A LIGHTWEIGHT TAG GROUPING ALGORITHM FOR ENHANCING RFID TAG ANTI-COLLISION MAC PROTOCOL
Abstract
Compared to previous automatic identification technologies (Auto-IDs), Radio Frequency Identification (RFID) has various benefits, such as wireless object recognition, the ability to identify many tags at once, and the ability to uniquely identify a certain product within the same item. RFID tags' signals frequently collide because they use the same communication channel to respond to queries from RFID readers. RFID anti-collision protocol is the attempt to resolve this collision and dynamic frame slotted ALOHA (DFSA) is the de-facto algorithm implemented in its medium access control (MAC) component. This collision becomes more likely with the widespread use of RFID, such as in Internet of Things (IoT) applications. Clustering technique is used in this research paper to group tags and reduce the likelihood of a collision. This paper uses a tag grouping principle that forces the reader to query a small number of tags (a tag cluster) at once, hence, minimizing the possibility of tags colliding. MATLAB was used to simulate and model a large-scale tag deployment. Simulation findings indicate that the clustering technique employed in this research, groups RFID tags uniformly, regardless of the number of clusters chosen. Through efficient tag grouping, the proposed approach shows promise in improving the current RFID tag anti-collision MAC protocol.
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KEYWORDS IoT, passive UHF RFID, DFSA, clustering, RFID tag anti-collision protocol.
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