Distance-based algorithm for solving representative node set in two-dimensional space

Abstract

The invention discloses a novel distance-based algorithm for solving a representative node set in a two-dimensional space. The novel distance-based algorithm comprises the steps of inputting a data set; calculating the Skyline point set Q in the data set through the BNL algorithm; sequencing the point set Q; solving the manhattan distance value from the initial point to any other Skyline point and storing; solving k representative Skyline points in the Skyline point set; returning the k representative Skyline points. According to the algorithm, the time complexity is shown as O (K2LOG3m) which is far less than that of the DRS algorithm in the prior art.

Description

technical field [0001] The invention relates to a new distance-based algorithm for solving representative node sets in two-dimensional space (New Distance-based Representative Skyline, NDRS for short). Background technique [0002] The Skyline query problem was proposed by Borzsonyi in 2001. In recent years, Skyline's query processing has attracted the attention of a large number of database researchers, and has quickly become a research hotspot in the database field. A large number of Skyline query processing algorithms have been born. The existing achievements mainly cover three aspects: [0003] (1) Skyline query processing on centralized database: including BNL algorithm (Block Nested Loop), SFS algorithm (Sort Filter Skyline), divide and conquer algorithm (Divide and Conquer), bitmap algorithm (Bitmap), index algorithm (Index) [5], NN algorithm (Nearest Neighbor), BBS (Branch and Bound Skyline) [3], etc. [0004] (2) Skyline query processing on distributed databases:...

AI Technical Summary

Problems solved by technology

[0008] Among the above algorithms, the TRS algorithm has an obvious shortcoming, that is, the selected "representative Skyline points" have a certain bias, and tend to be biased towards places where the points in the data set are relatively dense. At the same time, its time complexity (O(km 2 +nlog(m))) is too high, where n represents the number of points in the data set, and m represents the number of Skyline points

Therefore, it will be difficult to guarantee the effectiveness of TRS in scenarios where the data scale is large and the data distribution is concentrated

Although the DRS-based algorithm solves the defect that TRS cannot represent the entire Skyline point set well, the time complexity is still too high (O(|D|.log(m)+m 2 (k-2))), where |D| represents the size of the data set, which severely restricts the scope of application of the algorithm

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