A Hadoop Processing Method for Massive Sensor Network Data Based on Internet of Things

Based on the analysis of the architecture of the Internet of Things service platform and the key technologies of cloud computing, a massive sensing information processing scheme based on the Internet of Things service platform is proposed. The scheme first proposes a system architecture model that can satisfy the massive sensor information processing in an open platform environment, and designs multiple functional unit modules of the system. By combining these functional units, service configurability can be realized, facing thousands of services and Tenant. Then, Hadoop open source framework is used to realize the distributed computing of the system, which makes full use of the processing advantages of MapReduce computing model, HBase distributed database and HDFS distributed file system in Hadoop framework, and uses Oracle database as a supplement to realize the system high. Finally, the mass sensor information was deployed and tested. The effectiveness of the Hadoop processing method was verified by analyzing the results of MapReduce parallel computing experiments. The average cache hit rate is 93.1%, which has a high cache hit rate, greatly reduces MySQL database I/O, and improves system performance.