A novel hash-based file clustering scheme for efficient distributing, storing, and retrieving of large scale health records
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- Conference Proceeding
- Proceedings - 15th IEEE International Conference on Trust, Security and Privacy in Computing and Communications, 10th IEEE International Conference on Big Data Science and Engineering and 14th IEEE International Symposium on Parallel and Distributed Processing with Applications, IEEE TrustCom/BigDataSE/ISPA 2016, 2016, pp. 1485 - 1491
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|Cameraready_Dat_ISPA-16_HBFC-short Final Camera.pdf||Accepted Manuscript||657.15 kB|
|6184223A-D433-4F94-A5FB-5AFE00D12387 am.pdf||Accepted Manuscript Version||639.71 kB|
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© 2016 IEEE. Cloud computing has been adopted as an efficient computing infrastructure model for provisioning resources and providing services to users. Several distributed resource models such as Hadoop and parallel databases have been deployed in healthcare-related services to manage electronic health records (EHR). However, these models are inefficient for managing a large number of small files and hence they are not widely deployed in Healthcare Information Systems. This paper proposed a novel Hash-Based File Clustering Scheme (HBFC) to distribute, store and retrieve EHR efficiently in cloud environments. The HBFC possesses two distinctive features: it utilizes hashing to distribute files into clusters in a control way and it utilizes P2P structures for data management. HBFC scheme is demonstrated to be effective in handling big health data that comprises of a large number of small files in various formats. It allows users to retrieve and access data records efficiently. The initial implementation results demonstrate that the proposed scheme outperforms original P2P system in term of data lookup latency.
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