COMPARATIVE ANALYSIS OF TRADITIONAL RFID TAG ANTI-COLLISION TECHNIQUES FOR IOT APPLICATIONS

Umelo N. H.; Eze U. J.; Eleje N.E.

Authors

Umelo N. H. Wireless and Photonics Network Centre of Excellence (WiPNET), UPM, Malaysia, Department of Computer Engineering, Akanu Ibiam Federal Polytechnic Unwana, Ebonyi state. Nigeria, Department of Computer Engineering, Madonna University, Akpugo Campus, Enugu state, Nigeria
Eze U. J. Department of Computer Engineering, Madonna University, Akpugo Campus, Enugu state, Nigeria
Eleje N.E. Department of Electrical Electronics Engineering, Madonna University, Akpugo Campus, Enugu state, Nigeria

Keywords:

IoT; RFID; Tag anti-collision protocol; Probabilistic method; Deterministic method; Time slot; Tag identification rate

Abstract

Radio Frequency Identification (RFID) is seen as inevitable especially within the sensing layer of IoT architecture. RFID is important because it communicates wirelessly and numerous tags can be identified at same time. Besides, low cost of passive RFID tags makes the tagging and connectivity of things around us realizable. The tag collision problem (TCP) of RFID systems have received much research attention for small-scale tag deployments. However, the overcrowded nature of RFID tags in IoT puts a strong doubt, the ability of existing RFID tag anti-collision methods to effectively tackle TCP. This paper examines traditional methods (the probabilistic and deterministic methods) used in developing the existing RFID tag anti-collision protocol. Their pros and cons were explored. Both methods were implemented as M-files in MATLAB while simulation analysis were performed with varying tag density. RFID tags’ unique RN16 were simulated using 16-bit random numbers generated in MATLAB and under overcrowded environment of minimum 100 tags and maximum 1000 tags. The 1000 tags represents IoT scenario. Results of a Monte-Carlo simulation show a tag identification rate (TIR) of 0.98 in IoT for ALOHA-based (probabilistic) method and a tag identification rate of 0.90 in IoT for Tree-based (deterministic) method. Simulation result also shows ALOHA-based method uses less number of time slots (identification time) of 3200 than 4400 of Tree-based method. Since access to the communication channel is represented in times slots, the simulation results imply that ALOHA method takes less time to identify tags.

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COMPARATIVE ANALYSIS OF TRADITIONAL RFID TAG ANTI-COLLISION TECHNIQUES FOR IOT APPLICATIONS

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