• Title/Summary/Keyword: Embedded Relational DBMS

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Comparison research of the Spatial Indexing Methods for ORDBMS in Embedded Systems (임베디드 시스템의 객체 관계형 DBMS에 적합한 공간 인덱스 방법 비교 연구)

  • Lee, Min-Woo;Park, Soo-Hong
    • Journal of the Korean Association of Geographic Information Studies
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    • v.8 no.1
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    • pp.63-74
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    • 2005
  • The telematics device, which is a typical embedded system on the transportation or vehicle, requires the embedded spatial DBMS based on RTOS (Real Time Operating System) for processing the huge spatial data in real time. This spatial DBMS can be developed very easily by SQL3 functions of the ORDBMS such as UDT (user-defined type) and UDF (user-defined function). However, developing index suitable for the embedded spatial DBMS is very difficult. This is due to the fact that there is no built-in SQL3 functions to construct spatial indexes. In this study, we compare and analyze both Generalized Search Tree and Relational Indexing methods which are suggested as common ways of developing User-Defined Indexes nowadays. Two implementations of R-Tree based on each method were done and region query performance test results were evaluated for suggesting a suitable indexing method of an embedded spatial DBMS, especially for telematics devices.

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Design, Implementation, and Performance Evaluation of an Embedded RDBMS Miracle (Miracle 임베디드 RDBMS 설계, 구현 및 성능 평가)

  • Seo, Nam-Won;Kim, Keong-Yul;Kim, Su-Hee
    • Journal of the Korea Academia-Industrial cooperation Society
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    • v.12 no.7
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    • pp.3227-3235
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    • 2011
  • In this paper, a relational embedded DBMS was designed and a prototype 'Miracle' RDBMS (MDB) was developed. MDB is written in C and works on Unix, Linux and Windows platforms locally. It accesses database through SQL interfaces and API functions and uses $B^+$ tree index. It guarantees ACID in transactions and supports low concurrency control and processes SQL statements on a single table. To evaluate the performance of MDB on an ARM board EZ-S3C6410 and to compare the performance of MDB with that of SQLite, an experiment was carried out to estimate processing times for insertion, selection, update and deletion operations. The result shows that the average times for selections and insertions in MDB were 38.46% and 22.86% faster than those in SQLite, respectively, but the average times for updates and deletions in SQLite were 28.33% and 26.00% faster than MDB, respectively, This experiment shows that fetching data from database and sending data to database in MDB is faster than in SQLite, but $B^+$ tree index is implemented more effectively in SQlite than in MDB.

An Implementation of Dynamic Gesture Recognizer Based on WPS and Data Glove (WPS와 장갑 장치 기반의 동적 제스처 인식기의 구현)

  • Kim, Jung-Hyun;Roh, Yong-Wan;Hong, Kwang-Seok
    • The KIPS Transactions:PartB
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    • v.13B no.5 s.108
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    • pp.561-568
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    • 2006
  • WPS(Wearable Personal Station) for next generation PC can define as a core terminal of 'Ubiquitous Computing' that include information processing and network function and overcome spatial limitation in acquisition of new information. As a way to acquire significant dynamic gesture data of user from haptic devices, traditional gesture recognizer based on desktop-PC using wire communication module has several restrictions such as conditionality on space, complexity between transmission mediums(cable elements), limitation of motion and incommodiousness on use. Accordingly, in this paper, in order to overcome these problems, we implement hand gesture recognition system using fuzzy algorithm and neural network for Post PC(the embedded-ubiquitous environment using blue-tooth module and WPS). Also, we propose most efficient and reasonable hand gesture recognition interface for Post PC through evaluation and analysis of performance about each gesture recognition system. The proposed gesture recognition system consists of three modules: 1) gesture input module that processes motion of dynamic hand to input data 2) Relational Database Management System(hereafter, RDBMS) module to segment significant gestures from input data and 3) 2 each different recognition modulo: fuzzy max-min and neural network recognition module to recognize significant gesture of continuous / dynamic gestures. Experimental result shows the average recognition rate of 98.8% in fuzzy min-nin module and 96.7% in neural network recognition module about significantly dynamic gestures.