Analysis of a local-area wireless network
MobiCom '00 Proceedings of the 6th annual international conference on Mobile computing and networking
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
Towards a model of user mobility and registration patterns
ACM SIGMOBILE Mobile Computing and Communications Review
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
The QoS-RWP mobility and user behavior model for public area wireless networks
Proceedings of the 9th ACM international symposium on Modeling analysis and simulation of wireless and mobile systems
Density estimation for out-of-range events on personal mobile devices
Proceedings of the 1st ACM SIGMOBILE workshop on Mobility models
An analytical study of fundamental mobility properties for encounter-based protocols
International Journal of Autonomous and Adaptive Communications Systems
A Novel Mobility Model from a Heterogeneous Military MANET Trace
ADHOC-NOW '08 Proceedings of the 7th international conference on Ad-hoc, Mobile and Wireless Networks
User-Centric Mobility Models for Opportunistic Networking
Bio-Inspired Computing and Communication
Agenda driven mobility modelling
International Journal of Ad Hoc and Ubiquitous Computing
Modeling spatial and temporal dependencies of user mobility in wireless mobile networks
IEEE/ACM Transactions on Networking (TON)
An analysis of human mobility using real traces
WCNC'09 Proceedings of the 2009 IEEE conference on Wireless Communications & Networking Conference
Fitting opportunistic networks data with a pareto distribution
KES'07/WIRN'07 Proceedings of the 11th international conference, KES 2007 and XVII Italian workshop on neural networks conference on Knowledge-based intelligent information and engineering systems: Part III
Fine-grained mobility characterization: steady and transient state behaviors
Proceedings of the eleventh ACM international symposium on Mobile ad hoc networking and computing
Predicting mobility events on personal devices
Pervasive and Mobile 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
An empirical framework for user mobility models: Refining and modeling user registration patterns
Journal of Computer and System Sciences
Proceedings of the 14th ACM international conference on Modeling, analysis and simulation of wireless and mobile systems
A global local modeling of internet usage in large mobile societies
Proceedings of the 7th ACM workshop on Performance monitoring and measurement of heterogeneous wireless and wired networks
Analysing the mobility, predictability and evolution of WLAN users
International Journal of Autonomous and Adaptive Communications Systems
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We present an empirical registration model derived from the WLAN registration patterns of the mobile users. There exist models that accurately describe individually the spatial and temporal aspects of user registration, and demonstrate the importance of this modeling. The main distinction of the new model from the previous empirical models is that we are able to formulate the inter-dependence of space and time explicitly by a set of few equations. Our extensive studies of the WLAN traces indicate that a simple but proper notion of popularity radient suffices to capture the correlation across space and time. Indeed, when locations (i.e., AP coverage area) are differentiated with respect to the number of visits they are receiving (i.e., AP popularity), the time spent at each location i before user moves from i to k turns out to be closely related to the difference of popularity between locations i and k This observation led to the design of a joint time-space registration model (referred to as ModelT++) that builds upon the Model T, which itself models only the space aspect of the registration, but is derived from the same campus WiFi network. As part of the process of generating a joint space-time model, we further extend spatial aspects of the Model T. We evaluate our model using various metrics against a random walk model as well as the Model T by superimposing location independent time series on these space-only registration models. Our results suggest that with a slight increase in the model complexity, our joint time-space registration model is able to better capture the real network registration than the independent time models. Model T++ can be easily integrated into both WLAN and multi-hop wireless mesh network simulations that require realistic registration models.