TDMA‐SDMA‐based RFID algorithm for fast detection and efficient collision avoidance

Saadi, Hadjer; Touhami, R.; Yagoub, M.C.E.

doi:10.1002/dac.3392

Cited by 6 publications

(3 citation statements)

References 42 publications

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“…The IoT transmits intelligent services over the network from the users' standpoints. Thus, it can track users' health status over the long or short term, offer navigation information and road conditions, detect and analyze air or water quality, and digitally link residential areas and workplaces [17], [18]. This paper utilizes IoT sensors and cameras to collect the internal data of GIS.…”

Section: B Internet Of Things (Iot) Technologymentioning

confidence: 99%

Exploration on Automatic Management of GIS Using TL-CNN and IoT

et al. 2022

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The research aims to effectively monitor the state of complex industrial equipment in real time, diagnose the internal Partial Discharge (PD) pattern of Gas Insulated Metal Enclosed Switchgear (GIS), implement effective health management, and change the traditional model optimization route of increasing training time in exchange for performance improvement. This paper studies the complex equipment-oriented Health Management System (HMS) based on Internet of Things (IoT) technology and Transfer Learning. Firstly, the principles of Transfer Learning and Deep Learning (DL) technology are introduced. Secondly, the requirements of GIS internal status recognition and management are studied. Furthermore, a GIS-oriented HMS based on Transfer Learning-optimized Convolutional Neural Networks (CNN) is proposed, and the training dataset is constructed. Finally, the proposed model is tested. The results show that the complex equipment-oriented HMS based on IoT technology, CNN, and Transfer Learning can detect the internal status of GIS in real time. Compared with the traditional DL algorithm and expert system, the proposed model has a shorter training time of only 16min, faster convergence speed, high testing recognition rate, and over 96% recognition rate. Compared with other mainstream algorithms, it has higher identification, the storage parameter volume is 408, and the storage space is 12.8MB. Moreover, the proposed Transfer Learning-optimized CNN model can accurately detect the status of GIS, identify abnormal statuses, and help prolong the service life of GIS. The proposed complex equipment-oriented HMS contributes to the intelligent manufacturing industry and provides a new direction for applying emerging Computer Technology in the intelligent industry.INDEX TERMS Internet of Things, convolutional neural network, GIS, status recognition, equipment health management. I. INTRODUCTIONChinese continuous industrialization has gradually entered the era of ''industry 4.0'', which helps to popularize industrial reform, thus affecting all walks of life through advanced technologies, such as Information Technology (IT). As a result, the manufacturing industry set off a new round of revolution towards intelligent manufacturing, and intelligent industrial equipment sees extensive application [1], [2]. In particular, Gas-Insulated Metal Closed Switchgear (GIS), [3] because of its unique advantages, such as small footprint, high reliability, and little electromagnetic contamination is widely used in modern power systems. However, due to the limited production, transmission, and installation conditions, GIS will haveThe associate editor coordinating the review of this manuscript and approving it for publication was Porfirio Tramontana .

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Section: B Internet Of Things (Iot) Technologymentioning

confidence: 99%

Exploration on Automatic Management of GIS Using TL-CNN and IoT

et al. 2022

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“…Alternatively, to increase the read throughput (generally defined as the number of tags read per time slot). Based on access schemes, such algorithms are usually classified into time-division multiple access (TDMA), frequency-division multiple access (FDMA), and carrier-sense multiple access (CSMA) [23]- [28]. Considering TDMA has a relatively low implementation complexity and operational cost, most of such algorithms are TDMA-based, which can be further divided into ALOHA-based and tree-based algorithms [29].…”

Section: Introductionmentioning

confidence: 99%

A Machine Learning Auxiliary Approach for the Distributed Dense RFID Readers Arrangement Algorithm

2020

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This paper is an extended version of the work published. Radio-frequency identification (RFID) is widespread in industries such as supply-chain management and logistics due to its low-cost feature. In many real-world problems, one often needs to leverage a considerable amount of RFID readers to cover a large area. Many graph-based dense RFID readers system anti-collision algorithms were proposed to address the collision problems. However, state-of-the-art collision avoidance algorithms are centralized algorithms. In a dense RFID system, the graphs generated by the centralized algorithms could be very complicated. Therefore, a centralized algorithm increases the computational workload of the central server. We proposed a distributed anti-collision algorithm based on the idea of a centralized collision avoidance algorithm called MWISBAII. In our later research, we found that due to the lack of global information, there is a gap between the performance of our distributed algorithm and the centralized MWISBAII. To narrow this gap, we introduced machine learning into the proposed algorithm. The machine learning model is an empirical model that mitigates the deficiency of the lack of global information. The experimental results show that the proposed distributed algorithm with machine learning can get almost the same performance as the centralized MWISBAII in different experimental settings. INDEX TERMS Large scale RFID network optimization, reader coverage collision avoidance (RCCA), maximum weight independent set (MWIS), machine learning (ML).

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“…So there are three kinds of collisions: The tag-tag collision, the reader-reader collision and the tag-reader collision. To counter this problem, anti-collision algorithms have been introduced which have their own literature, e.g., [1][2][3][4][5][6][7][8][9][10][11]. There are many issues in the field of anti-collision in RFID systems which researchers try to solve, e.g., increasing the number of read tags by the reader.…”

Section: Introductionmentioning

confidence: 99%

On the Security of Rotation Operation Based Ultra-Lightweight Authentication Protocols for RFID Systems

2018

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Passive Radio Frequency IDentification (RFID) tags are generally highly constrained and cannot support conventional encryption systems to meet the required security. Hence, designers of security protocols may try to achieve the desired security only using limited ultra-lightweight operations. In this paper, we show that the security of such protocols is not provided by using rotation functions. In the following, for an example, we investigate the security of an RFID authentication protocol that has been recently developed using rotation function named ULRAS, which stands for an Ultra-Lightweight RFID Authentication Scheme and show its security weaknesses. More precisely, we show that the ULRAS protocol is vulnerable against de-synchronization attack. The given attack has the success probability of almost ‘1’, with the complexity of only one session of the protocol. In addition, we show that the given attack can be used as a traceability attack against the protocol if the parameters’ lengths are an integer power of 2, e.g., 128. Moreover, we propose a new authentication protocol named UEAP, which stands for an Ultra-lightweight Encryption based Authentication Protocol, and then informally and formally, using Scyther tool, prove that the UEAP protocol is secure against all known active and passive attacks.

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TDMA‐SDMA‐based RFID algorithm for fast detection and efficient collision avoidance

Cited by 6 publications

References 42 publications

Exploration on Automatic Management of GIS Using TL-CNN and IoT

Exploration on Automatic Management of GIS Using TL-CNN and IoT

A Machine Learning Auxiliary Approach for the Distributed Dense RFID Readers Arrangement Algorithm

On the Security of Rotation Operation Based Ultra-Lightweight Authentication Protocols for RFID Systems

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