An effective frame breaking policy for dynamic framed slotted aloha in RFID

The tag collision problem is considered as one of the critical issues in RFID system. To further improve the identification efficiency of an UHF RFID system, a frame breaking policy is proposed with dynamic framed slotted aloha algorithm. Specifically, the reader makes effective use of idle, successful, and collision statistics during the early observation phase to recursively determine the optimal frame size. Then the collided tags in each slot will be resolved by individual frames. Simulation results show that the proposed algorithm achieves a better identification performance compared with the existing Aloha-based algorithms

A Fast Anticollision Algorithm with Early Adjustment of Frame Length for the EPCglobal UHF Class-1 Generation-2 RFID Standard

This paper develops a fast algorithm to identify a large number of tags in a short period of time duration in RFID systems. The main goal of the proposed algorithm is to meet the requirement in supply chain management. In this paper, we derive mathematical model to analyze the tag identify process. Based on the analysis, we can decide the optimal frame length and when the current read round is early ended. We find that the optimal frame length should be set to 1.72 times of the number of tags when the ratio between collision-slot duration and empty-slot duration is 4. Through the use of early adjustment of frame length, the RFID interrogator examines the fitness of frame lemgth only at three time slots in each read round. The primary advantage of our algorithm is the ability to achieve a good compromise between throughput performance and computation complexity

A partitioning approach to RFID identification

Radio-frequency identification (RFID) is a major enabler of Internet of Things (IoT), and has been widely applied in tag-intensive environments. Tag collision arbitration is considered as a crucial issue of such RFID system. To enhance the reading performance of RFID, numerous anti-collision algorithms have been presented in previous literatures. However, most of them suffer from the slot efficiency bottleneck of 0.368. In this paper, we revisit the performance of tag identification in Aloha-based RFID anti-collision approaches from the perspective of time efficiency. Based on comprehensive reviews and analysis of the existing algorithms, a novel partitioning approach is proposed to maximize identification performance in framed slotted Aloha based UHF RFID systems. In the proposed approach, the tag set is divided into many groups which only contains a few tags, and then each group is identified in sequence. Benefiting from the optimal partition, the proposed algorithm can achieve a significant performance improvement. Simulation results supplemented by prototyping tests show that the proposed solution achieves an asymptotical slot efficiency up to 0.4348, outperforming the existing UHF RFID solutions

A fast tag identification anti-collision algorithm for RFID systems

© 2019 John Wiley & Sons, Ltd. In this work, we propose a highly efficient binary tree-based anti-collision algorithm for radio frequency identification (RFID) tag identification. The proposed binary splitting modified dynamic tree (BS-MDT) algorithm employs a binary splitting tree to achieve accurate tag estimation and a modified dynamic tree algorithm for rapid tag identification. We mathematically evaluate the performance of the BS-MDT algorithm in terms of the system efficiency and the time system efficiency based on the ISO/IEC 18000-6 Type B standard. The derived mathematical model is validated using computer simulations. Numerical results show that the proposed BS-MDT algorithm can provide the system efficiency of 46% and time system efficiency of 74%, outperforming all other well-performed algorithms

Asymptotic Analysis of Backlog Estimates for Dynamic Frame Aloha

In this paper a new analysis is presented that allowsto investigate the asymptotic behavior of some backlog estimation procedures for Dynamic Frame Aloha (DFA) in Radio Frequency Identification (RFID) environment. Although efficiency e-1 can theoretically be reached, none of the solution proposed in the literature has been shown to reach such value. Here we analyze first the Schoute’s backlog estimate, which is very attractive for its simplicity, and formally show that its asymptotic efficiency is 0:311 for any finite initial frame length. Since the analysis shows how the Schoute’s estimate impairment can be avoided, wefurther propose the Asymptotic Efficient Estimate (AE2), an improvement of the Schoute’s one, that exploits the Frame Restart property of the standard and that is proved to asymptotically reach efficiency e-1

Global traceability

The use of Ultra High Frequency (UHF) Radio Frequency Identification (RFID) in supply chain management (SCM) systems was a big source for optimism. However, the expected rapid industry adoption of RFID did not take place. This research explores some of the existing challenges and obstacles to RFID adoption, such as the lack of consistent UHF spectrum regulations for RFID or the absence of standards that promote integration with Automatic Identification and Data Capture (AIDC) media. As a conclusion, in this project we suggest some solutions to these challenges in the use of multi-frequency RFID tags that can be read at more that one frequency or novel migration strategies and standards that would help expand the industry.Outgoin

A Reduced Complexity of Vahedi's Tag Estimation Method for DFSA

In order to calculate the number of tags in a radio frequency identification (RFID) system, several tag estimation methods have been investigated in literature and most of the available estimation methods need the overall knowledge of idle, success and collision slots of the previous frame to carry out the tag estimation process. In this article, we present three techniques to reduce the complexity of Vahedi’s tag estimation for tag collision resolution in RFID systems using dynamic frame slotted ALOHA. Our modified and useful approach considers the information about only the number of empty, successful or colliding slots in the previous frame for the tag estimation. Three decision rules were obtained by maximizing the likelihood of success, idle and collision which helps in the reduction of complexity substantially. However, the accuracy of estimation decreases for success-only and idle-only methods while the collision-only method gives a consistent and lower estimate error when the frame sizes and the number of tags increase

セキュアRFIDタグチップの設計論

In this thesis, we focus on radio frequency identification (RFID) tag. We design, implement, and evaluate hardware performance of a secure tag that runs the authentication protocol based on cryptographic algorithms. The cryptographic algorithm and the pseudorandom number generator are required to be implemented in the tag. To realize the secure tag, we tackle the following four steps: (A) decision of hardware architecture for the authentication protocol, (B) selection of the cryptographic algorithm, (C) establishment of a pseudorandom number generating method, and (D) implementation and performance evaluation of a silicon chip on an RFID system.(A) The cryptographic algorithm and the pseudorandom number generator are repeatedly called for each authentication. Therefore, the impact of the time needed for the cryptographic processes on the hardware performance of the tag can be large. While low-area requirements have been mainly discussed in the previous studies, it is needed to discuss the hardware architecture for the authentication protocol from the viewpoint of the operating time. In this thesis, in order to decide the hardware architecture, we evaluate hardware performance in the sense of the operating time. As a result, the parallel architecture is suitable for hash functions that are widely used for tag authentication protocols.(B) A lot of cryptographic algorithms have been developed and hardware performance of the algorithms have been evaluated on different conditions. However, as the evaluation results depend on the conditions, it is hard to compare the previous results. In addition, the interface of the cryptographic circuits has not been paid attention. In this thesis, in order to select a cryptographic algorithm, we design the interface of the cryptographic circuits to meet with the tag, and evaluate hardware performance of the circuits on the same condition. As a result, the lightweight hash function SPONGENT-160 achieves well-balanced hardware performance.(C) Implementation of a pseudorandom number generator based on the performance evaluation results on (B) can be a method to generate pseudorandom number on the tag. On the other hand, as the cryptographic algorithm and the pseudorandom number generator are not used simultaneously on the authentication protocol. Therefore, if the cryptographic circuit could be used for pseudorandom number generation, the hardware resource on the tag can be exploited efficiently. In this thesis, we propose a pseudorandom number generating method using a hash function that is a cryptographic component of the authentication protocol. Through the evaluation of our proposed method, we establish a lightweight pseudorandom number generating method for the tag.(D) Tag authentication protocols using a cryptographic algorithm have been developed in the previous studies. However, hardware implementation and performance evaluation of a tag, which runs authentication processes, have not been studied. In this thesis, we design and do a single chip implementation of an analog front-end block and a digital processing block including the results on (A), (B), and (C). Then, we evaluate hardware performance of the tag. As a result, we show that a tag, which runs the authentication protocol based on cryptographic algorithms, is feasible.電気通信大学201

Advances in analytical models and applications for RFID, WSN and AmI systems

Experimentos llevados a cabo con el equipo de división de honor UCAM Volleyball Murcia.[SPA] Internet de las cosas (IoT) integra distintos elementos que actúan tanto como fuentes, como sumideros de información, a diferencia de la percepción que se ha tenido hasta ahora de Internet, centrado en las personas. Los avances en IoT engloban un amplio número de áreas y tecnologías, desde la adquisición de información hasta el desarrollo de nuevos protocolos y aplicaciones. Un concepto clave que subyace en el concepto de IoT, es el procesamiento de forma inteligente y autónoma de los flujos de información que se dispone. En este trabajo, estudiamos tres aspectos diferentes de IoT. En primer lugar, nos centraremos en la infraestructura de obtención de datos. Entre las diferentes tecnologías de obtención de datos disponibles en los sistemas IoT, la Identificación por Radio Frecuencia (RFID) es considerada como una de las tecnologías predominantes. RFID es la tecnología detrás de aplicaciones tales como control de acceso, seguimiento y rastreo de contenedores, gestión de archivos, clasificación de equipaje o localización de equipos. Con el auge de la tecnología RFID, muchas instalaciones empiezan a requerir la presencia de múltiples lectores RFID que operan próximos entre sí y conjuntamente. A estos escenarios se les conoce como dense reader environments (DREs). La coexistencia de varios lectores operando simultáneamente puede causar graves problemas de interferencias en el proceso de identificación. Uno de los aspectos claves a resolver en los RFID DREs consiste en lograr la coordinación entre los lectores. Estos problemas de coordinación son tratados en detalle en esta tesis doctoral. Además, dentro del área de obtención de datos relativa a IoT, las Redes de Sensores Inalámbricas (WSNs) desempeñan un papel fundamental. Durante la última década, las WSNs han sido estudiadas ampliamente de forma teórica, y la mayoría de problemas relacionados con la comunicación en este tipo de redes se han conseguido resolver de forma favorable. Sin embargo, con la implementación de WSNs en proyectos reales, han surgido nuevos problemas, siendo uno de ellos el desarrollo de estrategias realistas para desplegar las WSN. En este trabajo se estudian diferentes métodos que resuelven este problema, centrándonos en distintos criterios de optimización, y analizando las diferentes ventajas e inconvenientes que se producen al buscar una solución equilibrada. Por último, la Inteligencia Ambiental (AmI) forma parte del desarrollo de aplicaciones inteligentes en IoT. Hasta ahora, han sido las personas quienes han tenido que adaptarse al entorno, en cambio, AmI persigue crear entornos de obtención de datos capaces de anticipar y apoyar las acciones de las personas. AmI se está introduciendo progresivamente en diversos entornos reales tales como el sector de la educación y la salud, en viviendas, etc. En esta tesis se introduce un sistema AmI orientado al deporte que busca mejorar el entrenamiento de los atletas, siendo el objetivo prioritario el desarrollo de un asistente capaz de proporcionar órdenes de entrenamiento, basadas tanto en el entorno como en el rendimiento de los atletas. [ENG] Internet of Things (IoT) is being built upon many different elements acting as sources and sinks of information, rather than the previous human-centric Internet conception. Developments in IoT include a vast set of fields ranging from data sensing, to development of new protocols and applications. Indeed, a key concept underlying in the conception of IoT is the smart and autonomous processing of the new huge data flows available. In this work, we aim to study three different aspects within IoT. First, we will focus on the sensing infrastructure. Among the different kind of sensing technologies available to IoT systems, Radio Frequency Identification (RFID) is widely considered one of the leading technologies. RFID is the enabling technology behind applications such as access control, tracking and tracing of containers, file management, baggage sorting or equipment location. With the grow up of RFID, many facilities require multiple RFID readers usually operating close to each other. These are known as Dense Reader Environments (DREs). The co-existence of several readers operating concurrently is known to cause severe interferences on the identification process. One of the key aspects to solve in RFID DREs is achieving proper coordination among readers. This is the focus of the first part of this doctoral thesis. Unlike previous works based on heuristics, we address this problem through an optimization-based approach. The goal is identifying the maximum mean number of tags while network constraints are met. To be able to formulate these optimization problems, we have obtained analytically the mean number of identifications in a bounded -discrete or continuous- time period, an additional novel contribution of our work. Results show that our approach is overwhelmingly better than previous known methods. Along sensing technologies of IoT, Wireless Sensor Networks (WSNs) plays a fundamental role. WSNs have been largely and theoretically studied in the past decade, and many of their initial problems related to communication aspects have been successfully solved. However, with the adoption of WSNs in real-life projects, new issues have arisen, being one of them the development of realistic strategies to deploy WSNs. We have studied different ways of solving this aspect by focusing on different optimality criteria and evaluating the different trade-offs that occur when a balanced solution must be selected. On the one hand, deterministic placements subject to conflicting goals have been addressed. Results can be obtained in the form of Pareto-frontiers, allowing proper solution selection. On the other hand, a number of situations correspond to deployments were the nodes¿ position is inherently random. We have analyzed these situations leading first to a theoretical model, which later has been particularized to a Moon WSN survey. Our work is the first considering a full model with realistic properties such as 3D topography, propellant consumptions or network lifetime and mass limitations. Furthermore, development of smart applications within IoT is the focus of the Ambient Intelligence (AmI) field. Rather than having people adapting to the surrounding environment, AmI pursues the development of sensitive environments able to anticipate support in people¿s actions. AmI is progressively being introduced in many real-life environments like education, homes, health and so forth. In this thesis we develop a sport-oriented AmI system designed to improve athletes training. The goal is developing an assistant able to provide real-time training orders based on both environment and athletes¿ biometry, which is aimed to control the aerobic and the technical-tactical training. Validation experiments with the honor league UCAM Volleyball Murcia team have shown the suitability of this approach.[ENG] Internet of Things (IoT) is being built upon many different elements acting as sources and sinks of information, rather than the previous human-centric Internet conception. Developments in IoT include a vast set of fields ranging from data sensing, to development of new protocols and applications. Indeed, a key concept underlying in the conception of IoT is the smart and autonomous processing of the new huge data flows available. In this work, we aim to study three different aspects within IoT. First, we will focus on the sensing infrastructure. Among the different kind of sensing technologies available to IoT systems, Radio Frequency Identification (RFID) is widely considered one of the leading technologies. RFID is the enabling technology behind applications such as access control, tracking and tracing of containers, file management, baggage sorting or equipment location. With the grow up of RFID, many facilities require multiple RFID readers usually operating close to each other. These are known as Dense Reader Environments (DREs). The co-existence of several readers operating concurrently is known to cause severe interferences on the identification process. One of the key aspects to solve in RFID DREs is achieving proper coordination among readers. This is the focus of the first part of this doctoral thesis. Unlike previous works based on heuristics, we address this problem through an optimization-based approach. The goal is identifying the maximum mean number of tags while network constraints are met. To be able to formulate these optimization problems, we have obtained analytically the mean number of identifications in a bounded -discrete or continuous- time period, an additional novel contribution of our work. Results show that our approach is overwhelmingly better than previous known methods. Along sensing technologies of IoT, Wireless Sensor Networks (WSNs) plays a fundamental role. WSNs have been largely and theoretically studied in the past decade, and many of their initial problems related to communication aspects have been successfully solved. However, with the adoption of WSNs in real-life projects, new issues have arisen, being one of them the development of realistic strategies to deploy WSNs. We have studied different ways of solving this aspect by focusing on different optimality criteria and evaluating the different trade-offs that occur when a balanced solution must be selected. On the one hand, deterministic placements subject to conflicting goals have been addressed. Results can be obtained in the form of Pareto-frontiers, allowing proper solution selection. On the other hand, a number of situations correspond to deployments were the nodes¿ position is inherently random. We have analyzed these situations leading first to a theoretical model, which later has been particularized to a Moon WSN survey. Our work is the first considering a full model with realistic properties such as 3D topography, propellant consumptions or network lifetime and mass limitations. Furthermore, development of smart applications within IoT is the focus of the Ambient Intelligence (AmI) field. Rather than having people adapting to the surrounding environment, AmI pursues the development of sensitive environments able to anticipate support in people¿s actions. AmI is progressively being introduced in many real-life environments like education, homes, health and so forth. In this thesis we develop a sport-oriented AmI system designed to improve athletes training. The goal is developing an assistant able to provide real-time training orders based on both environment and athletes¿ biometry, which is aimed to control the aerobic and the technical-tactical training. Validation experiments with the honor league UCAM Volleyball Murcia team have shown the suitability of this approach.Universidad Politécnica de CartagenaPrograma de doctorado en Tecnología de la Información y de las Comunicacione

Global traceability

The use of Ultra High Frequency (UHF) Radio Frequency Identification (RFID) in supply chain management (SCM) systems was a big source for optimism. However, the expected rapid industry adoption of RFID did not take place. This research explores some of the existing challenges and obstacles to RFID adoption, such as the lack of consistent UHF spectrum regulations for RFID or the absence of standards that promote integration with Automatic Identification and Data Capture (AIDC) media. As a conclusion, in this project we suggest some solutions to these challenges in the use of multi-frequency RFID tags that can be read at more that one frequency or novel migration strategies and standards that would help expand the industry.Outgoin