A critical analysis of research potential, challenges and future directives in industrial wireless sensor networks

In recent years, Industrial Wireless Sensor Networks (IWSNs) have emerged as an important research theme with applications spanning a wide range of industries including automation, monitoring, process control, feedback systems and automotive. Wide scope of IWSNs applications ranging from small production units, large oil and gas industries to nuclear fission control, enables a fast-paced research in this field. Though IWSNs offer advantages of low cost, flexibility, scalability, self-healing, easy deployment and reformation, yet they pose certain limitations on available potential and introduce challenges on multiple fronts due to their susceptibility to highly complex and uncertain industrial environments. In this paper a detailed discussion on design objectives, challenges and solutions, for IWSNs, are presented. A careful evaluation of industrial systems, deadlines and possible hazards in industrial atmosphere are discussed. The paper also presents a thorough review of the existing standards and industrial protocols and gives a critical evaluation of potential of these standards and protocols along with a detailed discussion on available hardware platforms, specific industrial energy harvesting techniques and their capabilities. The paper lists main service providers for IWSNs solutions and gives insight of future trends and research gaps in the field of IWSNs

A Survey of Prediction and Classification Techniques in Multicore Processor Systems

In multicore processor systems, being able to accurately predict the future provides new optimization opportunities, which otherwise could not be exploited. For example, an oracle able to predict a certain application\u27s behavior running on a smart phone could direct the power manager to switch to appropriate dynamic voltage and frequency scaling modes that would guarantee minimum levels of desired performance while saving energy consumption and thereby prolonging battery life. Using predictions enables systems to become proactive rather than continue to operate in a reactive manner. This prediction-based proactive approach has become increasingly popular in the design and optimization of integrated circuits and of multicore processor systems. Prediction transforms from simple forecasting to sophisticated machine learning based prediction and classification that learns from existing data, employs data mining, and predicts future behavior. This can be exploited by novel optimization techniques that can span across all layers of the computing stack. In this survey paper, we present a discussion of the most popular techniques on prediction and classification in the general context of computing systems with emphasis on multicore processors. The paper is far from comprehensive, but, it will help the reader interested in employing prediction in optimization of multicore processor systems

Architectural solutions of conformal network-centric staring-sensor systems with spherical field of view

The article presents the concept of network-centric conformal electro-optical systems construction with spherical field of view. It discusses abstract passive distributed electro-optical systems with focal array detectors based on a group of moving objects distributed in space. The system performs conformal processing of information from sensor matrix in a single event coordinate-time field. Unequivocally the construction of the systems which satisfy the different criteria of optimality is very complicated and requires special approaches to their development and design. The paper briefly touches upon key questions (in the authors' opinion) in the synthesis of such systems that meet different criteria of optimality. The synthesis of such systems is discussed by authors with the systematic and synergy approaches.Comment: 16 pages, 2 figures, 2 tables, Report accepted for conference: SPIE Security+Defence 2011, Conferences "Electro-Optical and Infrared Systems: Technology and Applications", 19-22 September 2011, Prague, Czech Republic, Paper 8185-1

Hybrid Satellite-Terrestrial Communication Networks for the Maritime Internet of Things: Key Technologies, Opportunities, and Challenges

With the rapid development of marine activities, there has been an increasing number of maritime mobile terminals, as well as a growing demand for high-speed and ultra-reliable maritime communications to keep them connected. Traditionally, the maritime Internet of Things (IoT) is enabled by maritime satellites. However, satellites are seriously restricted by their high latency and relatively low data rate. As an alternative, shore & island-based base stations (BSs) can be built to extend the coverage of terrestrial networks using fourth-generation (4G), fifth-generation (5G), and beyond 5G services. Unmanned aerial vehicles can also be exploited to serve as aerial maritime BSs. Despite of all these approaches, there are still open issues for an efficient maritime communication network (MCN). For example, due to the complicated electromagnetic propagation environment, the limited geometrically available BS sites, and rigorous service demands from mission-critical applications, conventional communication and networking theories and methods should be tailored for maritime scenarios. Towards this end, we provide a survey on the demand for maritime communications, the state-of-the-art MCNs, and key technologies for enhancing transmission efficiency, extending network coverage, and provisioning maritime-specific services. Future challenges in developing an environment-aware, service-driven, and integrated satellite-air-ground MCN to be smart enough to utilize external auxiliary information, e.g., sea state and atmosphere conditions, are also discussed

Real-Time Monitoring and Fault Diagnostics in Roll-To-Roll Manufacturing Systems

A roll-to-roll (R2R) process is a manufacturing technique involving continuous processing of a flexible substrate as it is transferred between rotating rolls. It integrates many additive and subtractive processing techniques to produce rolls of product in an efficient and cost-effective way due to its high production rate and mass quantity. Therefore, the R2R processes have been increasingly implemented in a wide range of manufacturing industries, including traditional paper/fabric production, plastic and metal foil manufacturing, flexible electronics, thin film batteries, photovoltaics, graphene films production, etc. However, the increasing complexity of R2R processes and high demands on product quality have heightened the needs for effective real-time process monitoring and fault diagnosis in R2R manufacturing systems. This dissertation aims at developing tools to increase system visibility without additional sensors, in order to enhance real-time monitoring, and fault diagnosis capability in R2R manufacturing systems. First, a multistage modeling method is proposed for process monitoring and quality estimation in R2R processes. Product-centric and process-centric variation propagation are introduced to characterize variation propagation throughout the system. The multistage model mainly focuses on the formulation of process-centric variation propagation, which uniquely exists in R2R processes, and the corresponding product quality measurements with both physical knowledge and sensor data analysis. Second, a nonlinear analytical redundancy method is proposed for sensor validation to ensure the accuracy of sensor measurements for process and quality control. Parity relations based on nonlinear observation matrix are formulated to characterize system dynamics and sensor measurements. Robust optimization is designed to identify the coefficient of parity relations that can tolerate a certain level of measurement noise and system disturbances. The effect of the change of operating conditions on the value of the optimal objective function – parity residuals and the optimal design variables – parity coefficients are evaluated with sensitivity analysis. Finally, a multiple model approach for anomaly detection and fault diagnosis is introduced to improve the diagnosability under different operating regimes. The growing structure multiple model system (GSMMS) is employed, which utilizes Voronoi sets to automatically partition the entire operating space into smaller operating regimes. The local model identification problem is revised by formulating it into an optimization problem based on the loss minimization framework and solving with the mini-batch stochastic gradient descent method instead of least squares algorithms. This revision to the GSMMS method expands its capability to handle the local model identification problems that cannot be solved with a closed-form solution. The effectiveness of the models and methods are determined with testbed data from an R2R process. The results show that those proposed models and methods are effective tools to understand variation propagation in R2R processes and improve estimation accuracy of product quality by 70%, identify the health status of sensors promptly to guarantee data accuracy for modeling and decision making, and reduce false alarm rate and increase detection power under different operating conditions. Eventually, those tools developed in this thesis contribute to increase the visibility of R2R manufacturing systems, improve productivity and reduce product rejection rate.PHDMechanical EngineeringUniversity of Michigan, Horace H. Rackham School of Graduate Studieshttps://deepblue.lib.umich.edu/bitstream/2027.42/146114/1/huanyis_1.pd

Limits on Fundamental Limits to Computation

An indispensable part of our lives, computing has also become essential to industries and governments. Steady improvements in computer hardware have been supported by periodic doubling of transistor densities in integrated circuits over the last fifty years. Such Moore scaling now requires increasingly heroic efforts, stimulating research in alternative hardware and stirring controversy. To help evaluate emerging technologies and enrich our understanding of integrated-circuit scaling, we review fundamental limits to computation: in manufacturing, energy, physical space, design and verification effort, and algorithms. To outline what is achievable in principle and in practice, we recall how some limits were circumvented, compare loose and tight limits. We also point out that engineering difficulties encountered by emerging technologies may indicate yet-unknown limits.Comment: 15 pages, 4 figures, 1 tabl

Physical parameter-aware Networks-on-Chip design

PhD ThesisNetworks-on-Chip (NoCs) have been proposed as a scalable, reliable and power-efficient communication fabric for chip multiprocessors (CMPs) and multiprocessor systems-on-chip (MPSoCs). NoCs determine both the performance and the reliability of such systems, with a significant power demand that is expected to increase due to developments in both technology and architecture. In terms of architecture, an important trend in many-core systems architecture is to increase the number of cores on a chip while reducing their individual complexity. This trend increases communication power relative to computation power. Moreover, technology-wise, power-hungry wires are dominating logic as power consumers as technology scales down. For these reasons, the design of future very large scale integration (VLSI) systems is moving from being computation-centric to communication-centric. On the other hand, chip’s physical parameters integrity, especially power and thermal integrity, is crucial for reliable VLSI systems. However, guaranteeing this integrity is becoming increasingly difficult with the higher scale of integration due to increased power density and operating frequencies that result in continuously increasing temperature and voltage drops in the chip. This is a challenge that may prevent further shrinking of devices. Thus, tackling the challenge of power and thermal integrity of future many-core systems at only one level of abstraction, the chip and package design for example, is no longer sufficient to ensure the integrity of physical parameters. New designtime and run-time strategies may need to work together at different levels of abstraction, such as package, application, network, to provide the required physical parameter integrity for these large systems. This necessitates strategies that work at the level of the on-chip network with its rising power budget. This thesis proposes models, techniques and architectures to improve power and thermal integrity of Network-on-Chip (NoC)-based many-core systems. The thesis is composed of two major parts: i) minimization and modelling of power supply variations to improve power integrity; and ii) dynamic thermal adaptation to improve thermal integrity. This thesis makes four major contributions. The first is a computational model of on-chip power supply variations in NoCs. The proposed model embeds a power delivery model, an NoC activity simulator and a power model. The model is verified with SPICE simulation and employed to analyse power supply variations in synthetic and real NoC workloads. Novel observations regarding power supply noise correlation with different traffic patterns and routing algorithms are found. The second is a new application mapping strategy aiming vii to minimize power supply noise in NoCs. This is achieved by defining a new metric, switching activity density, and employing a force-based objective function that results in minimizing switching density. Significant reductions in power supply noise (PSN) are achieved with a low energy penalty. This reduction in PSN also results in a better link timing accuracy. The third contribution is a new dynamic thermal-adaptive routing strategy to effectively diffuse heat from the NoC-based threedimensional (3D) CMPs, using a dynamic programming (DP)-based distributed control architecture. Moreover, a new approach for efficient extension of two-dimensional (2D) partially-adaptive routing algorithms to 3D is presented. This approach improves three-dimensional networkon- chip (3D NoC) routing adaptivity while ensuring deadlock-freeness. Finally, the proposed thermal-adaptive routing is implemented in field-programmable gate array (FPGA), and implementation challenges, for both thermal sensing and the dynamic control architecture are addressed. The proposed routing implementation is evaluated in terms of both functionality and performance. The methodologies and architectures proposed in this thesis open a new direction for improving the power and thermal integrity of future NoC-based 2D and 3D many-core architectures

Analysis of Wireless Body-Centric Medical Sensors for Remote Healthcare

Aquesta tesi aborda el problema de trobar solucions confortables, de baixa potència i sense fils per aplicacions mèdiques. La tesi tracta els avantatges i les limitacions de tres tecnologies de comunicació diferents per la mesura de paràmetres del cos i mètodes per redissenyar sensors per avaluacions òptimes centrades en el cos. La tecnologia RFID es considera una de les solucions més influents per superar el problema del consum d'energia limitat, a causa de la presència de molts sensors connectats. També s'ha estudiat la tecnologia Bluetooth de baixa energia per resoldre els problemes de seguretat i la distància de lectura que, en general, representen el coll d'ampolla de RFID pels sensors de cos. Els dispositius analògics poden reduir dràsticament les necessitats d'energia a causa dels sensors i les comunicacions, considerant pocs elements i un mètode de transmissió simple. S'estudia un mètode de comunicació completament passiu, basat en FSS, que permet una distància de lectura raonable amb capacitats de detecció precises i confiables, que s'ha discutit en aquesta tesi. L'objectiu d'aquesta tesi és investigar múltiples tecnologies sense fils per dispositius portàtils per identificar solucions adequades per aplicacions particulars en el camp mèdic. El primer objectiu és demostrar la facilitat d'ús de les tecnologies econòmiques sense bateria com un indicador útil de paràmetres fisiopatològics mitjançant la investigació de les propietats de les etiquetes RFID. A més a més, s'ha abordat un aspecte més complex respecte a l'ús de petits components passius com sensors sense fils per trastorns del son. Per últim, un altre objectiu de la tesi és el desenvolupament d'un sistema completament autònom que utilitzi tecnologia BLE per obtenir propietats avançades mantenint baix tant el consum com el preuEsta tesis aborda el problema de encontrar soluciones confortables, inalámbricas y de baja potencia para aplicaciones médicas. La tesis discute las ventajas y limitaciones de tres tecnologías de comunicación diferentes para la medición en el cuerpo y los métodos para elegir y remodelar los sensores para evaluaciones óptimas centradas en el cuerpo. La tecnología RFID se considera una de las soluciones más influyentes para superar el consumo de energía limitado debido a la presencia de muchos sensores conectados. Además, la baja energía de Bluetooth se ha estudiado se ha estudiado la tecnologia Bluetooth de baja energia para resolver los problemas de seguridad y la distancia de lectura que, en general, representan el cuello de botella de la RFID para los sensores de cuerpo. Los dispositivos analógicos pueden reducir drásticamente las necesidades de energía debido a los sensores y las comunicaciones, considerando pocos elementos y un método de transmisión simple. Se estudia un método de comunicación completamente pasivo, basado en FSS, que permite una distancia de lectura razonable con capacidades de detección precisas y confiables, que se ha discutido en esta tesis. El objetivo de esta tesis es investigar múltiples tecnologías inalámbricas para dispositivos portátiles para identificar soluciones adecuadas para aplicaciones particulares en campos médicos. El primer objetivo es demostrar la facilidad de uso de las tecnologías económicas sin batería como un indicador útil de dichos parámetros fisiopatológicos mediante la investigación de las propiedades de las etiquetas RFID. Además, se ha abordado un aspecto más complejo con respecto al uso de pequeños componentes pasivos como sensores inalámbricos para enfermedades del sueño. Por último, un resultado de la tesis es desarrollar un sistema completamente autónomo que utilice la tecnología BLE para obtener propiedades avanzadas que mantengan la baja potencia y un precio bajo.This thesis addresses the problem of comfortable, low powered and, wireless solutions for specific body-worn sensing. The thesis discusses advantages and limitations of three different communication technologies for on body measurement and investigate methods to reshape sensors for optimum body-centric assessments. The RFID technology is considered one of the most influential solutions to overcome the limitated power consumption due to the presence of many sensors connected. Further, the Bluetooth low energy has been studied to solve security problems and reading distance that overall represent the bottleneck of the RFID for the body-worn sensors. Analog devices can drastically reduce the energy needs due to the sensors and the communications, considering few elements and a simple transmitting method. An entirely passive communication method, based on FSS is studied, enabling a reasonable reading distance with precise and reliable sensing capabilities, which has been discussed in this thesis. The objective of this thesis is to investigate multiple wireless technologies for wearable devices to identify suitable solutions for particular applications in medical fields. The first objective is to demonstrate the usability of the inexpensive battery-less technologies as a useful indicator of such a physio-pathological parameters by investigating the properties of the RFID tags. Furthermore, a more complex aspect regards the use of small passive components as wireless sensors for sleep diseases has been addressed. Lastly, an outcome of the thesis is to develop an entirely autonomous system using the BLE technology to obtain advanced properties keeping low power and a low price