不同流量密度和人参与程度下物联网流量特性分析研究

发布时间：2018-07-04 23:14

本文选题：物联网 + 流量特性　；参考：《西南交通大学》2017年硕士论文

【摘要】：大量测量数据表明传统的互联网流量具有自相似(或长相关性)特性,该特性对网络性能评价和业务建模技术产生了很大的影响。物联网具有不同于传统互联网的特点,包括低移动性、上行占优、没有人的参与等,因此物联网流量特性将会发生重大地变化。网络流量特性研究是网络规划设计和性能评估的基础,对了解网络的运行规律、保证网络安全具有非常重要的作用。本文在分析了物联网的发展、体系结构和应用模式的基础上,对四种典型的物联网业务进行了分析,包括远程医疗、智能农业、自动驾驶和自动售货,依据分析结果构建相应的物联网业务流量模型,根据业务流量模型产生仿真流量,分析了流量在不同时间尺度、不同流量密度和不同人参与程度下的Hurst参数和方差特性。结果表明网络数据流量在不同情况下具有不同的流量特性。同种业务在不同流量密度下,有的自相似特性随着流量密度的增加而增加,有的比较稳定。同一种业务产生的流量,有的时间尺度上具有自相似特性,有的时间尺度上没有。然后分析了具有不同特性的流量聚合之后流量的特性,发现没有自相似特性的流量聚合之后依然没有自相似特性,具有自相似特性的流量聚合以后仍然具有自相似特性,当没有自相似特性的流量和具有自相似特性的流量聚合之后,聚合流量的特性和组成聚合流量的各类业务的Hurst参数和方差参数有关。接着分析了在不同方差和Hurst参数情况下聚合流量的特性,发现流量方差对聚合流量有着很大的影响。最后通过OPNET仿真,分析了网络流量参数对网络时延特性的影响,发现网络流量的方差和Hurst参数对网络性能都有很大的影响。
[Abstract]:A large number of measured data show that the traditional Internet traffic has self-similar (or long correlation) characteristics, which has a great impact on network performance evaluation and business modeling technology. The Internet of things is different from the traditional Internet of things, including low mobility, uplink dominance, no participation and so on, so the characteristics of Internet of things traffic will change greatly. The study of network traffic characteristics is the basis of network planning, design and performance evaluation, which plays an important role in understanding the operation rules of the network and ensuring the network security. Based on the analysis of the development, architecture and application mode of the Internet of things, this paper analyzes four typical Internet of things businesses, including telemedicine, intelligent agriculture, self-driving and self-selling. According to the analysis results, the corresponding traffic model of the Internet of things is constructed. According to the traffic model, the Hurst parameters and variance characteristics of the traffic are analyzed under different time scales, different traffic density and different degree of participation. The results show that network data traffic has different traffic characteristics under different conditions. Under different traffic density, some self-similar characteristics of the same service increase with the increase of traffic density, and some are more stable. The traffic generated by the same service is self-similar in time scale and not in time scale. Then, the characteristics of traffic after flow aggregation with different characteristics are analyzed. It is found that the flow aggregation without self-similarity still has no self-similarity, and the flow aggregation with self-similarity still has self-similarity. When traffic without self-similarity and traffic with self-similarity are aggregated, the characteristics of aggregate traffic are related to Hurst parameters and variance parameters of various services that make up aggregate traffic. Then, the characteristics of aggregate flow under different variance and Hurst parameters are analyzed, and it is found that traffic variance has great influence on aggregate flow. Finally, through OPNET simulation, the influence of network traffic parameters on network delay characteristics is analyzed. It is found that both network traffic variance and Hurst parameters have great influence on network performance.
【学位授予单位】：西南交通大学
【学位级别】：硕士
【学位授予年份】：2017
【分类号】：TN929.5;TP393.06;TP391.44

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