大数据环境下网络数据传输及融合优化仿真

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英文篇名：Network Data Transmission and Fusion Optimization Simulation in Big Data Environment 作者：郭银芳 英文作者：GUO Yin-fang;Department of Computer Engineering Taiyuan University; 关键词：大数据环境 ; 网络数据 ; 数据传输 ; 数据融合 ; 压缩域 英文关键词：Big data environment;;Network data;;Data transmission;;Data fusion;;Compressed domain 中文刊名：JSJZ 英文刊名：Computer Simulation 机构：太原学院计算机工程系; 出版日期：2019-04-15 出版单位：计算机仿真 年：2019 期：v.36 语种：中文; 页：JSJZ201904026 页数：5 CN：04 ISSN：11-3724/TP 分类号：126-129+189

摘要

为了解决采用传统融合方法进行大规模网络数据传输时,存在数据传输量小、节点传输能耗大的问题,基于压缩感知理论,提出一种在压缩域直接进行数据融合的优化方法。通过构建网络数据传输模型分析数据节点能量消耗情况,计算网络数据传输最大吞吐量,获取网络数据传输节点的能量消耗值。同时根据节点能量消耗情况选取合适节点对网络数据进行参数设计,构建能耗控制参数;通过对目标网络进行配置生成多个簇结构,结合节点能耗控制参数提高网络数据压缩率,减少数据传输量及传输能耗。压缩后的数据在大数据环境下传输,并在不同簇首实现压缩域下的数据融合。实验结果表明,所提方法在提高压缩比的同时提高了压缩速度,并与其它数据传输优化方法相比,有效减少了数据传输量及传输能耗,实现了数据实时传输。
        Based on the compressed sensing theory,an optimization method for direct data fusion in compressed domain was put forward. By constructing the network data transmission model,the data node energy consumption was analyzed. Then,the maximum throughput of network data transmission was calculated to obtain the energy consumption value of network data transmission node. According to the energy consumption of node,appropriate nodes were selected to design the parameter of network data. Meanwhile,the energy consumption was constructed. Moreover,many cluster structures were generated by configuring target network. The network energy consumption control parameters were used to improve compression rate of network data and reduce the amount of data transmission and energy consumption. Finally,the compressed data was transmitted in big data environment,and the data fusion in compressed domain was achieved based on different cluster heads. Simulation results show that the proposed method improves the compression speed while improving the compression ratio. Compared with other methods of data transmission optimization,this method effectively reduces the amount of data transmission and transmission energy consumption. Thus,the real-time data transmission was achieved.

引文

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