Year of Publication

2011

Paper Type

Master's Thesis

College

College of Computing, Engineering & Construction

Degree Name

Master of Science in Computer and Information Sciences (MS)

Department

Computing

First Advisor

Zornitza Genova Prodanoff, Ph.D.

Second Advisor

Kelmeth E. Martin, Ph.D.

Third Advisor

Susan Vasana, Ph.D.

Abstract

Radio Frequency Identification (RFID) is a powerful emerging technology widely used for asset tracking, supply chain management, animal identification, military applications, payment systems, and access control. Over the years, RFID has emerged as a popular technology in various industries because of its ability to track moving objects. As RFID is becoming less expensive and more robust, many companies and vendors are developing tags to track objects. Multiple vendors manufacture RFID tags worldwide. Therefore, it is quite possible that they manufacture tags with the same identification code (ID) as vendor ID code data sets may not be synchronized or may be subject to tag id errors. Due to this drawback, there is the possibility that non-unique tags exist along with unique tags in the same RFID system. As existing implementations optimize the performance of RFID systems performance based on the assumption of unique tags, it is important to study the effect of non-unique tags on RFID systems.

This thesis focuses on a formal analysis of the Basic Frame Slotted ALOHA (BFSA) Muting RFID system with non-unique tags. An RFID network was modeled with OPNET Modeler 14.5. An evaluation model was built to measure the total census delay, optimal frame size, and network throughput for an RFID network based on a BFSA protocol for non-unique tags and support for muting. The evaluation results are in agreement with results obtained from the evaluation of a similar model for unique tags [Kang08]. Comparing total census delay for unique and non-unique tags for variable frame sizes showed an increase in total census delay with an increase in the number of tags. Comparing minimum network throughput, mean network throughput, and maximum network throughput for unique and non-unique tags for variable frame sizes showed a decrease in network throughput with an increase in the number of tags.

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