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In this paper, we investigate a campus wide Wireless Local Area Network (WLAN) over a period of one month with the help of an advanced training system. Traffic characteristics and analysis has been performed based on the users` connectivity and their traffic behavior in a WLAN environment. The obtained results predict the users` traffic intensity in different time slots of the day and different days...