An Adaptive Algorithm for Computing Subspace SKYLINE Queries Over Distributed Uncertain Data

The skyline queries has received considerable attention from the database community, due to its importance in many applications including multicriteria decision making, preference answering, and so forth. Data collected from different sources in distributed locations exhibit a kind of uncertainty. A skyline query retrieves the set of nondominated data points in a multi-dimensional dataset. For efficient subspace skyline processing, a notion of subspace dataset is derived, which contains all data elements that are necessary to answer a skyline query in any arbitrary subspace. Then the problem of distributed skyline computation is studied and proposed an adaptive algorithm towards re tr ievi ng the g lobal skyl i ne tuple s f rom al l t he di st ribute d l ocal si te s wi t h mi nim um comm unic at ion c os t .