Web网络下的异常路由数据监测技术研究
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摘要
在Web网络环境下,路由器应用过程中利用信道传输介质数据会出现异常干扰数据,而传统路由数据监测技术很难准确辨别异常数据,并且存在不能承接Web网络的缺陷。针对上述问题,提出Web网络下的异常路由数据监测技术。对监控总框架进行优化设计,增设Web网络承接模块,导入多层次监测机制,通过Contra variant算法实现异常数据监测。设置仿真实验,实验结果表明,提出的数据监测技术能够有效地监控路由异常数据。
In the Web network environment,abnormal interference data exists when using the channel to transmit medium data during the router application process. It is difficult for the traditional routing data monitoring technology to accurately identify the abnormal data,and the defects of Web network cannot be overcome. In view of the above problems,the abnormal routing data monitoring technology in the Web network environment is proposed. The abnormal data monitoring is implemented with the Contra variant algorithm while optimizing the design of overall monitoring framework,adding the Web network support module,introducing the multi-level monitoring mechanism. The simulation experiment was carried out. The experimental results show that the proposed data monitoring technology can effectively monitor the abnormal routing data.
In the Web network environment,abnormal interference data exists when using the channel to transmit medium data during the router application process. It is difficult for the traditional routing data monitoring technology to accurately identify the abnormal data,and the defects of Web network cannot be overcome. In view of the above problems,the abnormal routing data monitoring technology in the Web network environment is proposed. The abnormal data monitoring is implemented with the Contra variant algorithm while optimizing the design of overall monitoring framework,adding the Web network support module,introducing the multi-level monitoring mechanism. The simulation experiment was carried out. The experimental results show that the proposed data monitoring technology can effectively monitor the abnormal routing data.
引文
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[3]姚海容.路由交换数据在线时间复杂度预测链路漏洞检测[J].科技通报,2015,31(9):212-219.YAO Hairong.Routing exchange data online time complexity forecasting link leak detection[J].Bulletin of science and technology,2015,31(9):212-219.
[4]杨静.大型云计算信息系统的异常数据检测模型仿真[J].计算机仿真,2015,32(11):378-381.YANG Jing.Simulation of Abnormal data detection model for large scale cloud computing information system[J].Computer simulation,2015,32(11):378-381.
[5]王乐,王芳.数据库异常数据的检测仿真研究[J].计算机仿真,2016,33(1):430-433.WANG Le,WANG Fang.Simulation of database with data mining[J].Computer simulation,2016,33(1):430-433.
[6]刘丰华.基于传感器网络的船舱环境监视系统[J].舰船科学技术,2015,37(3):214-217.LIU Fenghua.A novel ship cabin monitoring system based on wireless sensor network[J].Ship science and technology,2015,37(3):214-217.
[7]王娜,杜学绘,王文娟,等.边界网关协议安全研究综述[J].计算机学报,2017,40(7):1626-1648.WANG Na,DU Xuehui,WANG Wenjuan,et al.A survey of the border gateway protocol security[J].Chinese journal of computers,2017,40(7):1626-1648.
[8]高彩芳,冯振乾,虞万荣,等.适用于空间网络的通用路由协议设计与实现[J].小型微型计算机系统,2015,36(10):2270-2274.GAO Caifang,FENG Zhenqian,YU Wanrong,et al.Design and implementation of a general routing protocol for space network[J].Journal of Chinese computer systems,2015,36(10):2270-2274.
[9]良梓,任哲坡,吴晓军.DTN中基于时间因素的拥塞感知路由算法[J].计算机工程与应用,2015,51(5):97-101.LIANG Zi,REN Zhepo,WU Xiaojun.Congestion-aware routing algorithm based on time factor in DTN[J].Computer engineering and applications,2015,51(5):97-101.
[10]邓燕,张新有,邢焕来.一种基于传输容量控制的DTN动态分段编码路由算法[J].计算机应用研究,2017,34(9):2753-2757.DENG Yan,ZHANG Xinyou,XING Huanlai.Routing algorithm for DTN based on dynamic segmented network coding and transmission capacity control[J].Application research of computers,2017,34(9):2753-2757.