Adaptive channel allocation for wireless PCN
Mobile Networks and Applications - Special issue: resource management in mobile wireless communication networks
Mining the most interesting rules
KDD '99 Proceedings of the fifth ACM SIGKDD international conference on Knowledge discovery and data mining
LeZi-update: an information-theoretic approach to track mobile users in PCS networks
MobiCom '99 Proceedings of the 5th annual ACM/IEEE international conference on Mobile computing and networking
Principles of data mining
Architecture and algorithms for scalable mobile QoS
Wireless Networks
User Mobility Pattern Scheme for Location Update and Paging in Wireless Systems
IEEE Transactions on Mobile Computing
Pattern Classification (2nd Edition)
Pattern Classification (2nd Edition)
An adaptive bandwidth reservation scheme for high-speed multimedia wireless networks
IEEE Journal on Selected Areas in Communications
Journal of Control Science and Engineering
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A centralized collaborative system between nodes and BSs is developed, and a new prediction mobility scheme is proposed with Data Mining and Time Series techniques. Based on the mobility prediction, bandwidth is reserved for the paths with the maximum support or the best confidence rule, so that the handoff calls' service can be guaranteed. This new approach belongs to the Direct Group Mobility (DGM) prediction scheme and is based on the Tree Path Construction Algorithm (TPCON) for each Base Station (BS). The nodes with DGM support provide the BSs with the important aggregate bandwidth information so that they can avoid the congestion for the handoff users' sake. For finding the most popular group path, based on TPCON, clusters are constructed according to the various flows of the group mobility over an area of mobile stations. We focus on the center oriented clusters that are very crucial for bandwidth prediction purposes. An adaptive clustering algorithm creates the chain of activated cells at each time. A Call Admission Control (CAC) algorithm is developed for each BS for minimizing the call dropping probability. This study deals with the system behavior only at exceptional congestion time periods (periodical events). Simulation results are provided.