Numerical recipes in C (2nd ed.): the art of scientific computing
Numerical recipes in C (2nd ed.): the art of scientific computing
Bayesian classification (AutoClass): theory and results
Advances in knowledge discovery and data mining
Analysis of a local-area wireless network
MobiCom '00 Proceedings of the 6th annual international conference on Mobile computing and networking
Analysis of a metropolitan-area wireless network
Wireless Networks - Selected Papers from Mobicom'99
Time Series Analysis, Forecasting and Control
Time Series Analysis, Forecasting and Control
Efficient Similarity Search In Sequence Databases
FODO '93 Proceedings of the 4th International Conference on Foundations of Data Organization and Algorithms
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
Model T: an empirical model for user registration patterns in a campus wireless LAN
Proceedings of the 11th annual international conference on Mobile computing and networking
Mining call and mobility data to improve paging efficiency in cellular networks
Proceedings of the 13th annual ACM international conference on Mobile computing and networking
Mining behavioral groups in large wireless LANs
Proceedings of the 13th annual ACM international conference on Mobile computing and networking
WCNC'09 Proceedings of the 2009 IEEE conference on Wireless Communications & Networking Conference
Max-contribution: on optimal resource allocation in delay tolerant networks
INFOCOM'10 Proceedings of the 29th conference on Information communications
Similarity analysis and modeling in mobile societies: the missing link
Proceedings of the 5th ACM workshop on Challenged networks
Predicting human behaviour from selected mobile phone data points
Proceedings of the 12th ACM international conference on Ubiquitous computing
Data-driven co-clustering model of internet usage in large mobile societies
Proceedings of the 13th ACM international conference on Modeling, analysis, and simulation of wireless and mobile systems
Spectral analysis of periodicity and regularity for mobile encounters in delay tolerant networks
ACM SIGMOBILE Mobile Computing and Communications Review
Groups and frequent visitors shaping the space dynamics
NEW2AN'11/ruSMART'11 Proceedings of the 11th international conference and 4th international conference on Smart spaces and next generation wired/wireless networking
Proceedings of the 14th ACM international conference on Modeling, analysis and simulation of wireless and mobile systems
Centrality prediction in dynamic human contact networks
Computer Networks: The International Journal of Computer and Telecommunications Networking
Gauging human mobility characteristics and its impact on mobile routing performance
International Journal of Sensor Networks
SLAW: self-similar least-action human walk
IEEE/ACM Transactions on Networking (TON)
Proceedings of the 2012 ACM Conference on Ubiquitous Computing
Are call detail records biased for sampling human mobility?
ACM SIGMOBILE Mobile Computing and Communications Review
Time-clustering-based place prediction for wireless subscribers
IEEE/ACM Transactions on Networking (TON)
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Understanding user mobility and its effect on access points (APs) is important in designing location-aware systems and wireless networks. Although various studies of wireless networks have provided useful insights, it is hard to apply them to other situations. Here we present a general methodology for extracting mobility information from wireless network traces, and for classifying mobile users and APs. We used the Fourier transform to reveal important periods and chose the two strongest periods to serve as parameters to a classification system based on Bayes' theory. Analysis of 1-month traces shows that while a daily pattern is common among both users and APs, a weekly pattern is common only for APs. Analysis of 1-year traces revealed that both user mobility and AP popularity depend on the academic calendar. By plotting the classes of APs on our campus map, we discovered that their periodic behavior depends on their proximity to other APs.