PACKET ERROR RATE PREDICTIVE MODEL FOR SENSOR RADIOS ON FAST ROTATING STRUCTURES

Wireless sensing technologies have raised widespread interests in the applications for monitoring fast rotating or moving machinery structures in manufacturing environments. Over the past five years, a few wireless sensor systems have been implemented and proven to feasibly work under fast rotation conditions. However, few of these studies evaluated data transmission performance of the wireless communication systems. Although the manufacturing environments are known to be harsh for wireless communication, in many cases, an excellent data throughput is critical for such systems. Conventional statistical methods for studying wireless communication channels are not sufficient in this specific field. This dissertation presents systematic experiments to understand and characterize the behavior of a 2.4 GHz band wireless channel between a fast rotating transmitter and a stationary data receiver. The experiments prove, in manufacturing machines, multipath propagation induced by metallic objects causes high power attenuation of radio signals during transmitter motion, and the consequence, low received signal power, is recognized as the major cause of transmission errors. The dissertation proposes a deterministic packet error rate (PER) predictive model for rotating wireless measuring systems using IEEE 802.15.4 sensor radios. The model consists of three sub-models that predict power attenuation, bit error rate (BER), and PER in three stages for given specifications regarding environment, radio transmission, and rotation. The dissertation provides experimental validation of the sub-models and discusses their limitations and prediction errors. By either experiments or simulations, two data transmission protocols, automatic retransmission request (ARQ) method and online error avoidance algorithm, are proved efficient for a reliable wireless communication of such sensor radios. As the first effort to characterize and model such radio channels, the dissertation provides in-depth understandings of the channels\u27 fast varying behavior, achieves prediction guidance for the channels\u27 communication performance, and introduces prospective transmission protocols for performance enhancement

Transmission Error Analysis and Avoidance for IEEE 802.15.4 Wireless Sensors on Rotating Structures

Wireless sensors are increasingly adopted in manufacturing and vehicular systems for monitoring critical components under continuous operation. Many such components move rapidly and frequently in metallic containments with challenging radio propagation characteristics. For wireless sensors mounted on rotating structures, previous studies identified an eminent increase in packet transmission errors at higher rotation speeds. Such errors were found to occur at specific locations around the rotating spindle\u27s periphery and such locations depended sensitively on sensor location and surrounding geometry. This thesis presents a systematic study of the expected packet error rates due to such errors, and analytically derives the first transmission error rate for a given system. Simulations done on C++ are used to characterize the error region properties. A transmission error avoidance approach based on on-line error pattern inference and packet transmission time control for IEEE 802.15.4 compatible sensor radios is proposed. The transmission avoidance scheme has two phases: error identification phase to determine the error characteristics of the system and the operational phase to avoid errors. Simulation studies showed a 50% error reduction and up to 75% throughput increase for a rotation system with four symmetric 4¼ wide error zones with 100% BER inside the error region and 0% BER outside the error region. Higher throughput gains for higher rate and larger size transmissions were also noticed for this system. Simulations also show that the throughput decreases when the packet size duration is greater than the separation between the error zone

Illumination-Based Synchronization of High-Speed Vision Sensors

To acquire images of dynamic scenes from multiple points of view simultaneously, the acquisition time of vision sensors should be synchronized. This paper describes an illumination-based synchronization method derived from the phase-locked loop (PLL) algorithm. Incident light to a vision sensor from an intensity-modulated illumination source serves as the reference signal for synchronization. Analog and digital computation within the vision sensor forms a PLL to regulate the output signal, which corresponds to the vision frame timing, to be synchronized with the reference. Simulated and experimental results show that a 1,000 Hz frame rate vision sensor was successfully synchronized with 32 μs jitters

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

Low-Power Embedded Design Solutions and Low-Latency On-Chip Interconnect Architecture for System-On-Chip Design

This dissertation presents three design solutions to support several key system-on-chip (SoC) issues to achieve low-power and high performance. These are: 1) joint source and channel decoding (JSCD) schemes for low-power SoCs used in portable multimedia systems, 2) efficient on-chip interconnect architecture for massive multimedia data streaming on multiprocessor SoCs (MPSoCs), and 3) data processing architecture for low-power SoCs in distributed sensor network (DSS) systems and its implementation. The first part includes a low-power embedded low density parity check code (LDPC) - H.264 joint decoding architecture to lower the baseband energy consumption of a channel decoder using joint source decoding and dynamic voltage and frequency scaling (DVFS). A low-power multiple-input multiple-output (MIMO) and H.264 video joint detector/decoder design that minimizes energy for portable, wireless embedded systems is also designed. In the second part, a link-level quality of service (QoS) scheme using unequal error protection (UEP) for low-power network-on-chip (NoC) and low latency on-chip network designs for MPSoCs is proposed. This part contains WaveSync, a low-latency focused network-on-chip architecture for globally-asynchronous locally-synchronous (GALS) designs and a simultaneous dual-path routing (SDPR) scheme utilizing path diversity present in typical mesh topology network-on-chips. SDPR is akin to having a higher link width but without the significant hardware overhead associated with simple bus width scaling. The last part shows data processing unit designs for embedded SoCs. We propose a data processing and control logic design for a new radiation detection sensor system generating data at or above Peta-bits-per-second level. Implementation results show that the intended clock rate is achieved within the power target of less than 200mW. We also present a digital signal processing (DSP) accelerator supporting configurable MAC, FFT, FIR, and 3-D cross product operations for embedded SoCs. It consumes 12.35mW along with 0.167mm2 area at 333MHz

High-performance AES-128 algorithm implementation by FPGA-based SoC for 5G communications

none4siIn this research work, a fast and lightweight AES-128 cypher based on the Xilinx ZCU102 FPGA board is presented, suitable for 5G communications. In particular, both encryption and decryption algorithms have been developed using a pipelined approach, so enabling the simultaneous processing of the rounds on multiple data packets at each clock cycle. Both the encryption and decryption systems support an operative frequency up to 220 MHz, reaching 28.16 Gbit/s maximum data throughput; besides, the encryption and decryption phases last both only ten clock periods. To guarantee the interoperability of the developed encryption/decryption system with the other sections of the 5G communication apparatus, synchronization and control signals have been integrated. The encryption system uses only 1631 CLBs, whereas the decryption one only 3464 CLBs, ascribable, mainly, to the Inverse Mix Columns step. The developed cypher shows higher efficiency (8.63 Mbps/slice) than similar solutions present in literature.openP.Visconti, R. Velazquez, S. Capoccia, R. de FazioVisconti, P.; Velazquez, R.; Capoccia, S.; de Fazio, R

High-performance AES-128 algorithm implementation by FPGA-based SoC for 5G communications

In this research work, a fast and lightweight AES-128 cypher based on the Xilinx ZCU102 FPGA board is presented, suitable for 5G communications. In particular, both encryption and decryption algorithms have been developed using a pipelined approach, so enabling the simultaneous processing of the rounds on multiple data packets at each clock cycle. Both the encryption and decryption systems support an operative frequency up to 220 MHz, reaching 28.16 Gbit/s maximum data throughput; besides, the encryption and decryption phases last both only ten clock periods. To guarantee the interoperability of the developed encryption/decryption system with the other sections of the 5G communication apparatus, synchronization and control signals have been integrated. The encryption system uses only 1631 CLBs, whereas the decryption one only 3464 CLBs, ascribable, mainly, to the Inverse Mix Columns step. The developed cypher shows higher efficiency (8.63 Mbps/slice) than similar solutions present in literature

Resource Efficient Urban Delay/disruptive Tolerant Networks

Ph.DDOCTOR OF PHILOSOPH

Smart Wireless Sensor Networks

The recent development of communication and sensor technology results in the growth of a new attractive and challenging area - wireless sensor networks (WSNs). A wireless sensor network which consists of a large number of sensor nodes is deployed in environmental fields to serve various applications. Facilitated with the ability of wireless communication and intelligent computation, these nodes become smart sensors which do not only perceive ambient physical parameters but also be able to process information, cooperate with each other and self-organize into the network. These new features assist the sensor nodes as well as the network to operate more efficiently in terms of both data acquisition and energy consumption. Special purposes of the applications require design and operation of WSNs different from conventional networks such as the internet. The network design must take into account of the objectives of specific applications. The nature of deployed environment must be considered. The limited of sensor nodes� resources such as memory, computational ability, communication bandwidth and energy source are the challenges in network design. A smart wireless sensor network must be able to deal with these constraints as well as to guarantee the connectivity, coverage, reliability and security of network's operation for a maximized lifetime. This book discusses various aspects of designing such smart wireless sensor networks. Main topics includes: design methodologies, network protocols and algorithms, quality of service management, coverage optimization, time synchronization and security techniques for sensor networks