局域网应急通信堵塞强化预警算法设计  

Design of Enhanced Early Warning Algorithm for LAN Emergency Communication Congestion

作　　者：李杰[1] LI Jie(Jiujiang Vocational University,JiuJiang 332000,China)

机构地区：[1]九江职业大学,江西九江332000

出　　处：《信息工程大学学报》2022年第5期550-555,共6页Journal of Information Engineering University

基　　金：江西省教育厅科学技术研究资助项目(GJJ213908)。

摘　　要：为避免网络堵塞现象影响局域网通信安全,设计局域网应急通信堵塞强化预警算法。首先,基于物联网技术计算影响目标节点的关键锚节点位置数据,划分局域网内堵塞节点范围;其次,提取堵塞节点特征,采用匹配方法计算堵塞节点和正常节点之间的特征值差异;最后,将差异值作为量子遗传算法改进核向量机预警模型的输入项,模型运算后输出局域网应急通信堵塞强化预警结果。实验结果表明,该算法可成功检测出不同堵塞程度的异常节点,优化核心向量机的训练参数选取,提高堵塞节点预警性能。To avoid the impact of network congestion on the communication security of local area network, an enhanced early warning algorithm for local area network(LAN) emergency communication congestion is designed. Firstly, based on the Internet of Things technology, the location data of key anchor nodes that affect target nodes are calculated, and the range of blocked nodes in LAN is divided. Then, the features of blocked nodes are extracted, and the difference of feature values between blocked nodes and normal nodes is calculated by matching method. Finally, the difference value is used as the input of the improved kernel vector machine early warning model based on quantum genetic algorithm, and the early warning result of LAN emergency communication congestion is output after the model operation. Experimental results show that the algorithm can successfully detect abnormal nodes with different blocking degrees, optimize the selection of core vector machine training parameters, and improve the early warning performance of blocked nodes.

关 键 词：局域网 应急通信堵塞 强化预警 量子遗传算法 特征提取 核向量机 

分 类 号：TP393.1[自动化与计算机技术—计算机应用技术] TP309[自动化与计算机技术—计算机科学与技术]