Smart energy meter error big data security storage device and method based on fountain code

Abstract

A device and method for safely storing error big data of smart electric energy meters based on fountain codes, the device includes a smart electric energy meter self-service error calibration device connected in sequence, an HDFS client, and a Hadoop big data storage platform; the self-service error of the intelligent electric energy meter The calibration device is used to collect the measured smart energy meter data; the HDFS client is used to preprocess the collected smart energy meter data, and encode and decode the preprocessed data; the Hadoop big data storage platform uses For the distributed storage of large error data of smart electric energy meters, the technical effect of the present invention is: improving storage efficiency; improving storage space utilization; solving the traditional problem of data loss caused by DataNode failure; ensuring user data security Privacy protection.

Description

technical field [0001] The invention relates to the technical field of energy metering and marketing big data storage, and belongs to the application field of information technology such as distributed computing and information security, and specifically relates to a fountain code-based smart energy meter error big data safe storage device and method. Background technique [0002] In recent years, with the large-scale installation and application of smart energy meters, the data on the power user side has grown exponentially, and the storage of massive data has become more and more important. The traditional power data storage system based on large relational databases such as Oracle has the disadvantages of slow analysis speed, poor scalability and reliability, and it is difficult to adapt to the demand for data storage and analysis of power big data in the smart grid era. where the bottleneck is. [0003] HDFS (Hadoop Distributed File System) is the basis of cloud computi...

AI Technical Summary

Problems solved by technology

However, such schemes usually have low data recovery and high complexity. In addition, the typical configuration of HDFS requires three copies of each file block, and the space utilization rate is only 33%. On the other hand, massive power The data is managed by the cloud server provided by the third-party resource platform, and the user eventually loses control over the data. The security of power data information and the protection of user privacy depend on the cloud service provider

Although cloud service providers can provide more reliable data backup and data recovery capabilities, it cannot be ruled out that due to their own interests and interference from external factors, cloud service providers may leak, hide, or lose data stored in the cloud by users or be blocked. Malicious tampering, etc.

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