非结构化离散网络传输路径预测方法仿真

发布时间：2019-06-19 23:08

【摘要】：为了有效提升非结构化离散网络的传输质量,需要进行非结构化离散网络传输路径预测。但是采用当前方法进行非结构化离散网络传输路径预测时,忽略了网络传输信道和路径间的干扰影响,存在路径预测误差大的问题。为此,提出一种基于支持向量机回归的非结构化离散网络传输路径预测方法。方法先采用测量往返时延的基本思想进行非结构化离散网络传输路径时延测量,得到网络传输路径时延的抖动值,计算出网络传输路径的丢包率,获取发送端在网络传输路径上发送的最大数据量,在得到群数据包延迟序列后,对非结构化离散网络传输路径预测问题进行建模,结合支持向量机回归理论对模型进行求解,有效完成了对非结构化离散网络传输路径预测。仿真证明,所提方法能够有效提升非结构化离散网络传输路径预测精度,且预测效率较高。
[Abstract]:In order to effectively improve the transmission quality of unstructured discrete networks, it is necessary to predict the transmission paths of unstructured discrete networks. However, when the current method is used to predict the transmission path of unstructured discrete networks, the interference between network transmission channels and paths is ignored, and there is a problem of large path prediction error. In this paper, an unstructured discrete network transmission path prediction method based on support vector machine regression is proposed. Methods firstly, the basic idea of measuring round-trip delay is used to measure the transmission path delay of unstructured discrete networks, the buffeting value of network transmission path delay is obtained, the packet loss rate of network transmission path is calculated, and the maximum amount of data sent by the sender on the network transmission path is obtained. after the group packet delay sequence is obtained, the transmission path prediction problem of unstructured discrete network is modeled. Combined with support vector machine regression theory, the model is solved, and the transmission path prediction of unstructured discrete networks is completed effectively. Simulation results show that the proposed method can effectively improve the accuracy of transmission path prediction in unstructured discrete networks, and the prediction efficiency is high.
【作者单位】：西北政法大学商务安全研究所;
【分类号】：TP393.0

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