Density-based clustering method in the moving object database

Density-based clustering method in the moving object database

With the rapid advance of wireless communication, tracking the positions of the moving objects is becoming increasingly feasible and necessary. Because a large number of people use mobile phones, we must handle a large moving object database as well as the following problems. How can we provide the customers with high quality service, that means, how can we deal with so many enquiries within as less time as possible? Because of the large number of data, the gap between CPU speed and the size of main memory has increasing considerably. One way to reduce the time to handle enquiries is to reduce the I/O number between the buffer and the secondary storage. An effective clustering of the objects can minimize the I/O-cost between them. In this paper, according to the characteristic of the moving object database, we analyze the objects in buffer, according to their mappings in the two-dimension coordinate, and then develop a density-based clustering method to effectively reorganize the clusters. This new mechanism leads to the less cost of the I/O operation and the more efficient response to enquiries.