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Big Data Analysis of Internet of Things System
ACM Transactions on Internet Technology ( IF 5.3 ) Pub Date : 2020-07-07 , DOI: 10.1145/3389250
Zhihan Lv 1 , Amit Kumar Singh 2
Affiliation  

The study aims at exploring the Internet of things (IoT) system from the perspective of data and further improving the performance of the IoT system. The IoT data energy collection and information transmission system model is constructed by combining IoT and wireless relay cooperative transmission technology. Moreover, the energy efficiency, outage probability (OP), and accuracy of the model are evaluated by simulation experiments. The results show that, in the energy efficiency analysis, with the increase of power split factor ρ, the information transmission ability of the system increases. Whereas, the energy collection ability decreases, so the energy efficiency is reduced. Thus, choosing a more suitable power split factor for the energy efficiency of IoT is important. By analyzing OP and bit error rate (BER), as the values of m (Nakagami, the fading index of the fading distribution) and multi-hop paths increase, the OP and BER are reduced while the system performance is increased. Therefore, this article uses wireless relay cooperative transmission technology to integrate big data analysis into the IoT system. Finally, by adding multi-hop path and other methods to reduce the OP and BER of system, the system performance is improved. It provides experimental basis for the development of IoT systems.

中文翻译:

物联网系统大数据分析

该研究旨在从数据的角度探索物联网(IoT)系统,进一步提高物联网系统的性能。结合物联网和无线中继协同传输技术构建物联网数据能量采集与信息传输系统模型。此外,通过仿真实验评估了模型的能效、停电概率(OP)和准确性。结果表明,在能效分析中,随着功率分配因子ρ的增大,系统的信息传输能力增强。然而,能量收集能力降低,因此能量效率降低。因此,为物联网的能源效率选择更合适的功率分配因子非常重要。通过分析 OP 和误码率 (BER),作为(Nakagami,衰落分布的衰落指数)和多跳路径增加,OP和BER降低,同时系统性能提高。因此,本文采用无线中继协同传输技术,将大数据分析融入物联网系统。最后,通过增加多跳路径等方法降低系统的OP和BER,提高系统性能。为物联网系统的开发提供实验依据。
更新日期:2020-07-07
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