Analysis of a local-area wireless network

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Analysis of a local-area wireless network (2000)

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by Diane Tang

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194 - 3 self

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@INPROCEEDINGS{Tang00analysisof,
    author = {Diane Tang},
    title = {Analysis of a local-area wireless network},
    booktitle = {},
    year = {2000},
    pages = {1--10},
    publisher = {ACM Press}
}

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Abstract

To understand better how users take advantage of wireless networks, we examine a twelve-week trace of a building-wide local-area wireless network. We analyze the network for overall user behavior (when and how intensively people use the network and how much they move around), overall network traffic and load characteristics (observed throughput and symmetry of incoming and outgoing traffic), and traffic characteristics from a user point of view (observed mix of applications and number of hosts connected to by users). Amongst other results, we find that users are divided into distinct location-based sub-communities, each with its own movement, activity, and usage characteristics. Most users exploit the network for web-surfing, session-oriented activities and chat-oriented activities. The high number of chat-oriented activities shows that many users take advantage of the mobile network for synchronous communication with others. In addition to these user-specific results, we find that peak throughput is usually caused by a single user and application. Also, while incoming traffic dominates outgoing traffic overall, the opposite tends to be true during periods of peak throughput, implying that significant asymmetry in network capacity could be undesirable for our users. While these results are only valid for this local-area wireless network and user community, we believe that similar environments may exhibit similar behavior and trends. We hope that our observations will contribute to a growing understanding of mobile user behavior.

Keyphrases

local-area wireless network chat-oriented activity peak throughput traffic characteristic user-specific result single user significant asymmetry high number traffic dominates load characteristic distinct location-based sub-communities building-wide local-area wireless network opposite tends similar behavior network capacity synchronous communication mobile user behavior wireless network user community similar environment session-oriented activity many user overall network traffic mobile network usage characteristic user point observed mix overall user behavior twelve-week trace

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