2nd International ICST Workshop On Wireless Network Measurement

Research Article

On Modeling User Associations in Wireless LAN Traces on University Campuses

  • @INPROCEEDINGS{10.1109/WIOPT.2006.1666494,
        author={Wei-Jen Hsu and Ahmed  Helmy},
        title={On Modeling User Associations in Wireless LAN Traces on University Campuses},
        proceedings={2nd International ICST Workshop On Wireless Network Measurement},
        publisher={IEEE},
        proceedings_a={WINMEE},
        year={2006},
        month={8},
        keywords={},
        doi={10.1109/WIOPT.2006.1666494}
    }
    
  • Wei-Jen Hsu
    Ahmed Helmy
    Year: 2006
    On Modeling User Associations in Wireless LAN Traces on University Campuses
    WINMEE
    IEEE
    DOI: 10.1109/WIOPT.2006.1666494
Wei-Jen Hsu1,*, Ahmed Helmy1
  • 1: Department of Electrical Engineering, University of Southern California
*Contact email: weijenhs@usc.edu

Abstract

In this paper we analyze wireless LAN (WLAN) traces collected from four different sources, including three university campus WLANs and one corporate WLAN to compare the similarities and differences of user association behavior to access points (APs) in these environments. This study provides extensive comparison of multiple WLAN traces, and outlines a basis for creating models for user association patterns in WLANs. We propose a set of important metrics for modeling the association patterns of wireless LAN (WLAN) users. Specifically, we look into (a) Activeness of users, (b) Macro-level mobility, (c) Micro-level mobility and (d) Repetitive association patterns. We find that (1) A significant portion of users are offline for non-neligible fraction of time (on average, the online time fraction is between 87.68% and 14.12% for the traces we studied). (2) Users visit only a small subset of APs (on average less than 5%, and the maximum is less than 35%), and (3) Users show periodic pattern of visiting the same APs in some traces. The findings along these aspects show similar trends among the traces, with differences in details due to both underlying user population/environments and methodologies of trace collection.