Effective Top-down Clustering Algorithms for Location Database Systems

Recent technological advances in mobile communication systems have made explosive growth in the number of mobile device users worldwide. One of the most important issues in designing a mobile computing system is location management of users. The hierarchical systems had been proposed to solve the scalability problem in the location management. The scalability problem occurs when there are too many users for a mobile system to handle thus, the system is likely to react slow or even get down due to the late updates of the location databases. In this paper, we first propose a top-down clustering algorithm for hierarchical location database systems in a wireless network. A hierarchical location database system employs a tree structure. The proposed algorithm uses a top-down approach and utilizes the number of visits to each cell made by the users along with the movement information between a pair of adjacent cells. We then present a modified algorithm by incorporating the exhaustive method when there remain a few levels of the tree to be processed. The experimental results show that the modified top-down algorithm reduces the average update cost by 19.0% and the update time by about 61.0% over the previous work.