Joined Q-ary Tree Anti-Collision for Massive Tag Movement Distribution

Pupunwiwat, P. and Stantic, B.

Radio-Frequency Identification (RFID) systems consist of tags and networked electromagnetic readers. Despite the emergence of RFID technology, the prob- lem of identifying multiple tags, due to the Collisions is still a major problem. The problem can be solved by using anti-collision methods such as ALOHA-based approaches and Tree-based approaches. ALOHA-based approaches suffer from tag starvation, which causes that not all tags can be identified. The tree-based approaches suffer from too long identification delay caused by lengthy queries during identification process. In this paper, we propose a tree-based anti-collision method called “Joined Q-ary Tree”, which adaptively adjusts tree branches according to tag movement behavior and number of tags within an interrogation zone. In this empirical study, we demonstrate that the proposed method is suitable for numerous scenarios. It requires less queries issued per complete identification than existing approaches while en- suring identification of all tags within the interrogation zone.

Cite as: Pupunwiwat, P. and Stantic, B. (2010). Joined Q-ary Tree Anti-Collision for Massive Tag Movement Distribution. In Proc. 33rd Australasian Computer Science Conference (ACSC 2010) Brisbane, Australia. CRPIT, 102. Mans, B. and Reynolds, M. Eds., ACS. 99-108

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