Study On Big Data Cluster Analysis Method And Technology Of Internet Of Things

With the rapid development of Internet of Things technologies,a lot of application areas based on Internet of Things arise,such as GPS-based internet of vehicles,RFID-based Internet of things logistics systems.These applications have brought great convenience to people's lives,and also produced a large amount of data."Internet of things" and "big data" have become a pair of closely related technical application fields.The value model between Internet of Things and big data can help managers make the right decisions for the development trend of enterprises and improve enterprise efficiency.Therefore,it is necessary to investigate the big data analysis methods and techniques of Internet of Things..Facing the processing technical challenge of large data of Internet of Things,we start from the analysis of complex event relation and processing technology to study the RFID analysis method of large data of Internet of Things.After introducing the concept of complex event relations,the big data processing of the Internet of Things is transformed into the extraction and analysis of the complex relational model,so as to simplify the big data processing complexity of Internet of things.The improvement of the traditional K-means algorithm made it suitable for the RFID analysis method of large data of Internet of Things.Based on the Hadoop cluster Platform,the K-means clustering algorithm is implemented.Based on the traditional clustering algorithm,the center point selection technology which is suitable for RFID data clustering of Internet of Things is selected to improve the clustering efficiency.We design and implement a prototype system of the RFID clustering analysis of Internet of Things,and the feasibility of the above work.