一种新型直联小世界网络模型

现有计算机网络存在一定程度冗余和效率低等问题,提出一种新的直联小世界(DSW)网络模型以优化网络.首先将节点构成正则网络,然后取任意节点重画,通过迭代生成DSW网络.在该模型下,平均距离和聚集系数与原网络相同,但是网络的跳数等性能有所改变.实验证明,DSW网络的度数、平均度中心性以及平均最近距离中心性均低于原有小世界(SW)网络.表明DSW网络两节点的紧密程度高于SW网络.该模型不仅可以有效应用于社区信息的传播,还可以用于流行病传播的研究.

A novel Direct Small World network model

There is a certain degree of redundancy and low efficiency of existing computer networks.This paper presents a novel Direct Small World network model in order to optimize networks.In this model,several nodes construct a regular network.Then,randomly choose and replot some nodes to generate Direct Small World network iteratively.There is no change in average distance and clustering coefficient.However,the network performance,such as hops,is improved.The experiments prove that compared to traditional small world network,the degree,average of degree centrality and average of closeness centrality are lower in Direct Small World network.This illustrates that the nodes in Direct Small World networks are closer than Watts-Strogatz small world network model.The Direct Small World can be used not only in the communication of the community information,but also in the research of epidemics.