Mobility knowledge discovery in wireless networks

Wireless networks and mobile applications have grown very rapidly and have made a significant impact on computer systems. Especially, the usage of mobile phones and PDA is increased very rapidly. Added functions and values with these devices are thus greatly developed. If some regularity can be known from the user mobility behavior, then these functions and values can be further expanded and used intelligently. This paper thus attempts to mine appropriate mobility patterns for being used by mobile-system managers in future strategy planning. The location areas in which mobile users visit can be found from the log data stored in the home-location-register module. The preprocessing task for preparing appropriate data from HLR is then done. The mobility sequences from mobile users are formed. The algorithm then calculates the count of each term in all mobility sequences. The mining process based on counts is then performed to find mobility patterns.