Golay code clustering for mobility behavior similarity classification in pocket switched networks

Authors:
Hongjun Yu;Simon Berkovich;Tao Jing;Dechang Chen
Affiliations:
Department of Computer Science, The George Washington University, Washington, DC;Department of Computer Science, The George Washington University, Washington, DC;School of Electronics and Information Engineering, Beijing JiaoTong University, Beijing, P.R. China;Department of Preventive Medicine and Biometrics, Uniformed Services University of the Health Sciences, Bethesda, MD
Venue:
WASA'11 Proceedings of the 6th international conference on Wireless algorithms, systems, and applications
Year:
2011

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Abstract

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 codewords 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.