Open Access

ARTICLE

SI Bitmap Index and Optimization for Membership Query

Shu Gao^a,b,*, Zhen Wang^a, Liangchen Chen^a

^a School of Computer Science,Wuhan University of Technology, Wuhan, 430063, China;
^b Hubei Key Laboratory of Transportation Internet of Things, Wuhan University of Technology, Wuhan, 430063, China.

* Corresponding Author: Shu Gao

Intelligent Automation & Soft Computing 2019, 25(4), 683-689. https://doi.org/10.31209/2018.100000061

Abstract

The explosive growth of data produced by internet of things has contributed to the abundance of data. Since then, efficient indexing and querying techniques for data retrieval has become a major challenge. Bitmap index and its extension techniques, which involve a bit sequence that represents a specified property and indicates the data items that satisfies this property, are well-known methods to improve processing time for complex and interactive queries on the read-mostly or append-only data. This paper proposes an improved bitmap index technique, named Sliced-Interval Bitmap Index (SI Bitmap Index), which is efficient in both space and response time for Membership query. It also describes the method to optimize Membership query, based on SI Bitmap Index, in four steps. Experimental results indicate that SI Bitmap Index is space-saving as well as high efficiency on Membership query.

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Keywords

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