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A Data Security Storage Method for IoT Under Hadoop Cloud Computing Platform

机译:Hadoop云计算平台下物联网数据安全存储方法

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摘要

Taking the big data storage for internet of things (IoT) in the cloud computing environment as the research object, the paper mainly introduces two typical distributed storage systems in the cloud computing environment, namely Google's GFS and Hadoop's HDFS. The data storage technology is specially analyzed. The prior art was evaluated in terms of scalability and latency (how to support the storage of large amounts of small files), fault tolerance (data recovery in the event of data loss), and real-time performance of mass data storage. On this basis, the system architecture of the distributed file system is proposed. Aiming at the problem of IoT data security storage in cloud computing, an enhanced ant colony algorithm for data storage is proposed. The algorithm considers the shortest completion time and load balancing of data storage. At the same time, it refers to various improvements of ant colony algorithm in recent years, and innovatively assigns a task on a virtual machine as an ant search object. Experiments have shown that this method is effective.
机译:本文以云计算环境下的物联网大数据存储为研究对象,主要介绍了云计算环境下的两种典型的分布式存储系统,分别是Google的GFS和Hadoop的HDFS。专门分析了数据存储技术。在可伸缩性和等待时间(如何支持大量小文件的存储),容错(在数据丢失的情况下恢复数据)和大容量数据存储的实时性能方面评估了现有技术。在此基础上,提出了分布式文件系统的系统架构。针对云计算中的物联网数据安全存储问题,提出了一种用于数据存储的增强蚁群算法。该算法考虑了最短的完成时间和数据存储的负载平衡。同时,它引用了近年来蚁群算法的各种改进,并在虚拟机上创新地将任务分配为蚂蚁搜索对象。实验表明,该方法是有效的。

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