An efficient approach towards index structures for skyline queries

Abstract Given a multidimensional dataset, the skyline query is to find all objects that are not dominated by any other object in the dataset. This query represents a multi-objective optimization approach that is used extensively in various areas such as data analysis, decision support, and intellig...

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Main Authors: Huaiguang Song, Zhongbo Wu, Binglei Guo, Zhao Wu, Min Wang
Format: Article
Language:English
Published: Springer 2025-08-01
Series:Journal of King Saud University: Computer and Information Sciences
Subjects:
Online Access:https://doi.org/10.1007/s44443-025-00183-3
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author Huaiguang Song
Zhongbo Wu
Binglei Guo
Zhao Wu
Min Wang
author_facet Huaiguang Song
Zhongbo Wu
Binglei Guo
Zhao Wu
Min Wang
author_sort Huaiguang Song
collection DOAJ
description Abstract Given a multidimensional dataset, the skyline query is to find all objects that are not dominated by any other object in the dataset. This query represents a multi-objective optimization approach that is used extensively in various areas such as data analysis, decision support, and intelligent recommendation systems. However, even the most effective skyline query algorithms in the literature often show some limitations in dealing with diverse distribution data. By further analyzing the relationship between index structure and dominance tests, we propose the Quad*-Tree, a variant of the Quad-Tree that allows for configurable fan-out and addresses the issue of low node utilization in high-dimensional spaces. Based on Quad*-Tree, we introduce the concept of Node Dominance Groups (NDG). Based on NDG, we develop U-INDG (Upward Identification of Node Dominance Groups), a suite of novel and optimal skyline query approaches that significantly reduce the cost of dominance tests. Subsequently, we extend our approach to other index structures such as the sorted R-Tree, ZB-Tree, and Quad-Tree. Furthermore, U-INDG is simple to implement and can be efficiently scaled to various systems. Extensive experiments show that U-INDG outperforms the most efficient index-based skyline algorithms currently available. It significantly reduces query time across various types of datasets, with speedups ranging from approximately 2.4 $$\times $$ × to 7.8 $$\times $$ × compared to state-of-the-art algorithms, while ensuring stable performance.
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spelling doaj-art-6f5ee76087ec4b3cafb05c2eb9a6a0c92025-08-20T04:02:42ZengSpringerJournal of King Saud University: Computer and Information Sciences1319-15782213-12482025-08-0137612310.1007/s44443-025-00183-3An efficient approach towards index structures for skyline queriesHuaiguang Song0Zhongbo Wu1Binglei Guo2Zhao Wu3Min Wang4Department of Computer Engineering, Hubei University of Arts and ScienceDepartment of Computer Engineering, Hubei University of Arts and ScienceDepartment of Computer Engineering, Hubei University of Arts and ScienceDepartment of Computer Engineering, Hubei University of Arts and ScienceDepartment of Computer Engineering, Hubei University of Arts and ScienceAbstract Given a multidimensional dataset, the skyline query is to find all objects that are not dominated by any other object in the dataset. This query represents a multi-objective optimization approach that is used extensively in various areas such as data analysis, decision support, and intelligent recommendation systems. However, even the most effective skyline query algorithms in the literature often show some limitations in dealing with diverse distribution data. By further analyzing the relationship between index structure and dominance tests, we propose the Quad*-Tree, a variant of the Quad-Tree that allows for configurable fan-out and addresses the issue of low node utilization in high-dimensional spaces. Based on Quad*-Tree, we introduce the concept of Node Dominance Groups (NDG). Based on NDG, we develop U-INDG (Upward Identification of Node Dominance Groups), a suite of novel and optimal skyline query approaches that significantly reduce the cost of dominance tests. Subsequently, we extend our approach to other index structures such as the sorted R-Tree, ZB-Tree, and Quad-Tree. Furthermore, U-INDG is simple to implement and can be efficiently scaled to various systems. Extensive experiments show that U-INDG outperforms the most efficient index-based skyline algorithms currently available. It significantly reduces query time across various types of datasets, with speedups ranging from approximately 2.4 $$\times $$ × to 7.8 $$\times $$ × compared to state-of-the-art algorithms, while ensuring stable performance.https://doi.org/10.1007/s44443-025-00183-3Skyline queriesIndex structuresDiverse distribution dataDominance tests
spellingShingle Huaiguang Song
Zhongbo Wu
Binglei Guo
Zhao Wu
Min Wang
An efficient approach towards index structures for skyline queries
Journal of King Saud University: Computer and Information Sciences
Skyline queries
Index structures
Diverse distribution data
Dominance tests
title An efficient approach towards index structures for skyline queries
title_full An efficient approach towards index structures for skyline queries
title_fullStr An efficient approach towards index structures for skyline queries
title_full_unstemmed An efficient approach towards index structures for skyline queries
title_short An efficient approach towards index structures for skyline queries
title_sort efficient approach towards index structures for skyline queries
topic Skyline queries
Index structures
Diverse distribution data
Dominance tests
url https://doi.org/10.1007/s44443-025-00183-3
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