Compressed Storage And Query Method Of RFID Data In The Internet Of Things

The technology of RFID(Radio Frequency Identification) has attracted attention of more and more people with the wide research of the Internet of things. RFID has been successfully applied in many fields at present,however there is little work on the storage and query of the massive RFID data.First of all, this paper does a lot studies of present research of storage and query of RFID data, and analyzes the advantages and disadvantages of them.And this paper presents a three-level RFID(Radio Frequency Identification) data compression model and its algorithm of data gathering.After that it presents a algorithm of RFID path coding,which adopts the improved Haffman Coding and is used to code the RFID compression path.The experiment results show the three-level storage model can effectively storage compression data, demonstrates the algorithm of data gathering has higher rate of data compression as well as lower time complexity.Furthermore,there are more and more RFID data generated every day with the widely used of the technology of the Internet of things,and the problem is how to acquire knowledge from the massive location data.This paper presents a method of cluster paths to solve the problem.In order to determine the neighbor statement,this paper defines a Location Model(LM),and computes the mutual relation of the locations by this model.In addition,this paper presents a new algorithm to compute the similarities of the RFID paths,and clusters the paths according to the similarities.The experiment results show that the RFID path cluster algorithm based on location neighbor can cluster similar paths better,and has higher accuracy as well as lower time complexity.Thirdly,this paper presents a query method based on the three-level RFID data compression model.The method will let every query mapped to the model by using extended SQL statements,and meet the needs of RFID data query.