FDMFP: Mining Frequency Paths in Distributed RFID System

Radio Frequency Identification (RFID) technology is fast becoming an important tool for tracking commodities in supply chain management applications. The movement of commodities through the supply chain forms a gigantic workflow that can be mined for the discovery of moving trends that in turn can be valuable in understanding and optimizing business processes. There have been some methods dealing with mining frequency paths in single site. But the path data collected by RFID systems are usually distributed in different sites. The current mining methods are not created for mining frequency paths in distributed systems. In this paper, we propose a method called FDMFP to mine frequency paths in distributed RFID systems. The method uses current frequency paths mining algorithm to mine local frequency paths in each site, then save the results in path lexicographic trees. The sites send these trees to polling sites, and polling sites merge these trees. After first pruning, there will be semi global frequency paths in polling sites. Then by collecting true support from each site, the polling sites will update true support for these paths and by second pruning, method will find global frequency paths. The experiments in this paper show that it outperforms using frequency paths mining algorithm after centralizing data in center site obviously and scales over LAN with huge amount of data.