Understanding usage patterns in wireless local-area networks (WLANs) is critical for those who develop, deploy, and manage WLAN technology, as well as those who develop systems and application software for wireless networks. This paper presents results from the largest and most comprehensive trace of network activity in a large, production wireless LAN. For eleven weeks we traced the activity of nearly two thousand users drawn from a general campus population, using a campus-wide network of 476 access points spread over 161 buildings. Our study expands on those done by Tang and Baker, with a significantly larger and broader population. We found that residential traffic...

Abstract — Providing scalable distributed Web-based eventing services has been an important research topic. It is desirable to have an effective mechanism for the servers to summarize their filters for in-network preprocessing in order to optimize system performance. In this paper, we propose a summary-based routing mechanism and introduce the notion of imprecise summaries to provide a trade-off between routing overhead and event traffic. Our system uses similarity-based filter clustering to reduce overall event traffic and performs self-tuning summary precision selection to optimize throughput. We have implemented summary-based routing on top of an XML-based infrastructure that closely follows the proposed Web services standards. Measurements from the actual implementation validate our analytical and simulation results, and demonstrate the practical benefits of the proposed techniques. I.

The demand for cellular data networks is expected to increase with 3G and beyond technologies accompanied by highbandwidth consumer services, such as wireless video and camera phones. User mobility affects quality of service, and makes capacity planning more difficult. This paper presents an analysis of user mobility patterns based on data traffic traces from a major regional CDMA2000 cellular network. We find low overall mobility in the network, power-law characteristics in user mobility profiles, and weak correlations between call activity and mobility levels for individual users. We also find that users concentrate their activity in a “home cell ” with frequent shorter trips to other locations in the network. Based on the empirical findings, we develop and parameterize a model of cellular data user mobility and show its practical use in simulation.

This paper describes the analysis of low-level measurements from a CDMA2000 1x cellular data network. The network traces record detailed information about wireless Internet packet data call activity on the network, including mobile station identity, call initiation, burst behaviour, supplementary channel usage, soft handoffs, and call termination. The analysis in this paper focuses on one continuous week-long trace data set, representative of cellular data network activity. The results from the analysis illustrate the burstiness of the packet call arrival process and the diurnal patterns of cellular data users. The results also characterize the activity per cell site, activity per user, data burst activity, user mobility, and the density of cellular network coverage. Several observations reinforce known results about heavytailed properties in wired Internet traffic, while others show interesting differences in wireless versus wireline traffic. 1.

Abstract. The World Wide Web has provided users with the opportunity to access from any computer the largest set of information ever existing. Researchers have analyzed how such users surf the Web, and such analysis has been used to improve existing services (e.g., by means of data mining and personalization techniques) as well as the generation of new ones (e.g., online targeted advertisement). In recent years, a new trend has developed by which users do not need a computer to access the Web. Instead, the low prices of mobile data connections allow them to access it anywhere anytime. Some studies analyze how users access the Web on their handsets, but these studies use only navigation logs from a specific portal. Therefore, very little attention (due to the complexity of obtaining the data) has been given to how users surf the Web (off-portal) from their mobiles and how that information could be used to build user profiles. This paper analyzes full navigation logs of a large set of mobile users in a developed country, providing useful information about the way those users access the Web. Additionally, it explores how navigation logs can be categorized, and thus users interest can be modeled, by using online sources of information such as Web directories and social tagging systems. 1

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