Wavelet transformation-based management of integrated summary data for distributed query processing
As the Internet technology evolves, there is growing need for Internet queries involving multiple information sources. Efficient processing of such queries necessitates the integrated summary data that compactly represents the data distribution of the entire database scattered over many information sources. We propose a new method based on wavelet transform that creates and maintains the integrated summary data by merging multiple instances of summary data, each of which is maintained in an information source. A wavelet-based summary data is easily converted to satisfy conditions for merging. Moreover, the merging process is very simple owing to the shifting and linearity properties of wavelet transform. We formally derive the upper bound of the absolute, square-root, and maximum errors in the integrated wavelet-based summary data. We also show that the integrated summary data can be used for optimizing Internet queries effectively.
wavelet transformation summary data internet queries selectivity estimation