Distributed open environment for data retrieval based on pattern recognition techniques
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- 作者：A. Pereira ; J. Vega ; R. Castro ; A. Portas
- 关键词：Pattern recognition ; Embedded database ; Embedded web server
- 刊名：Fusion Engineering and Design
- 出版年：2010
- 出版时间：July 2010
- 年：2010
- 卷：85
- 期：3-4
- 页码：595-597
- 全文大小：302 K
文摘
Pattern recognition methods for data retrieval have been applied to fusion databases for the localization and extraction of similar waveforms within temporal evolution signals. In order to standardize the use of these methods, a distributed open environment has been designed. It is based on a client/server architecture that supports distribution, interoperability and portability between heterogeneous platforms. The server part is a single desktop application based on J2EE (Java 2 Enterprise Edition), which provides a mature standard framework and a modular architecture. It can handle transactions and concurrency of components that are deployed on JETTY, an embedded web container within the Java server application for providing HTTP services. The data management is based on Apache DERBY, a relational database engine also embedded on the same Java based solution. This encapsulation allows hiding of unnecessary details about the installation, distribution, and configuration of all these components but with the flexibility to create and allocate many databases on different servers. The DERBY network module increases the scope of the installed database engine by providing traditional Java database network connections (JDBC-TCP/IP). This avoids scattering several database engines (a unique embedded engine defines the rules for accessing the distributed data). Java thin clients (Java 5 or above is the unique requirement) can be executed in the same computer than the server program (for example a desktop computer) but also server and client software can be distributed in a remote participation environment (wide area networks). The thin client provides graphic user interface to look for patterns (entire waveforms or specific structural forms) and display the most similar ones. This is obtained with HTTP requests and by generating dynamic content (servlets) in response to these client requests.