A Distributed Algorithm for Skyline Query Based on Pre-Clustering

Abstract

With the increasing availability and mobile application of LBS (Location-Based Services), large scale spatial objects remind challenge in cloud environments. In order to retrieve a few data items within a very large structured data set, skyline queries are utilized to optimize a single respectively multiple criteria. In this paper, we develop a new pre-clustering-based skyline queries technique to address the skewed distribution problem. We also present distributed approaches that construct grid index and process skyline queries. We evaluate the effectiveness of our algorithms with extensive experiments using real data sets. The results demonstrate the efficiency and scalability of our skyline queries algorithms based on pre-clustering.

Scalable multi‐dimensional RNN query processing

“…We need to propose a new distributed index which enables efficient parallel processing of SRNN queries. So pre‐clustering‐based method is proposed to optimize performance of inverted grid index which can be used to SRNN queries or other spatial queries .…”