Similar base sequence query method based on editing distance in cloud environment

Abstract

The invention discloses a similar base sequence query method based on an editing distance in a cloud environment. The method is mainly used for solving the problem of finding similar base sequences from massive electronic records of cloud when the cloud is not completely credible. The method comprises the realization steps of (1), calculating a single character operation set of user base sequences; (2), carrying out clustering; (3), carrying out hash mapping on the user base sequences and a clustering center; (4), calculating the single character operation set of to-be-queried base sequences; (5); carrying out hash mapping on the to-be-queried base sequences; (6), selecting candidate clients; (7) and searching the similar base sequences. According to the method, the similar base sequence query method based on the editing distance in the cloud environment is applied to the cloud environment. Compared with the traditional similar base sequence query method, the method provided by the invention has better extensibility and scalability; the security of the base sequences in the cloud environment is ensured; and the consumption of the hardware resources is reduced.

Description

technical field [0001] The invention belongs to the field of computer technology, and further relates to a method for querying similar base sequences based on edit distance in a cloud environment in the field of cloud computing technology. The invention can be used to find similar base sequences from a large number of electronic records in the cloud when the cloud is not fully credible in the cloud computing environment. Background technique [0002] Sequence data is an important and special type of data, which widely exists in applications such as text, Web access sequences, and base sequences and protein sequences in biological databases. With the development of society and the advancement of technology, the research on efficient query of sequence data also poses severe challenges. Character sequence is a kind of common sequence data. Since character sequence has the characteristics of difficult feature extraction and effective expression, and the calculation of similarit...

AI Technical Summary

Problems solved by technology

In most of the existing similarity query algorithms for character sequences, most of them only use the characteristics of the sequence itself for calculation. There are problems: it consumes a lot of time, the operation efficiency is not high, and a large amount of hardware facilities are required, and the security of sequence data cannot be guaranteed.

The shortcomings of this method are: using edit distance to calculate the similarity of strings, the calculation efficiency will be limited by the size of the data, and the scalability and scalability are not strong; the security of sequence data cannot be guaranteed when calculating edit distance, and the string may Maliciously attacked or stolen by hackers, leaking string information

The disadvantage of this method is that all genomic data are stored in the local database, which takes up hardware resources. As the amount of data increases, it will exceed the carrying range of the database and cannot be calculated.

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