Characterizing user behavior and network performance in a public wireless LAN
SIGMETRICS '02 Proceedings of the 2002 ACM SIGMETRICS international conference on Measurement and modeling of computer systems
Maximizing the spread of influence through a social network
Proceedings of the ninth ACM SIGKDD international conference on Knowledge discovery and data mining
The link prediction problem for social networks
CIKM '03 Proceedings of the twelfth international conference on Information and knowledge management
Probabilistic routing in intermittently connected networks
ACM SIGMOBILE Mobile Computing and Communications Review
The changing usage of a mature campus-wide wireless network
Proceedings of the 10th annual international conference on Mobile computing and networking
User Mobility for Opportunistic Ad-Hoc Networking
WMCSA '04 Proceedings of the Sixth IEEE Workshop on Mobile Computing Systems and Applications
Characterizing mobility and network usage in a corporate wireless local-area network
Proceedings of the 1st international conference on Mobile systems, applications and services
IEEE Transactions on Knowledge and Data Engineering
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
ACM SIGKDD Explorations Newsletter
Reality mining: sensing complex social systems
Personal and Ubiquitous Computing
Impact of Human Mobility on Opportunistic Forwarding Algorithms
IEEE Transactions on Mobile Computing
Periodic properties of user mobility and access-point popularity
Personal and Ubiquitous Computing
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
Social network analysis for routing in disconnected delay-tolerant MANETs
Proceedings of the 8th ACM international symposium on Mobile ad hoc networking and computing
Bubble rap: social-based forwarding in delay tolerant networks
Proceedings of the 9th ACM international symposium on Mobile ad hoc networking and computing
Media sharing based on colocation prediction in urban transport
Proceedings of the 14th ACM international conference on Mobile computing and networking
Description and simulation of dynamic mobility networks
Computer Networks: The International Journal of Computer and Telecommunications Networking
Cellular Census: Explorations in Urban Data Collection
IEEE Pervasive Computing
Temporal distance metrics for social network analysis
Proceedings of the 2nd ACM workshop on Online social networks
Role of weak ties in link prediction of complex networks
Proceedings of the 1st ACM international workshop on Complex networks meet information & knowledge management
Modeling spatial and temporal dependencies of user mobility in wireless mobile networks
IEEE/ACM Transactions on Networking (TON)
On Nonstationarity of Human Contact Networks
ICDCSW '10 Proceedings of the 2010 IEEE 30th International Conference on Distributed Computing Systems Workshops
Exploiting temporal complex network metrics in mobile malware containment
WOWMOM '11 Proceedings of the 2011 IEEE International Symposium on a World of Wireless, Mobile and Multimedia Networks
Editorial: Complex dynamic networks: Tools and methods
Computer Networks: The International Journal of Computer and Telecommunications Networking
Distributed assessment of the closeness centrality ranking in complex networks
Proceedings of the Fourth Annual Workshop on Simplifying Complex Networks for Practitioners
Dynamic targeting in an online social medium
SocInfo'12 Proceedings of the 4th international conference on Social Informatics
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Real technological, social and biological networks evolve over time. Predicting their future topology has applications to epidemiology, targeted marketing, network reliability and routing in ad hoc and peer-to-peer networks. The key problem for such applications is usually to identify the nodes that will be in more important positions in the future. Previous researchers had used ad hoc prediction functions. In this paper, we evaluate ways of predicting a node's future importance under three important metrics, namely degree, closeness centrality, and betweenness centrality, using empirical data on human contact networks collected using mobile devices. We find that node importance is highly predictable due to both periodic and legacy effects of human social behaviour, and we design reasonable prediction functions. However human behaviour is not the same in all circumstances: the centrality of students at Cambridge is best correlated both daily and hourly, no doubt due to hourly lecture schedules, while academics at conferences exhibit rather flat closeness centrality, no doubt because conference attendees are generally trying to speak to new people at each break. This highlights the utility of having a number of different metrics for centrality in dynamic networks, so as to identify typical patterns and predict behaviour. We show that the best-performing prediction functions are 25% more accurate on average than simply using the previous centrality value. These prediction functions can be efficiently computed in linear time, and are thus practical for processing dynamic networks in real-time.