Opportunistic content distribution in an urban setting
Proceedings of the 2006 SIGCOMM workshop on Challenged networks
Impact of Human Mobility on Opportunistic Forwarding Algorithms
IEEE Transactions on Mobile Computing
Temporal distance metrics for social network analysis
Proceedings of the 2nd ACM workshop on Online social networks
Characterising temporal distance and reachability in mobile and online social networks
ACM SIGCOMM Computer Communication Review
Networks: An Introduction
STEPS - an approach for human mobility modeling
NETWORKING'11 Proceedings of the 10th international IFIP TC 6 conference on Networking - Volume Part I
How disorder impacts routing in human-centric disruption tolerant networks
Proceedings of the 2013 ACM SIGCOMM workshop on Future human-centric multimedia networking
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The small-world phenomenon first introduced in the context of static graphs consists of graphs with high clustering coefficient and low shortest path length. This is an intrinsic property of many real complex static networks. Recent research has shown that this structure is also observable in dynamic networks but how it emerges remains an open problem. In this paper, we propose a model capable of capturing the small-world behavior observed in various real traces. We then study information diffusion in such small-world networks. Analytical and simulation results with epidemic model show that the small-world structure increases dramatically the information spreading speed in dynamic networks.