摘要
优化电力通信网络敏感信息传输节点选取过程,可避免链路拥挤,高消耗的传输能量导致簇首分布不合理的问题。因此,为了提高敏感信息传输安全性和网络覆盖率,设计电力通信网络敏感信息传输路由安全优化方案。结合PageRank算法迭代更新连接节点,构建路由连接函数,综合考虑节点负荷容量和等级选取节点。构建路由安全优化协议整体框架,依据链路ETX值改善电力通信网络中能量损耗。计算目标节点分布概率密度,设计路由优化数据分发机制,实现敏感信息传输路由安全优化。由实验结果可知,所设计方法簇1、2、3、4的簇首中心坐标分别为(-1,2)、(1,1.8)、(0.95,-2.2)、(-1,-2),与实际簇首所在中心一致;最高网络覆盖率为96%,有效提高了网络连接安全性。
Optimizing the selection process of sensitive information transmission nodes in power commun-ication networks can avoid link congestion,high consumption of transmission energy,and unreasonable distribution of cluster heads.Therefore,in order to improve the security and network coverage of sensitive information transmission,a security optimization scheme for sensitive information transmission routing in power communication networks is designed.Combining the PageRank algorithm to iteratively update connection nodes,construct a routing connection function,and comprehensively consider node load capacity and level to select nodes.Build an overall framework for routing security optimization protocol,and improve energy loss in power communication networks based on link ETX values.Calculate the probability density of target node distribution,design a routing optimization data distribution mechanism,and achieve secure optimization of sensitive information transmission routes.From the experimental results,it can be seen that the center coordinates of cluster heads for the designed method clusters 1,2,3,and 4 are(-1,2),(1,1.8),(0.95,-2.2),and(-1,-2),respectively,which are consistent with the actual center where the cluster heads are located;The highest network coverage rate is 96%,effectively improving network connection security.
作者
杨波
YANG Bo(College of Information Science and Engineering,Northeastern University,Shenyang 110819,China)
出处
《电子设计工程》
2024年第24期32-35,41,共5页
Electronic Design Engineering
基金
国家自然科学基金联合基金(U22B20115)。
关键词
电力通信网络
敏感信息传输
路由安全优化
分布概率密度
PAGERANK算法
power communication network
sensitive information transmission
routing security optim-ization
distribution probability density
PageRank algorithm