Topological persistence and simplification
FOCS '00 Proceedings of the 41st Annual Symposium on Foundations of Computer Science
SCG '04 Proceedings of the twentieth annual symposium on Computational geometry
The changing usage of a mature campus-wide wireless network
Proceedings of the 10th annual international conference on Mobile computing and networking
Characterizing mobility and network usage in a corporate wireless local-area network
Proceedings of the 1st international conference on Mobile systems, applications and services
Access and mobility of wireless PDA users
ACM SIGMOBILE Mobile Computing and Communications Review
Pocket switched networks and human mobility in conference environments
Proceedings of the 2005 ACM SIGCOMM workshop on Delay-tolerant networking
Reality mining: sensing complex social systems
Personal and Ubiquitous Computing
Visualizing community detection in opportunistic networks
Proceedings of the second ACM workshop on Challenged networks
Crossing over the bounded domain: from exponential to power-law inter-meeting time in MANET
Proceedings of the 13th annual ACM international conference on Mobile computing and networking
Power law and exponential decay of inter contact times between mobile devices
Proceedings of the 13th annual ACM international conference on Mobile computing and networking
On the Local Behavior of Spaces of Natural Images
International Journal of Computer Vision
Topological estimation using witness complexes
SPBG'04 Proceedings of the First Eurographics conference on Point-Based Graphics
Fast track article: From encounters to plausible mobility
Pervasive and Mobile Computing
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In order to better understand human and animal mobility and its potential effects on Mobile Ad-Hoc networks and Delay-Tolerant Networks, many researchers have conducted experiments which collect encounter data. Most analyses of these data have focused on isolated statistical properties such as the distribution of node inter-encounter times and the degree distribution of the connectivity graph. On the other hand, new developments in computational topology, in particular persistent homology, have made it possible to compute topological invariants from noisy data. These homological methods provide a natural way to draw conclusions about global structure based on collections of local information. We use persistent homology techniques to show that in some cases encounter traces can be used to deduce information about the topology of the physical space the experiment was conducted in, and detect certain changes in the space. We also show that one can distinguish between simulated encounter traces generated on a bounded rectangular grid from traces generated on a grid with the opposite edges wrapped (a toroidal grid). Finally, we have found that nontrivial topological features also appear in real experimental encounter traces, and we speculate on types of node behavior that could produce these results. This demonstrates the ability of persistent homology to detect topological features in encounter data that could be diffcult to describe using traditional statistical and geometric methods.