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International Workshop on Wireless Traffic Measurements and Modeling — Abstract
Pp. 19–24 of the Proceedings
Modeling Users' Mobility among WiFi Access Points
Modeling Users' Mobility among WiFi Access Points
Abstract
Modeling movements of users is important for simulating wireless networks, but
current models often do not reflect real movements. Using real mobility traces,
we can build a mobility model that reflects reality. In building a mobility
model, it is important to note that while the number of handheld wireless
devices is constantly increasing, laptops are still the majority in most cases.
As a laptop is often disconnected from the network while a user is moving, it is
not feasible to extract the exact path of the user from network messages. Thus,
instead of modeling individual user's movements, we model movements in terms of
the influx and outflux of users between access points (APs). We first
counted the hourly visits to APs in the syslog messages recorded at APs. We
found that the number of hourly visits has a periodic repetition of 24 hours.
Based on this observation, we aggregated multiple days into a single day
by adding the number of visits of the same hour in different days.
We then clustered APs based on the different peak hour of visits.
We found that this approach of clustering is effective; we ended up with four
distinct clusters and a cluster of stable APs. We then computed the average
arrival rate and the distribution of the daily arrivals for each cluster. Using
a standard method (such as thinning) for generating non-homogeneous
Poisson processes, synthetic traces can be generated from our model.
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