On clusterings: Good, bad and spectral
Journal of the ACM (JACM)
A framework for community identification in dynamic social networks
Proceedings of the 13th ACM SIGKDD international conference on Knowledge discovery and data mining
Study of a bus-based disruption-tolerant network: mobility modeling and impact on routing
Proceedings of the 13th annual ACM international conference on Mobile computing and networking
A tutorial on spectral clustering
Statistics and Computing
A new mobility trace for realistic large-scale simulation of bus-based DTNs
Proceedings of the 5th ACM workshop on Challenged networks
BUBBLE Rap: Social-Based Forwarding in Delay-Tolerant Networks
IEEE Transactions on Mobile Computing
Highway Vehicular Delay Tolerant Networks: Information Propagation Speed Properties
IEEE Transactions on Information Theory
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Group structure detection presents an insight of the potential organization and functional properties, and benefit the data packet propagation in the various networks. This paper finds that the average number of neighbors of bus changes in a regular way across the running time. Thus we present a dynamic group-finding algorithm in public bus networks. The proposed algorithm includes two phases. To begin with, time is divided into some time interval based on the average number of neighbors of bus, and the time interval is extracted from the bus mobility trace. A group detection algorithm based on spectral clustering is then proposed for each time interval. The simulation results over a realistic bus trace data show that our dynamic group-finding algorithm well adapts to public bus networks.