An efficient skyline query algorithm in the distributed environment

2021 ◽  
pp. 101524
Author(s):  
Mei Bai ◽  
Senan Jiang ◽  
Xin Zhang ◽  
Xite Wang
Keyword(s):  
Distributed Environment ◽  
Skyline Query ◽  
Query Algorithm

A New Quadtree-Based Skyline Query Algorithm

2014 ◽  
Vol 981 ◽  
pp. 175-178
Author(s):  
Run Tao Liu ◽  
Yuan Jing Chen ◽  
Da Yong Cao ◽  
De Yu Liu
Keyword(s):  
Detailed Analysis ◽  
Spatial Data ◽  
Index Structure ◽  
Skyline Query ◽  
Set Up ◽  
Query Algorithm

In this paper, the index structure, PR-quadtree for spatial data, is used to store data for a database. The properties of the quadtree are studied. With the properties prunning rules are set up for searching the Skyline set of the data stored in the quadtree. Through detailed analysis for the tree the method of finding some approximate skyline points is designed, by which a new skyline searching algorithm is given. The new algorithm is more effective.

k-dominant Skyline query algorithm for dynamic datasets

2020 ◽  
Vol 15 (1) ◽  
Author(s):  
Zhiyun Zheng ◽  
Ke Ruan ◽  
Mengyao Yu ◽  
Xingjin Zhang ◽  
Ning Wang ◽  
...  
Keyword(s):  
Skyline Query ◽  
Query Algorithm

User Preference Based Spatial Skyline Query Method

2014 ◽  
Vol 530-531 ◽  
pp. 832-838
Author(s):  
Yong Gui Zou ◽  
Zhi Wang
Keyword(s):  
Spatial Data ◽  
Road Network ◽  
User Preference ◽  
Skyline Query ◽  
Data Set ◽  
Second Stage ◽  
Processing Data ◽  
Data Volume ◽  
Definition Of ◽  
Query Algorithm

With the increasing of data volume and data dimensions in road network query, the response gets slow in searching services, which cannot satisfy users demand for preference-based searching. This paper proposes a user preference-based Skyline query algorithm. At the first stage, this method is based on the fact that the static property of data does not change during the query processes. Therefore, Skyline starts its calculation in the non-spatial data set to have the candidate results and dominance relation. Then it calculates the total costs of routine by defining user preference function. At the second stage, compare the data connections with the total costs of preference to minimize time for processing data and searching. The experiment result shows that the definition of user preference meets the users demand, and Skyline query algorithm benefits to have quick response.

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

Energies ◽  
2021 ◽  
Vol 14 (19) ◽  
pp. 6223
Author(s):  
Lei Jin ◽  
Qing Chen ◽  
Jinjie Ji ◽  
Xiaotong Zhou
Keyword(s):  
Fault Diagnosis ◽  
Power Grid ◽  
Circuit Breaker ◽  
Information Loss ◽  
Uncertain Information ◽  
Skyline Query ◽  
Data Set ◽  
Information Set ◽  
Diagnosis Method ◽  
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.

An Adaptive Parallel PI-Skyline Query for Probabilistic and Incomplete Database

2019 ◽  
Vol 17 (07) ◽  
pp. 1950036
Author(s):  
Zezheng Liu ◽  
Yifu Zeng ◽  
Siyuan He ◽  
Yantao Zhou
Keyword(s):  
Data Mining ◽  
Decision Making ◽  
Incomplete Data ◽  
The Internet ◽  
Dominance Relationship ◽  
Skyline Query ◽  
Transmission Errors ◽  
Uncertain Database ◽  
Effectiveness And Efficiency ◽  
Query Algorithm

In the context of large quantities of information, the skyline query is a particularly useful tool for data mining and decision-making. However, the massive amounts of information on the Internet are frequently incomplete and uncertain due to data randomness, transmission errors, and many other reasons. Therefore, an efficient skyline query algorithm over an incomplete uncertain database is imperative. To address this issue, this paper proposes an efficient algorithm to apply skyline query on probabilistic incomplete data. The algorithm is based on U-Skyline model to avoid disadvantages of traditional P-Skyline model. The proposed methods introduce some novel concepts including transferred tuples, leading tuples and the new dominance relationship between probabilistic incomplete data. Besides, it is a parallel processing algorithm. Extensive experiments demonstrate the effectiveness and efficiency of the proposed algorithms.

scholarly journals Modified skyline query to measure priority region for personal protective equipment recipient of COVID-19 health workers

2021 ◽  
Vol 9 (3) ◽  
pp. 167-173
Author(s):  
Vega Purwayoga
Keyword(s):  
Personal Protective Equipment ◽  
Health Workers ◽  
Selection Process ◽  
Vital Role ◽  
Protective Equipment ◽  
Skyline Query ◽  
West Java ◽  
Query Algorithm

The distribution of personal protective equipment (PPE) plays a vital role in meeting the needs of PPE in an area. This study aims to measure the priority of PPE recipient regions in West Java Province using a skyline query algorithm, namely Sort Filter Skyline (SFS). In this study, the SFS algorithm is modified to optimize the dominance measurement section. Regions that do not have hospitals will not be prioritized for PPE recipients. The preferences used in this study are maximum and minimum. The maximum preference rule is used for the number of ODP, PDP, positive and dead cases, while the minimum preference rule is used for the cured and distance attributes. The application of SFS for calculating priority regions has been successfully carried out by developing two models, namely MS1 using unmodified SFS and MS2 using modified SFS by adding a selection process for regions with no hospitals. The MS1 produces 21 skyline objects (55.55 %), while MS2 15 (66.66 %) skyline objects. The MS2 is faster than that of MS1 because fewer objects are being tested. The MS1 takes 0.0222 seconds, while MS2 only 0.0193 seconds.

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