Graph drawing by force-directed placement
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Mobility increases the capacity of ad hoc wireless networks
IEEE/ACM Transactions on Networking (TON)
Disconnected Graph Layout and the Polyomino Packing Approach
GD '01 Revised Papers from the 9th International Symposium on Graph Drawing
A delay-tolerant network architecture for challenged internets
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Reality mining: sensing complex social systems
Personal and Ubiquitous Computing
Low-cost communication for rural internet kiosks using mechanical backhaul
Proceedings of the 12th annual international conference on Mobile computing and networking
Wireless sensor network localization techniques
Computer Networks: The International Journal of Computer and Telecommunications Networking
Visualizing community detection in opportunistic networks
Proceedings of the second ACM workshop on Challenged networks
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
Monte Carlo localization for mobile wireless sensor networks
Ad Hoc Networks
IEEE Transactions on Visualization and Computer Graphics
Using persistent homology to recover spatial information from encounter traces
Proceedings of the 9th ACM international symposium on Mobile ad hoc networking and computing
Stationary Distributions for the Random Waypoint Mobility Model
IEEE Transactions on Mobile Computing
The ONE simulator for DTN protocol evaluation
Proceedings of the 2nd International Conference on Simulation Tools and Techniques
Towards distributed network classification for mobile ad hoc networks
Proceedings of the 4th Annual International Conference on Wireless Internet
Opportunistic forwarding in workplaces
Proceedings of the 2nd ACM workshop on Online social networks
Sampling urban mobility through on-line repositories of GPS tracks
Proceedings of the 1st ACM International Workshop on Hot Topics of Planet-Scale Mobility Measurements
Modeling spatial and temporal dependencies of user mobility in wireless mobile networks
IEEE/ACM Transactions on Networking (TON)
A prsimonious model of mobile partitioned networks with clustering
COMSNETS'09 Proceedings of the First international conference on COMmunication Systems And NETworks
Plausible mobility: inferring movement from contacts
MobiOpp '10 Proceedings of the Second International Workshop on Mobile Opportunistic Networking
Delay-tolerant networking: an approach to interplanetary Internet
IEEE Communications Magazine
MobiCom 2011 poster: contact rule-based decision for mobile social networking testbed
ACM SIGMOBILE Mobile Computing and Communications Review
Ego network models for Future Internet social networking environments
Computer Communications
Extrapolating sparse large-scale GPS traces for contact evaluation
Proceedings of the 5th ACM workshop on HotPlanet
Plausible mobility inference from wireless contacts using optimization
Proceedings of the 8th ACM MobiCom workshop on Challenged networks
Examining vicinity dynamics in opportunistic networks
Proceedings of the 8th ACM workshop on Performance monitoring and measurement of heterogeneous wireless and wired networks
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Inferring plausible node mobility based only on information from wireless contact traces is a difficult problem. Working with mobility information allows richer protocol simulations, particularly in dense networks, but requires complex set-ups to measure. On the other hand, contact information is easier to measure but only allows for simplistic simulation models. In a contact trace a lot of node movement information is irretrievably lost so the original positions and velocities are in general out of reach. In this paper, we propose a fast heuristic algorithm, inspired by dynamic force-based graph drawing, capable of inferring a plausible movement from any contact trace, and evaluate it on both synthetic and real-life contact traces. Our results reveal that (i) the quality of the inferred mobility is directly linked to the precision of the measured contact trace, and (ii) the simple addition of appropriate anticipation forces between nodes leads to an accurate inferred mobility.