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冲动流量对蜂物联网的影响网络性能指标网络性能指标

Tammam Zuhair Dawood^1,2, Mikhail Sergeevich Stepanov¹, Matvey Kudashkin¹

¹Faculty of Communication Networks and Systems, Moscow Technical University of Communications and Informatics, 8A, Aviamotornaya Str., 111024 Moscow, Russia.

Sensors (Basel, Switzerland)

|January 11, 2024

概括

这项研究模拟了长期进化 (LTE) 细胞性能,用于经历数据到达的窄带物联网 (NB-IoT) 设备. 这项研究评估了LTE单元如何有效地处理同时的NB-IoT请求.

科学领域:

电信工程电信工程电信工程
无线传感器网络无线传感器网络
物联网 (IoT) 的物联网 (IoT) 的物联网.

背景情况:

无线传感器网络和物联网 (IoT) 的普及导致了数据传输需求的增加.
物联网设备通常利用蜂基础设施,如长期进化 (LTE),将数据传输到处理中心.
从物联网设备同时到达的大量数据对网络性能和稳定性构成重大挑战.

研究的目的:

开发和分析一个数学模型来评估LTE电池服务于窄带物联网 (NB-IoT) 设备的有效性.
具体评估LTE电池性能,当NB-IoT请求到达爆发,而不是单独.
为大规模物联网部署提供关于优化蜂网络容量的见解.

主要方法:

讨论常见的物联网应用程序和NB-IoT技术的特点.
开发一个数学模型来模拟和评估在冲动NB-IoT请求模式下LTE电池的性能.
实现计算算法和数值评估来分析模型的预测.

主要成果:

该研究提供了LTE电池容量的定量评估,当处理爆发的NB-IoT流量时.
开发的模型展示了到达模式对网络资源利用和潜在拥堵的影响.
数字评估提供了对高需求场景下性能限制和潜在瓶的洞察力.

结论:

这项研究突出了专业模型的关键需求,以了解网络行为与爆发的物联网数据.
这些发现有助于设计和优化蜂网络,以提供高效的NB-IoT服务.
进一步的研究可以将该模型扩展到其他物联网通信协议和网络条件.

关键词:

在LPWAN中使用.这就是为什么LTE是LTE.这是一个NB-IoT.获得许可的频谱.数学建模的数学建模递归算法递归算法

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