Study On Reverse Skyline Query Processing Techniques On Data Streams

With the development of economic and the progress of technological means, the flow property of data becomes more and more apparent. Reverse skyline query on data streams as an important operator for current market decision making, can be extensively applied in our daily life. However, the existing reverse skyline query algorithm on data streams can not take full advantage of the property of reverse skyline on data streams, so the algorithm’s performance is very poor, and it can not meet the practical needs. At the same time, people make profound understanding of the uncertainty of data, so reverse skyline query can be introduced to uncertain data streams.This thesis deeply studies the reverse skyline query on data streams and its corresponding problems. Its contributions are summarized as follows:1. The problem of reverse skyline query on data streams is discussed. This thesis makes a profound analysis on the properties of the reverse skyline query on data streams, according to the properties, a query model of reverse skyline on data streams is designed, and an efficient reverse skyline algorithm on data streams (RSDS) is proposed.2. The issue of probabilistic reverse skyline query on uncertain data streams is discussed. The thesis makes a profound analysis on the properties of probabilistic reverse skyline query on uncertain data streams, according to the properties, a query model of probabilistic reverse skyline on uncertain data streams is designed, and an efficient probabilistic reverse skyline algorithm on uncertain data streams (PRSDS) is proposed.3. Through a large number of simulation experiments, it proves that all algorithms in this thesis are correct. Comparing with the existing algorithm DCRS, it proves that RSDS algorithm has high availability. And through analysis experimental results of PRSDS algorithm, it proves that PRSDS is effective.