面向医疗信息管理系统的云存储技术研究与实现

发布时间：2019-01-20 17:35

【摘要】：我国目前的医疗卫生行业不断的提高和完善，随着各地各级医疗机构如医院、卫生院、社区卫生服务中心和诊所的医疗卫生机构相应建立，参加医保的民众不断增加，对各种疾病的研究深入，我国的医疗信息已经形成了相当海量的数据；加之各医院的病历信息、病人信息的大同小异，各地区实现和完善卫生部相关信息系统的不尽相同，不仅对病人的就诊、转诊带来不便，分散的病历对患者疾病的诊疗过程、用药等情况缺乏连续性记载，也不利于治疗，而且不尽相同的医疗信息影响国家对重大病例的管理和监控。有效而集中的数据，在如此海量信息的处理过程中起着重要作用，为此本文提出了医疗信息云存储。云存储是在云计算概念上延伸和发展出来的一个新的概念，继承了云计算的虚拟化、高可靠性、高可延伸性和廉价等特性，搭建一个云存储平台，可以有效利用医疗资源和共享存储信息。本文使用Hadoop、Hive、MongoDB等技术作为基础存储系统，对开发了一个面向医疗信息的云存储系统。 Hadoop是目前最为热门的开源分布式系统框架，允许用户简单部署Hadoop集群开发MapReduce应用，，并可以将Hive子项目作为数据任务处理。Hadoop项目的核心子项目HDFS，是分布式计算中数据存储管理的基础，具有节点监控日志管理、基础数据一致性管理和集群负载平衡等功能。MongoDB是一个基于分布式文件存储的NoSQL数据库，能够提供高效的数据访问和检索功能，并提供可扩展的数据处理能力，使数据具有一定的数据结构却不需要考虑数据模式问题，可以方便地进行数据分片处理和负载均衡。融合MongoDB存储和Hive处理是本系统最关键的模块，通过使用MongoDB作为数据输入，由Hive作为数据处理必须实现数据的输入输出、序列化反序列化等功能。在使用Hadoop和MongoDB作为底层存储的基础上，本文还介绍Spring Restful开发医疗信息数据访问层，将数据存储和各级医疗机构本地应用分离，并提供开放接口和安全认证，将数据访问和安全认证交由本地应用的业务流程处理。该系统将分成五个层次，分别是Hive处理数据层、MongoDB和HDFS数据存储层、Restful服务数据访问层、Nginx访问控制层和各级医疗信息系统应用层。
[Abstract]:At present, the medical and health industry in our country has been continuously improved and improved. With the corresponding establishment of medical and health institutions at various levels, such as hospitals, health centers, community health service centers and clinics, the number of people participating in medical insurance has been increasing. Deep research on various diseases, China's medical information has formed a considerable amount of data; In addition, the medical record information of each hospital is much the same as that of the patient, and the different regions realize and perfect the relevant information system of the Ministry of Health, which not only brings inconvenience to the patient's visit, but also brings inconvenience to the patient's referral, and the scattered medical record is the diagnosis and treatment process of the patient's disease. The lack of continuous records of drug use is not conducive to treatment, and different medical information affects the management and monitoring of major cases. Effective and centralized data play an important role in the process of processing such a large amount of information, so this paper proposes a medical information cloud storage. Cloud storage is a new concept that extends and develops in cloud computing concept. It inherits the virtualization, high reliability, high extensibility and low cost of cloud computing, and builds a cloud storage platform. It can effectively utilize medical resources and share storage information. In this paper, a cloud storage system for medical information is developed using Hadoop,Hive,MongoDB and other technologies as the basic storage system. Hadoop is the most popular open source distributed system framework, allowing users to simply deploy Hadoop clusters to develop MapReduce applications, and to treat Hive subprojects as data tasks. HDFS, is the core subproject of the Hadoop project MongoDB is a NoSQL database based on distributed file storage, which has the functions of node monitoring log management, basic data consistency management and cluster load balancing. It can provide efficient data access and retrieval function, and provide extensible data processing ability, so that the data have a certain data structure but do not need to consider the problem of data pattern, so it is convenient for data slicing and load balancing. Fusion of MongoDB storage and Hive processing is the most important module in this system. By using MongoDB as data input and Hive as data processing, the functions of data input and output, serialization and deserialization must be realized. On the basis of using Hadoop and MongoDB as the underlying storage, this paper also introduces the development of medical information data access layer by Spring Restful, which separates the data storage from the local application of medical institutions at all levels, and provides open interface and security authentication. Transfer data access and security authentication to local application business processes. The system will be divided into five layers: Hive processing data layer, MongoDB and HDFS data storage layer, Restful service data access layer, Nginx access control layer and medical information system application layer.
【学位授予单位】：华南理工大学
【学位级别】：硕士
【学位授予年份】：2012
【分类号】：TP311.52

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