Block-Based Multi-Version B$^+$ -Tree for Flash-Based Embedded Database Systems

2015 ◽  
Vol 64 (4) ◽  
pp. 925-940 ◽  
Author(s):  
Jiantao Wang ◽  
Kam-Yiu Lam ◽  
Yuan-Hao Chang ◽  
Jen-Wei Hsieh ◽  
Po-Chun Huang
Keyword(s):  
Database Systems ◽  
Block Based ◽  
Embedded Database

scholarly journals Embedded Internet of Things Applications of SQLite Based on WinCE Mobile Terminal

2020 ◽  
Author(s):  
Yuanhui Yu
Keyword(s):  
Embedded Systems ◽  
Mobile Terminal ◽  
Database Systems ◽  
Embedded Operating System ◽  
Embedded Internet ◽  
Multiple Interfaces ◽  
Application Data ◽  
Sqlite Database ◽  
Embedded Applications ◽  
Embedded Database

Abstract As we all know, embedded systems are becoming more and more widely used. All devices with digital interfaces, such as watches, microwave ovens, video recorders, automobiles, etc., use embedded systems, but most embedded systems are implemented by a single embedded application program to achieve the entire control logic.At present, embedded applications on the WinCE platform are extending towards microservices and miniaturization. More embedded device application data requires small, embedded database systems to organize, store, and manage. The embedded database SQLite has many advantages such as zero-configuration, lightweight, multiple interfaces, easy portability, readable source code, and open source. It is currently widely used in the WinCE embedded operating system. This article discusses the technical characteristics of the SQLite database in detail, SQLite data manipulation, SQLite transplantation under the WinCE platform, and finally implements SQLite data management on WinCE mobile terminal based on MFC programming.

Application of Improved B+-Trees Algorithm in Embedded Database

2013 ◽  
Vol 655-657 ◽  
pp. 1779-1782
Author(s):  
Jian Pin Mao ◽  
Cai Ping Liu ◽  
Jian Xu Mao
Keyword(s):  
Execution Time ◽  
Database Systems ◽  
Database System ◽  
Experimental Results ◽  
Data Organization ◽  
High Efficient ◽  
B Trees ◽  
Berkeley Db ◽  
Embedded Database

B+-trees algorithm is a high efficient and common-used data organization algorithm in database system. But B+-trees algorithm has a disadvantage of low storage utilization. This disadvantage has a bad effect especially on embedded database systems, which have limit storage. To overcome this drawback, this paper presents an improved B+-trees algorithm, and applies it to an embedded database-Berkeley DB. Experimental results show that the improved B+-trees algorithm can attain higher storage utilization at the expense of more execution time than the conventional B+-trees algorithm.

scholarly journals Embedded Internet of Things Applications of SQLite Based on WinCE Mobile Terminal

2020 ◽  
Author(s):  
Yuanhui Yu
Keyword(s):  
Mobile Terminal ◽  
Database Systems ◽  
Embedded Operating System ◽  
Data Manipulation ◽  
Embedded Internet ◽  
Multiple Interfaces ◽  
Application Data ◽  
Sqlite Database ◽  
Embedded Applications ◽  
Embedded Database

Abstract At present, embedded applications on the WinCE platform are extending towards microservices and miniaturization. More embedded device application data requires small, embedded database systems to organize, store, and manage. The embedded database SQLite has many advantages such as zero-configuration, lightweight, multiple interfaces, easy portability, readable source code, and open source. It is currently widely used in the WinCE embedded operating system. This article discusses the technical characteristics of the SQLite database in detail, SQLite data manipulation, SQLite transplantation under the WinCE platform, and finally implements SQLite data management on WinCE mobile terminal based on MFC programming.

scholarly journals Faster & strong: string dictionary compression using sampling and fast vectorized decompression

2020 ◽  
Vol 29 (6) ◽  
pp. 1263-1285
Author(s):  
Robert Lasch ◽  
Ismail Oukid ◽  
Roman Dementiev ◽  
Norman May ◽  
Suleyman S. Demirsoy ◽  
...  
Keyword(s):  
Experimental Evaluation ◽  
Database Systems ◽  
Random String ◽  
Database Applications ◽  
Access Method ◽  
Compression Algorithms ◽  
Memory Footprint ◽  
Alternative Version ◽  
Speed Up ◽  
Block Based

AbstractString dictionaries constitute a large portion of the memory footprint of database applications. While strong string dictionary compression algorithms exist, these come with impractical access and compression times. Therefore, lightweight algorithms such as front coding (PFC) are favored in practice. This paper endeavors to make strong string dictionary compression practical. We focus on Re-Pair Front Coding (RPFC), a grammar-based compression algorithm, since it consistently offers better compression ratios than other algorithms in the literature. To accelerate compression times, we propose block-based RPFC (BRPFC) which consists in independently compressing small blocks of the dictionary. For further accelerated compression times especially on large string dictionaries, we also propose an alternative version of BRPFC that uses sampling to speed up compression. Moreover, to accelerate access times, we devise a vectorized access method, using $$\hbox {Intel}^{\circledR }$$ Intel ®  Advanced Vector Extensions 512 ($$\hbox {Intel}^{\circledR }$$ Intel ®  AVX-512). Our experimental evaluation shows that sampled BRPFC offers compression times up to 190 $$\times $$ × faster than RPFC, and random string lookups 2.3 $$\times $$ × faster than RPFC on average. These results move our modified RPFC into a practical range for use in database systems because the overhead of Re-Pair-based compression for access times can be reduced by 2 $$\times $$ × .

Intelligent Processing of Loosely Structured Documents as a Strategy for Organizing Electronic Health Care Records

1993 ◽  
Vol 32 (04) ◽  
pp. 265-268 ◽  
Author(s):  
D. J. Essin
Keyword(s):  
Health Care ◽  
Health Care Organization ◽  
Database Systems ◽  
Relevant Information ◽  
Full Potential ◽  
Care Organization ◽  
Intelligent Processing ◽  
Data Interchange ◽  
Structured Documents ◽  
Health Care Records

AbstractLoosely structured documents can capture more relevant information about medical events than is possible using today’s popular databases. In order to realize the full potential of this increased information content, techniques will be required that go beyond the static mapping of stored data into a single, rigid data model. Through intelligent processing, loosely structured documents can become a rich source of detailed data about actual events that can support the wide variety of applications needed to run a health-care organization, document medical care or conduct research. Abstraction and indirection are the means by which dynamic data models and intelligent processing are introduced into database systems. A system designed around loosely structured documents can evolve gracefully while preserving the integrity of the stored data. The ability to identify and locate the information contained within documents offers new opportunities to exchange data that can replace more rigid standards of data interchange.

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