Optimized Query Algorithms for Top- K Group Skyline

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.

Analysis using top‐k skyline query of protein‐protein interaction reveals alpha‐synuclein as the most important protein in Parkinson’s disease

Parkinson’s disease is the second‐most‐common neurodegenerative disorder and can reduce patients’ quality of life. The disease is caused by abnormalities in dopaminergic neurons, such as reactive oxygen species (ROS) imbalance leading to programmed cell death, protein misfolding, and vesicle trafficking. Protein‐protein interaction (PPI) analysis has been demonstrated to understand better candidate proteins that might contribute to multifactorial neurodegenerative diseases, particularly in Parkinson’s disease. PPI analysis can be obtained from experiments and computational predictions. However, experiment data is often limited in interactome coverage. Therefore, additional computational prediction methods are required to provide more comprehensive PPI information. PPI can be represented as protein‐protein networks and analyzed based on centrality measures. The previous study has shown that top‐k skyline query, a method using dominance rule‐based centrality measures, reveals important protein candidates in Parkinson’s diseases. This study applied the top‐k skyline query to PPIs containing experiment and prediction data to find important proteins in Parkinson’s disease. The result shows that alpha‐synuclein (SNCA) is the most important protein and is expected to be a potential biomarker candidate for Parkinson’s disease.

Implementasi Skyline Query pada Sistem Rekomendasi Pemilihan Tempat Kuliner di Kota Depok, Bogor, dan Tanggerang

Usaha ekomomi kreatif berupa warung kuliner dalam beberapa tahun ini marak bermunculan di berbagai daerah di Indonesia. Adanya aplikasi platform digital untuk rekomendasi pemilihan tempat kuliner unggulan daerah diharapkan akan menjadi sangat membantu wisatawan dalam memilih tempat kuliner yang diinginkan sesuai dengan preferensi yang dimiliki. Terdapat tiga aspek sebagai standar dari usaha kuliner yaitu aspek produk, aspek pelayanan dan aspek pengelolaan, aspek ini dapat menjadi acuan dalam preferensi seseorang dalam memilih atau menentukan rating dari sebuah usaha kuliner. Penelitian ini menggunakan metode skyline query untuk implementasi rekomendasi pemilihan tempat makan berdasarkan preferensi wisatawan pada empat aspek kriteria: makanan, suasana, layanan dan kesehatan. Hasil survey melalui kuesioner dari 169 responden yang berasal dari kota Depok, Bogor dan Tanggerang didapat 85,63% responden memilih tempat makan berdasarkan aspek layanan, 77,42% aspek kesehatan, 73,99% aspek suasana, dan 67,82% aspek makanan. Hasil implementasi algoritma skyline query pada sistem database relasional MySQL dan prototype aplikasi berbasis web didapat 100% fungsional aplikasi berjalan dengan baik.

Efficiently computing Pareto optimal G-skyline query in wireless sensor network

There are much data transmitted from sensors in wireless sensor network. How to mine vital information from these large amount of data is very important for decision-making. Aiming at mining more interesting information for users, the skyline technology has attracted more attention due to its widespread use for multi-criteria decision-making. The point which is not dominated by any other points can be called skyline point. The skyline consists of all these points which are candidates for users. However, traditional skyline which consists of individual points is not suitable for combinations. To address this gap, we focus on the group skyline query and propose efficient algorithm to computing the Pareto optimal group-based skyline (G-skyline). We propose multiple query windows to compute key skyline layers, then optimize the method to compute directed skyline graph, finally introduce primary points definition and propose a fast algorithm based on it to compute G-skyline groups directly and efficiently. The experiments on the real-world sensor data set and the synthetic data set show that our algorithm performs more efficiently than the existing algorithms.

Sampling-based approximate skyline calculation on big data

Nowadays, big data is coming to the force in a lot of applications. Processing a skyline query on big data in more than linear time is by far too expensive and often even linear time may be too slow. It is obviously not possible to compute an exact solution to a skyline query in sublinear time, since an exact solution may itself have linear size. Fortunately, in many situations, a fast approximate solution is more useful than a slower exact solution. This paper proposes two sampling-based approximate algorithms for processing skyline queries. The first algorithm obtains a fixed size sample and computes the approximate skyline on it. The error of the algorithm is not only relatively small in most cases, but also is almost unaffected by the input size. The second algorithm returns an [Formula: see text]-approximation for the exact skyline efficiently. The running time of the algorithm has nothing to do with the input size in practical, achieving the goal of sublinearity on big data. Experiments verify the error analysis of the first algorithm, and show that the second is much faster than the existing skyline algorithms.

A Power Grid Fault Diagnosis Method in the Case of Alarm Information Loss Based on the Top-k Skyline Query Algorithm

After the failure of the power system, a large amount of alarm information will flood into the dispatching terminal instantly. At the same time, there are inevitable problems, such as the abnormal operation of the protection and the circuit breaker, the lack of alarm information, and so on. This kind of uncertainty problem brings great trouble to the fault diagnosis algorithm. As a data processing algorithm for an uncertain information set, Top-k Skyline query algorithm can eliminate the data points that do not meet the requirements in the information set, and then output the final K results in order. Based on this background, this paper proposes a power grid fault diagnosis method based on the Top-k Skyline query algorithm considering alarm information loss. Firstly, the fault area is determined by using the information of the electrical quantity and switching value. Then, backward reasoning Petri nets are established for the nodes in the fault area to form the data set of fault hypotheses. Then, the Top-k Skyline query algorithm is used to sort the hypotheses and choose the hypothesis with higher reliability. Finally, an IEEE 39-bus system example is given to verify the reliability of the proposed method.