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

机译:Hadoop云计算平台下的IOT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:在云计算环境中为云计算环境中的物联网(物联网)进行大数据存储,主要引入云计算环境中的两个典型的分布式存储系统,即Google的GFS和Hadoop的HDF。数据存储技术经过特殊分析。在可扩展性和延迟(如何支持大量小文件的存储)方面评估现有技术,容错(在数据丢失的情况下数据恢复),以及质量数据存储的实时性能。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。该算法考虑了数据存储的最短完成时间和负载平衡。与此同时,它是指近年来蚁群算法的各种改进,并且创新地将虚拟机的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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