Data Distribution Level Skyline. Distributed Database Computing

skyline operation filters out a set of points that are not dominated by any other point in the database. A point dominates another point if it is as good or better in all dimensions and better in at least one dimension. What is good or bad is not strictly defined, and it depends on customer. Recently, skyline operation has received a lot of attention in database community. This is mainly due to the importance of skyline in many applications, such as multi-criteria decision making, data mining and database visualization. As far as the research is concerned, skyline operation of distributed database has not developed as fast as the centralized database for its late start.Therefore, this paper, focusing on the distributed database, researches skyline operation with data in level distribution. (Level distribution refers to the storage of data in different servers.) The following aspects are included:Firstly, this paper proposes to calculate the global skyline after gathering all partial skyline results through analyzing the relationship between partial skyline and global skyline in each server.Secondly, this paper provides an optimal strategy to increase the efficiency of calculating through region division and multi-windows collection. More specifically, it discusses the idea of region division as well as the dominance relation among the divisions in different servers. An algorithm of three-dimensional data space is put forward based on such strategy.Thirdly, this paper probes into skyline operation in high-dimensional data space and offers the idea of only dividing the first three-dimension data.Fourthly, this paper, after analyzing lots of experimental results, comes to the conclusion that the strategy of region division and multi-windows collection contributes to improving skyline operation efficiency in distributed database.