FTSMAC: A Multi-Channel Hybrid Reader Collision Avoidance Protocol for RFID Network

Abstract

Due to the emergence of the Internet of Things, the need for effective identification and traceability has increased. Radio-frequency identification (RFID), a simple and cheap approach for gathering information, has therefore drawn the attention of research communities. However, this system suffers from problems caused by high density, such as collisions and duplication. Thus, the deployment of RFID is more effective in a dense environment where it may improve overage and delays. A wide range of solutions have been proposed; however, the majority of these are based on the application context. In this paper, we propose a general MAC layer protocol FTSMAC (Frequency Time Scheme MAC) in which the spectrum frequency is efficiently used by dividing the signal into different time slots via a messaging mechanism used by RFID readers. This limits the collisions in high-density RFID deployment that affect the performance of the system. Thus, our solution allows the communication system to converge to a stable state within a convenient time.

DMLAR: Distributed Machine Learning-Based Anti-Collision Algorithm for RFID Readers in the Internet of Things

“…FTSMAC [38] is a distributed hybrid protocol based on TDMA and FDMA. This algorithm makes it possible to create efficient frequency and time slot distribution schemes.…”

“…In order to collect the external information for the input (NbrRRI, NbrRTI and NbrINT) and output (RRI, RTI and INT) of the dataset, a notification system (Algorithm 1) is developed. At each simulation period, all readers in the network wait for Backoff [38]. The first reader to wake up Ri listens to the control channel CC during a period T in order to avoid collisions on this channel [38].…”

“…At each simulation period, all readers in the network wait for Backoff [38]. The first reader to wake up Ri listens to the control channel CC during a period T in order to avoid collisions on this channel [38]. Then, reader Ri broadcasts a MsgD within its data channel interference field equal to the control channel reading field.…”

“…In order to share datasets without collisions, we use an effective communication strategy after the collection phase. The reader Ri that wakes up first (Backoff = 0) [38] starts to broadcast the MsgM containing its dataset (Di). This message is received by the readers in the control channel reading field of Ri.…”

Machine Learning Enabled Food Contamination Detection Using RFID and Internet of Things System

“…[1][2][3][4][5][6][7]. Moreover, short-range IoT technologies such as RFID are considered to be last-mile solutions in many applications such as inventory management, supply chain tracking, healthcare, waste management, and so forth [8][9][10][11][12][13][14]. The UHF RFID technology provides sensing benefits due to its inherent capability of noticing impedance variations with respect to the permittivity of background environments [15][16][17][18][19].…”