Campus-oriented stepwise-optimal hierarchical clustering algorithm of IP address
面向校园网的IP地址逐步优化层次聚类算法

The cluster analysis of IP addresses can reveal useful knowledge for profiling of traffic flows and user behavior. However, the popular clustering algorithms were not applicable directly to IP addresses of the campus network traffic flows. The clusters which were generated by generic algorithms were inconsistent with the IP addresses partition and difficult to interpret. To overcome the shortcoming of the current algorithms which neglect the characteristics of IP addresses, a new algorithm which could effectively improve IP addresses clustering was proposed. Firstly, the initial clusters were got by adopting the longest prefix algorithm and the nearest neighbor clustering algorithm. Then the thought of stepwise-optimal hierarchical clustering was applied to merge the nearest groups of initial clusters. The similarity between initial clusters was determined by the longest prefix of IP addresses contained in these clusters. Finally, the algorithm automatically and meaningfully yielded clusters which were in accord with the characteristics of IP addresses on traffic flows. The results show that the proposed algorithm is accurate and effective in clustering IP addresses and robust to the input sequence of data.