Analyze and Update Data Method for Skyline Query Processing Against Distributed Data Sites
D. Umadevi, Shaheda Akthar, Sri Mittapalli · 2012
The skyline of a multidimensional point set is a subset of interesting points that are not dominated by others. In this paper, We are introducing the Analyze and Update data Method which enhances the constrained Skyline query processing against distributed data sites approach and user centric approach. User can easly compares the result data dynamically. we follow constrained skyline queries in a large-scale unstructured distributed environment, where relevant data are distributed among geographically scattered sites.A partition algorithm that divides all data sites into incomparable groups such that the skyline computations in all groups can be parallelized without changing the final result, then develop a novel algorithm framework called PaDSkyline for parallel skyline query processing among partitioned site groups. The method also employ intragroup optimization and multifiltering technique to improve the skyline query processes within each group. In particular, multiple (local) skyline points are sent together with the query as filtering points, which help identify unqualified local skyline points early on a data site. In this way, the amount of data to be transmitted via network connections is reduced, and thus, the overall query response time is shortened further. Cost models and heuristics are proposed to guide the selection of a given number of filtering points from a superset. A cost efficient model is developed to determine how many filtering points to use for a particular data site. The results of an extensive experimental study demonstrate that our proposals are effective and efficient.