Golay Code Clustering for Mobility Behavior Similarity Classification in Pocket Switched Networks

In Pocket Switched Networks （PSN）, the similarity of mobility patterns of different human beings can be exploited to design routing protocols that have better packet delivery ratio and shorter end-to-end delay. However, current research lacks techniques to effectively quantify the similarity of human beings＇ mobility behaviors as they exhibit diversities in both the time and spatial domains. In this paper, we provide a mechanism to encode the human mobility patterns and propose a Golay code based clustering system to facilitate the identification of the set of codeword that incarnate similar mobility behaviors. We will apply this clustering based mobility behavior similarity classification method to design PSN routing protocols in our future research.