A Novel Hybrid Anticollision Algorithm for RFID System Based on Grouped Dynamic Framed Recognition and Binary Tree Recursive Process
Author(s) -
Jian Yang,
Yonghua Wang,
Qingling Cai,
Yiju Zhan
Publication year - 2015
Publication title -
international journal of distributed sensor networks
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.324
H-Index - 53
eISSN - 1550-1477
pISSN - 1550-1329
DOI - 10.1155/2015/641327
Subject(s) - computer science , aloha , tree (set theory) , collision , collision problem , process (computing) , throughput , identification (biology) , radio frequency identification , channel (broadcasting) , set (abstract data type) , algorithm , binary search algorithm , real time computing , wireless , search algorithm , computer network , computer security , telecommunications , mathematical analysis , botany , mathematics , biology , programming language , operating system
Recently, RFID technology has come into end-user applications for monitoring, tracking, and so forth. In RFID system, a reader identifies a set of tags over a shared wireless channel. When multiple tags communicate with the same reader simultaneously, all packages will be lost and no tag can be recognized, which is known as tag collision. Tag collision is a significantly important issue for fast tag identification. We firstly make a thorough analysis among a variety of traditional RFID anticollision algorithms. Then a novel hybrid anticollision algorithm called T-GDFSA is proposed. Tags are assigned to different groups based on the initial tag estimation and then experience several dynamic read frames for identification. When a collision occurs in current slot, a tree-based recursive process will be deployed immediately. T-GDFSA combines the advantages of ALOHA-based and tree-based together and acquires higher system throughput by reducing unnecessary idle and collision slots and lower communication complexity by decreasing the data transmitted, which makes it identify tags faster with less power consumption. Simulations show that the theoretical values match well the simulation results. Moreover, T-GDFSA also has a good tolerance for the inaccuracy of initial tag estimation and the length variation of tag's ID.
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