A Data-Filtering Approach for Large-Scale Integrated RFID and Sensor Networks

Radio-Frequency identification, referred as RFID, is a technology for storing and retrieving data remotely using radio-labeled tags. Tags are small objects, and can be pasted or incorporated into objects and products or even implanted in living organisms. In the last years, several researches have focused on how to take benefit from this technology to build performing rechargeable sensor networks. The fusion of both technologies can extend widely the network’s lifetime and improve it performances since radio communications are only performed between readers and not between sensor tags. However, the RFID sensor networks present some drawbacks due to the random deployment especially for large scale systems, which can disturb the system’s performances and cause issues such as data duplication, and medium access control (MAC) collisions. In this paper, we deal especially with the redundancy problem by proposing an algorithm that avoids a priori the transmission of duplicated data before sending it into the network. Our approach can be considered as proactive since it predicts duplication by planning a first network discovery phase. Our scheme showed good performances in terms of latency, packet delivery, and computational cost.