Reader Anti-Collision in Dense RFID Network: An Overview, Taxonomy, and Evaluation - Brossura

Golsorkhtabaramiri, Mehdi; Hassan Ahmed, Omed; Khodkavandi, Sepideh; Rezaie, Hadiseh; IssazadehKojidi, Neda; Hosseinzadeh, Mehdi

Brossura

ISBN 13: 9798410225472

Casa editrice: Independently published, 2022

Riassunto

Nowadays, RFID networks are being used extensively in many fields such as automation, tracking, and the Internet of Things (IoT). The reason is related to the significant advantages that lie in making use of these systems. In the many different services of RFID networks, many mobile and fixed readers or RFID reader enhanced devices are used alongside each other. In these situations, there may be many readers and tags in the interference range of one reader, leading to reader collision in RFID systems. If RFID readers are densely used, they cannot read all the tags efficiently. Thus, reader collisions in dense reader environments will undoubtedly cause several difficulties in RFID system operations. Because of the readers’ simultaneous activities in the same frequencies, these environments are challenging. The need for RFID applications with several readers will make the research in anti-collision algorithms more critical and essential. In this book, solutions for avoiding and reducing reader collisions are reviewed and compared based on their efficiency to help proceed in studies related to anti-collision solutions. The combination of access schemes, matching the proposed methods with regulations and standards of RFID systems, and correct resource management should all be considered in presenting a good strategy for improving the efficiency of RFID systems. This book will be a helpful review and survey for researchers and graduate students in information technology and computer science and an excellent guide for researchers and developers in the IoT and automation industry.
Authors' Affiliations:

• Mehdi Golsorkhtabaramiri
  • Department of Computer Engineering, Babol Branch, Islamic Azad University, Babol, Iran
• Omed Hassan Ahmed
  • Department of Information Technology, University of Human Development, Sulaymaniyah, Iraq
• Sepideh khodkavandi
  • Department of Computer Engineering, Babol Branch, Islamic Azad University, Babol, Iran
• Hadiseh Rezaie
  • Department of Computer Engineering, Babol Branch, Islamic Azad University, Babol, Iran
• Neda IssazadehKojidi
  • Department of Computer Engineering, Babol Branch, Islamic Azad University, Babol, Iran
• Mehdi Hosseinzadeh
  • Mental Health Research Center, Psychosocial Health Research Institute, Iran University of Medical Sciences, Tehran, Iran

Dettagli dell'edizione

• Editore: Independently published
• Data di pubblicazione: 2022
• Lingua: Inglese
• ISBN 13: 9798410225472
• Rilegatura: Copertina flessibile
• Numero di pagine: 90
• Contatto del produttore: non disponibile
• Persona responsabile: non disponibile