基于尺度耦合特性分析的侦听网络流量扩张模型

发布时间：2018-08-01 15:05

【摘要】：在能量受限的侦听网络中,需要大量的信息交换,由于瓶颈节点的能量消耗无法满足侦听网络的流量需求,需要进行流量扩张模型构建。传统方法采用对偶子梯度法实现对侦听网络的流量扩张,方法只能考虑一种流量和节点的组合,适应性能不好。提出一种基于小波变换尺度耦合特性分析的侦听网络流量扩张模型,对侦听网络流量时间序列进行采集与分析,通过小波尺度耦合分析,对路由接收的调度任务指令数量做出有效预测,从而为调度模型的建立提供准确的数据基础。分析流量序列的瞬时频率线性变化规律,得到带宽频间谐振模型,通过小波尺度耦合特性约束,提高了流量的流通量,实现流量扩张。仿真结果表明,算法能有效提高侦听网络的数据流吞吐量,网络流量通道得到有效扩张,提高了侦听网络的安全性和通信效率,展示了较好的应用性能。
[Abstract]:A lot of information exchange is needed in the listening network with limited energy. Because the energy consumption of the bottleneck node can not meet the traffic demand of the listening network, it is necessary to construct the traffic expansion model. The traditional method uses dual subgradient method to realize the traffic expansion of the listening network. The method can only consider a combination of traffic and nodes, and the adaptive performance is not good. In this paper, a model of interception network traffic expansion based on wavelet transform scale coupling characteristic analysis is proposed. The time series of interception network traffic are collected and analyzed, and the wavelet scale coupling analysis is carried out. The number of scheduling task instructions received by routing is predicted effectively, which provides an accurate data basis for the establishment of scheduling model. By analyzing the linear variation law of instantaneous frequency of flow sequence, the resonant model with wide band frequency is obtained. By the constraint of wavelet scale coupling characteristic, the flow flux is improved and the flow expansion is realized. The simulation results show that the algorithm can effectively improve the throughput of the listening network data flow, the network traffic channel is effectively expanded, improve the security and communication efficiency of the listening network, and show a good performance.
【作者单位】：北京信息职业技术学院计算机工程系;
【分类号】：TP393.06

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