Dynamic Framed-Slot ALOHA Anti-Collision using Precise Tag Estimation Scheme

Abstract

Radio Frequency Identification (RFID) technology uses radio-frequency waves to automatically identify people or objects. Despite an emergence of RFID technology, multiple tag identification, where a reader identifies a multiple number of tags in a very short time, is still a major problem. This is known as Collision problem and can be solved by using anti-collision scheme. The current tree-based anti-collision approach suffers from long identification delay, while the ALOHA-Based approach suffers from tag starvation problem due to inaccurate Frame-size. In this paper, we propose a ``Precise Tag Estimation Scheme'' for a Dynamic Framed-Slot ALOHA (DFSA), which estimates precise number of tags around the reader. In this empirical study, we compare our approaches with the original tag estimation in DFSA. The results indicate that the various parameters used by ``Precise Tag Estimation Scheme'', including \textit{empty slots} variables and/or \textit{collision slots} variables, have an impact on system efficiency. Thus, the number of frames and slots used by DFSA can be minimised by adjusting correct variables.