气数据网络中的鲁棒路由协议设计RSSI估计度量。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Benchmarking the Robustness of Cellular Up-Links in Automatic Weather Station Networks
We present a problem for benchmarking the robustness of cellular up-links, in an automatic weather station (AWS) testbed. Based on the problem, we conduct a small-scale measurement study of robustness, where the AWS is equipped with four (4) cellular modems for weather data delivery. The effectiveness of up-links is challenging because of overlapping spatial-temporal factors such as the presence of good reflectors that lead to multi-path effects, interference, network load or other reasons. We argue that, there is a strong need for independent assessments of their robustness, to perform end-to-end network measurement. However, it is yet difficult to go from a particular measurement to an assessment of the entire network. We extensively measure the variability of Radio Signal Strength (RSSI) as link metric on the cellular modems. The RSSI is one of the important link metrics that can determine the robustness of received RF signals, and explore how they differed from one another at a particular location and instant time. We also apply the statistical analysis that quantifies the level of stability by considering the robustness, referring short-term variation, and determines good up-link in comparison to weak one. The results show that the robustness of cellular up-links exists for an unpredictable period of time and lower than one could hope. More than 50% of up-links are intermittent. Therefore, we plan to extend our work by exploring RSSI thresholds, to develop a classification scheme supporting a decision whether a link is either intermittent or not. This will help in normalizing the level of stability, to design the RSSI estimation metric for the robust routing protocol in weather data networks.
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