以往网络信息传播的研究多关注于节点的度等性质研究,然而节点的信息传播能力不仅与节点度有关,更与其邻居网络,即子网有关.为了对信息在网络上的传播进行有效控制,我们对局部网络拓扑结构进行研究.提出一种邻居度生成算法,对一个局部网络,通过分析每个节点的邻居度结构,可以有效地得到网络中每个节点的一阶邻居节点、二阶邻居节点、邻居度等节点属性信息,并依据这些信息来划分节点在网络中的重要性.仿真实验表明,邻居网络生成算法可行,可以快速计算出网络中各个节点的邻居度,并能够较好地将邻居节点进行邻居度划分.
Previous research focused on nodes of network information transmission properties such as degree. However, the node infor- marion transmission capacity is related not only with the node degrees, more with its neighbor network, namely the subnet. In order to effectively control the spread of information on the lnternet, we analysed the local topological structure in complex network. By analy- sis, we found a generation algorithms for the neighborhood-degree called "second_order neighborhood generate algorithm"(SNGenerate ), which can help us to get the detailed neighborhood information of each point. By this, we can easily differentiate the importance of nodes in the network. The simulation results show that it works well, and the algorithms can not only calculate the neighbor-degree of each node but also be able to control the network information dissemination effectively.