A study on skyline processing using hyperplane projections in multidimensional sensor data

Abstract

In sensor networks, data has many attributes and these attributes will be real values like temperature or moisture conditions. In this paper, we handle these sensor data with skyline processing for searching the data. Skyline processing is the one of representative method for top-k query processing. A top-k query returns k tuples with the lowest score from multidimensional relation consists of sensor data. We propose a method which improves the plane-project-parallel-skyline by eliminating data tuples. Our approach computes the approximate skyline once again when the number of data tuples in the subspace is bigger than other subspaces. © 2012 Springer Science+Business Media.