On power-law relationships of the Internet topology
Proceedings of the conference on Applications, technologies, architectures, and protocols for computer communication
Analysis of a campus-wide wireless network
Proceedings of the 8th annual international conference on Mobile computing and networking
Towards realistic mobility models for mobile ad hoc networks
Proceedings of the 9th annual international conference on Mobile computing and networking
Modeling users' mobility among WiFi access points
WiTMeMo '05 Papers presented at the 2005 workshop on Wireless traffic measurements and modeling
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
Model T++: an empirical joint space-time registration model
Proceedings of the 7th ACM international symposium on Mobile ad hoc networking and computing
Proceedings of the 7th ACM international symposium on Mobile ad hoc networking and computing
Impact of communication infrastructure on forwarding in pocket switched networks
Proceedings of the 2006 SIGCOMM workshop on Challenged networks
Phase transitions of opportunistic communication
Proceedings of the third ACM workshop on Challenged networks
Proceedings of the 13th ACM international conference on Modeling, analysis, and simulation of wireless and mobile systems
Pervasive and Mobile Computing
Classifying the mobility of users and the popularity of access points
LoCA'05 Proceedings of the First international conference on Location- and Context-Awareness
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The evaluation of a great deal of research on ad hoc networks, as well as cellular networks, depends on models of user mobility. Many models have been developed and utilized, such as the random walk and random waypoint models. These are simple to implement and analyze but unlikely to be realistic. We develop a model based on extensive experimental data from a campus Wi-Fi LAN installation, representing traces from about 6000 users over a period of about 2 years. This data does not enable us to develop a user mobility model directly. However, as a first step, we develop a model of the time and sequence of locations at which user devices register. Note that this can be very useful, for instance to evaluate protocols that attempt to manage routing or resource allocations at different nodes. This paper reports work in progress on developing a user registration model. It shows the key time domain as well as space domain features we have extracted from the data. In particular, we show that the time features indicate heavy-tailed, although not power-law, distributions. The spatial features strongly indicate registration localization and hierarchy. The model itself can be represented as a set of probability distributions for various parameters. The modeler, for example a protocol designer, can then generate traces that conform to these distributions while varying the scale of the model in terms of the number of users. We close with a brief discussion of further work to refine and extend the model.