A Survey of RFID Readers Anticollision Protocols

Mbacké, Abdoul Aziz; Mitton, Nathalie; Rivano, Hervé

doi:10.1109/jrfid.2018.2828094

Cited by 33 publications

(12 citation statements)

References 31 publications

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“…From the development history of the Internet of Things, from the initial simple identification of objects to the application of sensors to the integration of radio frequency identification [17], nanotechnology [18], intelligent embedded technology [19], the technology and connotation of the Internet of Things is constantly expanded. The essence is to allow the items on the earth to transmit information spontaneously.…”

Section: System Model a Internet Of Thingsmentioning

confidence: 99%

An Intelligent Supply Chain Information Collaboration Model Based on Internet of Things and Big Data

Jiang

2019

IEEE Access

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Supply chain information collaboration refers to a relationship in which supply chain partners organically integrate, coordinate, and develop resources, business processes, and organizations in order to achieve common goals. The goal is to create and coordinate efforts in all aspects of the supply chain. The overall value of the supply chain is greater than the simple sum of the value of each link, thereby improving the competitiveness of the entire supply chain. However, information sharing in supply chain information collaboration has always had problems such as information distortion, information loss, and information delay. The effective coordination of information has become a difficult point in supply chain management. This paper mainly uses the Internet of Things and big data technology to build a simulation model of the supply chain bullwhip effect based on the mathematical model of the bullwhip effect and uses the simulation method to simulate and study the key factors in the model. The image of the simulation results objectively clarifies the value of information collaboration in the supply chain. INDEX TERMS Supply chain, information collaboration model, Internet of Things, big data. I. INTRODUCTION

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Section: System Model a Internet Of Thingsmentioning

confidence: 99%

An Intelligent Supply Chain Information Collaboration Model Based on Internet of Things and Big Data

Jiang

2019

IEEE Access

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“…In practical deployment scenarios, there may exist contention and collision issues in two cases: (1) between tags (inter-tag case); (2) with other non-carrier WiFi signals. There have been a number of proposals to resolve contention between multiple RFID tags [22]- [25]. Some attempts have also been made for ambient backscatter communication [2], [26].…”

Section: Repetition Adaptation Algorithmmentioning

confidence: 99%

Adaptive Transmission Repetition and Combining in Bistatic WiFi Backscatter Communications

Hwang

Yun

2020

IEEE Access

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Extracting data bits from bistatic-backscattered WiFi signals by threshold-based decoding is challenging due to severe fluctuation of OFDM signals. We propose adaptive transmission repetition to combat this problem. The key idea is to let a backscatter transmitter repeat transmissions and a receiver combines those so that signal fluctuation is filtered out due to its time-changing patterns, as observed in our testbed experiments, thus reducing bit error rate. However, excessive transmission repetitions lead to the waste of channel time, thus we propose an algorithm to adapt the number of repetitions so as to maximize the effective throughput in the present communication condition. We demonstrate via testbed experiments that the proposed algorithm adapts well to various communication conditions and achieves near-best throughput performance. INDEX TERMS Ambient backscatter communication, WiFi backscatter, ultralow-power communication, backscatter tag, IoT.

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“…In case the medium is occupied, the readers can switch to another channel and perform their listening. Several other proposals can be found as detailed in [17].…”

Section: Related Workmentioning

confidence: 99%

DACAR: Distributed & Adaptable Crosslayer Anticollision and Routing Protocol for RFID

Mbacké

Mitton

Rivano

2018

Ad-Hoc, Mobile, and Wireless Networks

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In the midst of Internet of Things development, a first requirement was tracking and identification of those mentioned "things which could be done thanks to Radio Frequency Identification. However, since then, the development of RFID allowed a new range of applications among which is remote sensing of environmental values. While RFID can be seen as a more efficient solution than traditional Wireless Sensor Networks, two main issues remain: first reading collisions and second proficient data gathering solution. In this paper, we examine the implementation of two applications: for industrial IoT and for smart cities, respectively. Both applications, in regards to their requirements and configuration, challenge the operation of a RFID sensing solution combined with a dynamic wireless data gathering over multihops. They require the use of both mobile and fixed readers to cover the extent of deployment area and a quick retrieval of tag information. We propose a distributed crosslayer solution for improving the efficiency of the RFID system in terms of collision and throughput but also its proficiency in terms of tag information routing towards one or multiple sinks. Simulation results show that we can achieve high level of throughput while maintaining a low level of collision and a fairness of reader medium access above 95% in situations where readers can be fix and mobile, while tag information is routed with a data rate of ≈ 97% at worst and reliable delays for considered applications.

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A Survey of RFID Readers Anticollision Protocols

Cited by 33 publications

References 31 publications

An Intelligent Supply Chain Information Collaboration Model Based on Internet of Things and Big Data

An Intelligent Supply Chain Information Collaboration Model Based on Internet of Things and Big Data

Adaptive Transmission Repetition and Combining in Bistatic WiFi Backscatter Communications

DACAR: Distributed & Adaptable Crosslayer Anticollision and Routing Protocol for RFID

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