基于云计算和物联网的网络大数据技术研究

为了使网络大数据应用的范围更广,更大程度地提高网络数据存储与管理精度,减少网络数据处理与控制的时间,需要对网络大数据进行研究。当前的网络大数据研究方法多是采用Hadoop基础架构对网络大数据进行研究,在数据存储中没有设定具体的安全存储指标,无法得到数据安全存储指标权重,存在数据存储安全性能低,网络大数据研究精度偏差大等问题。为此,提出一种基于云计算和物联网的网络大数据研究方法。该方法首先利用分级网络编码对网络数据进行传输,以传输的数据为基础,采用CRC算法实现网络数据的计算,然后依据分组存储的方式将数据进行存储,最后利用分层逆序叠加定位法对网络数据进行高精度查询,由此完成对网络大数据的研究。实验结果表明,所提方法可以全面具体地对网络大数据进行研究,提高了数据处理精度和网络数据计算速度,增加了网络数据存储空间容量和查询效率,减少了网络数据运行时的丢失率,扩展了网络数据的运作范围,为后续网络大数据的研究提供了强有力的依据。

Big data based on cloud computing and Internet of things network technology research

In order to make the network data applications broader, more to improve the precision of the network data storage and management, reduce the time of the network data processing and control, need to study of network data. The current network data research method is to adopt more major Hadoop infrastructure of network data, the data is stored in the safe storage index is set, do not have access to data security storage index weight and the low data storage security performance, network problems such as big data research accuracy deviation. For this, put forward a kind of big data based on cloud computing and Internet of things network research methods. This method firstly using hierarchical network coding for network data transmission, based on the transmission of data, the calculation of CRC algorithm was adopted to realize network data, and then based on the data packet storage way for storage, the hierarchical reverse superposition method is used to analyse the network data precision query, thus completing the study of network data. The experimental results show that the proposed method can comprehensively and concretely study of network data, improves the precision of data processing and network data computing speed, increased the network data storage capacity and query efficiency, reduces the network data presented.according to the runtime, expanded the scope of the operation of network data, large data for subsequent network research provides a strong basis.