A group mobility model for ad hoc wireless networks
MSWiM '99 Proceedings of the 2nd ACM international workshop on Modeling, analysis and simulation of wireless and mobile systems
Stability-based validation of clustering solutions
Neural Computation
A structured group mobility model for the simulation of mobile ad hoc networks
Proceedings of the second international workshop on Mobility management & wireless access protocols
A sober look at clustering stability
COLT'06 Proceedings of the 19th annual conference on Learning Theory
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In a number of network scenarios (including military settings), mobile nodes are clustered into groups, with nodes within the same group exhibiting significant correlation in their movements. Mobility models for such networks should reflect this group structure. In this paper, we consider the problem of identifying the number of groups, and the membership of mobile nodes within groups, from a trace of mobile nodes. We present two clustering algorithms to determine the number of groups and their identities: k-means chain and spectral clustering. Different from traditional k-means clustering, k-means chain identifies the number of groups in a dynamic graph, using a chaining process to keep track of group trajectories over the entire trace. The second approach uses spectral clustering, which uses similarities between node pairs to cluster nodes into groups. We show that the number of groups and node membership can be accurately extracted from traces, particularly when the number of groups is small.