An HBase-Based Optimization Model for Distributed Medical Data Storage and Retrieval
In medical services, the amount of data generated by medical devices is increasing explosively, and access to medical data is also put forward with higher requirements. Although HBase-based medical data storage solutions exist, they cannot meet the needs of fast locating and diversified access to me...
| Main Authors: | , , , , , , |
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| Format: | Article |
| Language: | English |
| Published: |
MDPI AG
2023-02-01
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| Series: | Electronics |
| Subjects: | |
| Online Access: | https://www.mdpi.com/2079-9292/12/4/987 |
| _version_ | 1797621273474367488 |
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| author | Chengzhang Zhu Zixi Liu Beiji Zou Yalong Xiao Meng Zeng Han Wang Ziang Fan |
| author_facet | Chengzhang Zhu Zixi Liu Beiji Zou Yalong Xiao Meng Zeng Han Wang Ziang Fan |
| author_sort | Chengzhang Zhu |
| collection | DOAJ |
| description | In medical services, the amount of data generated by medical devices is increasing explosively, and access to medical data is also put forward with higher requirements. Although HBase-based medical data storage solutions exist, they cannot meet the needs of fast locating and diversified access to medical data. In order to improve the retrieval speed, the recognition model S-TCR and the dynamic management algorithm SL-TCR, based on the behavior characteristics of access, were proposed to identify the frequently accessed hot data and dynamically manage the data storage medium as to maximize the system access performance. In order to improve the search performance of keys, an optimized secondary index strategy was proposed to reduce I/O overhead and optimize the search performance of non-primary key indexes. Comparative experiments were conducted on real medical data sets. The experimental results show that the optimized retrieval model can meet the needs of hot data access and diversified medical data retrieval. |
| first_indexed | 2024-03-11T08:53:30Z |
| format | Article |
| id | doaj.art-13f94be6a64e481d91a4927312d0e705 |
| institution | Directory Open Access Journal |
| issn | 2079-9292 |
| language | English |
| last_indexed | 2024-03-11T08:53:30Z |
| publishDate | 2023-02-01 |
| publisher | MDPI AG |
| record_format | Article |
| series | Electronics |
| spelling | doaj.art-13f94be6a64e481d91a4927312d0e7052023-11-16T20:13:16ZengMDPI AGElectronics2079-92922023-02-0112498710.3390/electronics12040987An HBase-Based Optimization Model for Distributed Medical Data Storage and RetrievalChengzhang Zhu0Zixi Liu1Beiji Zou2Yalong Xiao3Meng Zeng4Han Wang5Ziang Fan6Department of Computer Science, Central South University, Changsha 410083, ChinaDepartment of Computer Science, Central South University, Changsha 410083, ChinaDepartment of Computer Science, Central South University, Changsha 410083, ChinaDepartment of Computer Science, Central South University, Changsha 410083, ChinaDepartment of Computer Science, Central South University, Changsha 410083, ChinaDepartment of Computer Science, Central South University, Changsha 410083, ChinaDepartment of Literature and Journalism, Central South University, Changsha 410083, ChinaIn medical services, the amount of data generated by medical devices is increasing explosively, and access to medical data is also put forward with higher requirements. Although HBase-based medical data storage solutions exist, they cannot meet the needs of fast locating and diversified access to medical data. In order to improve the retrieval speed, the recognition model S-TCR and the dynamic management algorithm SL-TCR, based on the behavior characteristics of access, were proposed to identify the frequently accessed hot data and dynamically manage the data storage medium as to maximize the system access performance. In order to improve the search performance of keys, an optimized secondary index strategy was proposed to reduce I/O overhead and optimize the search performance of non-primary key indexes. Comparative experiments were conducted on real medical data sets. The experimental results show that the optimized retrieval model can meet the needs of hot data access and diversified medical data retrieval.https://www.mdpi.com/2079-9292/12/4/987big medical dataHBaseretrieval optimizationhot datasecondary index |
| spellingShingle | Chengzhang Zhu Zixi Liu Beiji Zou Yalong Xiao Meng Zeng Han Wang Ziang Fan An HBase-Based Optimization Model for Distributed Medical Data Storage and Retrieval Electronics big medical data HBase retrieval optimization hot data secondary index |
| title | An HBase-Based Optimization Model for Distributed Medical Data Storage and Retrieval |
| title_full | An HBase-Based Optimization Model for Distributed Medical Data Storage and Retrieval |
| title_fullStr | An HBase-Based Optimization Model for Distributed Medical Data Storage and Retrieval |
| title_full_unstemmed | An HBase-Based Optimization Model for Distributed Medical Data Storage and Retrieval |
| title_short | An HBase-Based Optimization Model for Distributed Medical Data Storage and Retrieval |
| title_sort | hbase based optimization model for distributed medical data storage and retrieval |
| topic | big medical data HBase retrieval optimization hot data secondary index |
| url | https://www.mdpi.com/2079-9292/12/4/987 |
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