Krapivsky P L, Redner S
Center for Polymer Studies and Department of Physics, Boston University, Boston, MA 02215, USA.
Phys Rev E Stat Nonlin Soft Matter Phys. 2005 Mar;71(3 Pt 2A):036118. doi: 10.1103/PhysRevE.71.036118. Epub 2005 Mar 17.
We introduce a growing network model in which a new node attaches to a randomly selected node, as well as to all ancestors of the target node. This mechanism produces a sparse, ultrasmall network where the average node degree grows logarithmically with network size while the network diameter equals 2. We determine basic geometrical network properties, such as the size dependence of the number of links and the in- and out-degree distributions. We also compare our predictions with real networks where the node degree also grows slowly with time--the Internet and the citation network of all Physical Review papers.
我们引入了一种增长网络模型,其中新节点不仅连接到随机选择的节点,还连接到目标节点的所有祖先节点。这种机制产生了一个稀疏的超小网络,其中平均节点度随网络规模呈对数增长,而网络直径等于2。我们确定了基本的几何网络属性,例如链接数量的规模依赖性以及入度和出度分布。我们还将我们的预测与节点度也随时间缓慢增长的真实网络——互联网和所有《物理评论》论文的引用网络进行了比较。