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Big Data Analytics for 6G-Enabled Massive Internet of Things
IEEE Internet of Things Journal ( IF 8.2 ) Pub Date : 2-7-2021 , DOI: 10.1109/jiot.2021.3056128
Zhihan Lv , Ranran Lou , Jinhua Li , Amit Kumar Singh , Houbing Song

The purposes are to enable large-scale Internet of Things (IoT) devices to analyze data more effectively and provide high-efficiency, low-energy, and wide-coverage technical services for terminals. The channel model and energy loss model analyze the devices' access performance, data transmission path delay, energy consumption in the IoT, and large-scale devices' access in the cellular narrowband IoT (NB-IoT) based on big data analysis technology are also discussed. The results show that in the access success rate analysis, the access success rate is the highest with an access time ( T) of 5 s and a preamble resource number ( K) of 25. The restriction factor is inversely proportional to the access success rate. In the node utilization analysis, different transmission node priorities result in different node utilization, and priority 2's node utilization is better than that of priority 1. Moreover, local data makes data analysis and transmission faster. The search time is prolonged, and the corresponding energy consumption is also higher without local data. In the energy consumption analysis, with the 6-generation (6G) technology, different interference thresholds lead to the different energy efficiency of data transmission. The larger the interference threshold, the higher the energy efficiency. Therefore, the 6G-based big data analysis technology can significantly improve large-scale IoT devices' access success rate and enable the system to meet the requirements of low energy consumption and high access success rate, significant for research on more devices' access data analysis.

中文翻译:


面向 6G 大规模物联网的大数据分析



目的是让大规模物联网设备能够更有效地分析数据,为终端提供高效、低能耗、广覆盖的技术服务。信道模型和能量损耗模型分析了物联网中设备的接入性能、数据传输路径时延、能耗,以及基于大数据分析技术的蜂窝窄带物联网(NB-IoT)中大规模设备的接入。讨论过。结果表明,接入成功率分析中,接入时间(T)为5 s、前导码资源数量(K)为25时,接入成功率最高。限制因子与接入成功率成反比。 。在节点利用率分析中,不同的传输节点优先级导致节点利用率不同,优先级2的节点利用率优于优先级1。而且本地数据使得数据分析和传输更快。在没有本地数据的情况下,搜索时间延长,相应的能耗也较高。在能耗分析中,随着第六代(6G)技术的发展,不同的干扰阈值导致数据传输的能量效率不同。干扰阈值越大,能量效率越高。因此,基于6G的大数据分析技术可以显着提高大规模物联网设备的接入成功率,使系统满足低能耗、高接入成功率的要求,对于研究更多设备的接入数据分析具有重要意义。
更新日期:2024-08-22
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