大数据通信中带宽优化技术仿真

发布时间：2018-05-23 12:08

本文选题：对等网 + 大数据通信　；参考：《计算机仿真》2014年09期

【摘要】：在宽带通信中,采用点对点信道传递技术,在传递大数据时,服务器只起到链接作用,无调控功能,造成信道很容易被海量数据占用,带宽占用率过高。传统的带宽调整策略都是在应用到对等网络中时,以服务器流量分流控制为基础,对等网络中,服务器不再起调控作用,因此,传统的带宽优化通信技术效果较差。提出基于均衡遗传算法的对等网P2P大数据通信中带宽减压方法。采用均衡技术,使种群中的所有个体均衡分布在指定空间中,针对所有的种群个体进行染色体编码,建立所有染色体构成的初始种群,对种群个体进行选择、交叉和变异运算,获取通信中带宽数据传输的合理调度方式,实现对等网P2P大数据通信中带宽减压。实验结果表明,利用改进算法能够在短时间内传递大量的通信数据,提高了带宽效率,满足了大数据通信的实际需求。
[Abstract]:In wideband communication, using point-to-point channel transmission technology, when transmitting big data, the server only plays the role of link, no control function, resulting in the channel is easily occupied by mass data, and the bandwidth utilization is too high. The traditional bandwidth adjustment strategy is based on server flow control when it is applied to peer-to-peer network. In peer-to-peer network, the server no longer plays a regulatory role, so the traditional bandwidth optimization communication technology is not effective. A bandwidth decompression method for peer-to-peer P2P big data communication based on balanced genetic algorithm is proposed. By using the equalization technique, all the individuals in the population are evenly distributed in the specified space, the chromosome coding is carried out for all the individuals of the population, the initial population of all the chromosomes is established, and the selection, crossover and variation operation of the population individuals are carried out. In order to achieve bandwidth decompression in peer-to-peer P2P big data communication, the reasonable scheduling mode of bandwidth data transmission is obtained. The experimental results show that the improved algorithm can transfer a large amount of communication data in a short time, improve the bandwidth efficiency, and meet the actual requirements of big data communication.
【作者单位】：电子科技大学计算机科学与工程学院;
【分类号】：TN919

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