Optimized Query Algorithms for Top- K  Group Skyline

Jia Liu,Yasser H Elawady,Ziyang Chen,Lin Liu,Wei Chen,Kaiyu Liu,Yuhong Wu,Amar Jain

doi:10.1155/2022/3404906

Abstract

Skyline query is a typical multiobjective query and optimization problem, which aims to find out the information that all users may be interested in a multidimensional data set. Multiobjective optimization has been applied in many scientific fields, including engineering, economy, and logistics. It is necessary to make the optimal decision when two or more conflicting objectives are weighed. For example, maximize the service area without changing the number of express points, and in the existing business district distribution, find out the area or target point set whose target attribute is most in line with the user’s interest. Group Skyline is a further extension of the traditional definition of Skyline. It considers not only a single point but a group of points composed of multiple points. These point groups should not be dominated by other point groups. For example, in the previous example of business district selection, a single target point in line with the user’s interest is not the focus of the research, but the overall optimality of all points in the whole target area is the final result that the user wants. This paper focuses on how to efficiently solve top- k group Skyline query problem. Firstly, based on the characteristics that the low levels of Skyline dominate the high level points, a group Skyline ranking strategy and the corresponding SLGS algorithm on Skyline layer are proposed according to the number of Skyline layer and vertices in the layer. Secondly, a group Skyline ranking strategy based on vertex coverage is proposed, and corresponding VCGS algorithm and optimized algorithm VCGS+ are proposed. Finally, experiments verify the effectiveness of this method from two aspects: query response time and the quality of returned results.

Highlights

Skyline query are called maxima or Pareto [1]
(1) Aiming at the problem of large result set and large number of meaningless result point groups in existing Skyline algorithm, the Skyline query problem of the top-k group is given, and a SLGS algorithm based on Skyline layer is proposed to return k optimal Skyline point groups
This algorithm combines the structural characteristics of the high-level points dominated by the middle and low-level points in Skyline layer and gives a quantitative criterion to find the better one of two groups

Summary

Introduction

Skyline query are called maxima or Pareto [1] (to gain optimality without harming the interests of others in the field of business management). In the skyline query on the data stream, with the dynamic change of data stream tuples, for a given constraint query, Wireless Communications and Mobile Computing find the nodes that fall into the valid area or affect the result tuple set Such queries are often applied to intelligent transportation, online monitoring, and other fields. Liu et al [12] first extend the Skyline based on an original single point to the Skyline based on the point group and propose the corresponding algorithm for Skyline In practical applications, such objective optimization problems can be applied to path optimization [13] to calculate the minimum cost path, mobile trajectory tracking [14, 15] to look for similar trajectories, social networks to find close communities, and graph correlation [16] to get the correlation degree of the target point. The validity and accuracy of the proposed algorithms are verified

Background Knowledge

Query Algorithm Based on Skyline Layer

Query Algorithm Based on Vertex Cover

Experiment and Result Analysis

The Performance Comparison and Analysis

Conclusions