In large-scale distributed network applications

nodes clustering is a useful way to construct an effective network infrastructure.The coordinates of network nodes can be get by the network coordinates system Vivaldi

then

network nodes can be clustered by the K-medoids algorithm according to their coordinates.But K-medoids is sensitive to the initial cluster centers and easy to get stuck at the local optimal solutions.In order to improve the performance of the K-medoids algorithm

the K-medoids based on immune clonal algorithm(KICA) is presented in this paper.Experimental results show KICA has good reliability and expansibility

and it is effective for clustering internet nodes.