摘要
通过互联网结构特性分析为互联网再设计、网络性能提升提供相应的指导与基础.首先使用粗粒度重整化方法对互联网IPv4和IPv6路由级拓扑进行处理,得出多重参数的变化特性;其次探索互联网度分布的分形特征;最后通过对CAIDA数据源的数据分析,研究了IP级数据在时间演化上的分形特征.结果表明:k核取值不高的网络具有分形自相似特征;高度值节点之间的连接随着时间维度的发展不断下降.相关的结论能够对后续的互联网结构特性研究起到一定的指导作用.
A guidance and basis can be provided for Internet＇ s redesign and performance improvement by analyzing the Internet＇ s structural characteristics. Firstly, variation characteristics of network parameter could be got by using coarsness renormalization to process IPv4 level and IPv6 level＇ s topology in Internet. Secondly, fractal feature of degree＇ s distribution in Internet was explored. Finally, the fractal feature of IP level data in time evolution dimensionality was researched by analyzing the data from CAIDA data source. The result showed that, the network was of fractal similar feature while the value of the network＇ s k was low, and the connections among nodes with high degree went down as the development of time dimension. The relevant conclusions could be used to guide the subsequent research in Internet＇ s structural characteristics.
出处
《东北大学学报（自然科学版）》
EI
CAS
CSCD
北大核心
2014年第1期43-46,55,共5页
Journal of Northeastern University(Natural Science)
基金
辽宁省教育厅科研一般项目(L2012088)
国家自然科学基金资助项目(60972022)
关键词
复杂网络
分形
度
重整化算法
IPV6
complex network
fractal
degree
renormalization algorithm
IPv6
