On Maximizing the Efficiency of Multipurpose WSNs Through Avoidance of Over- or Under-Provisioning of Information

A wireless sensor network (WSN) is a distributed collection of sensor nodes, which are resource constrained and capable of operating with minimal user attendance. The core function of a WSN is to sample physical phenomena and their environment and transport the information of interest, such as current status or events, as required by the application. Furthermore, the operating conditions and/or user requirements of WSNs are often desired to be evolvable, either driven by changes of the monitored phenomena or by the properties of the WSN itself. Consequently, a key objective for setting up/configuring WSNs is to provide the desired information subject to user defined quality requirements (accuracy, reliability, timeliness etc.), while considering their evolvability at the same time. The current state of the art only addresses the functional blocks of sampling and information transport in isolation. The approaches indeed assume the respective other block to be perfect in maintaining the highest possible information contribution. In addition, some of the approaches just concentrate on a few information attributes such as accuracy and ignore other attributes (e.g., reliability, timeliness, etc.). The existing research targeting these blocks usually tries to enhance the information quality requirements (accuracy, reliability, timeliness etc.), regardless of user requirements and use more resources, leading to faster energy depletion. However, we argue that it is not always necessary to provide the highest possible information quality. In fact, it is essential to avoid under or over provision of information in order to save valuable resources such as energy while just satisfying user evolvable requirements. More precisely, we show the interdependence of the different user requirements and how to co-design them in order to tune the level of provisioning. To discern the fundamental issues dictating the tunable co-design in WSNs, this thesis models and co-designs the sampling accuracy, information transport reliability and timeliness, and compares existing techniques. We highlight the key problems of existing techniques and provide solutions to achieve desired application requirements without under or over provisioning of information. Our first research direction is to provide tunable information transport. We show that it is possible to drastically improve efficiency, while satisfying the user evolvable requirements on reliability and timeliness. In this regard, we provide a novel timeliness model and show the tradeoff between the reliability and timeliness. In addition, we show that the reliability and timeliness can work in composition for maximizing efficiency in information transport. Second, we consider the sampling and information transport co-design by just considering the attributes spatial accuracy and transport reliability. We provide a mathematical model in this regard and then show the optimization of sampling and information transport co-design. The approach is based on optimally choosing the number of samples in order to minimize the number of retransmission in the information transport while maintaining the required reliability. Third, we consider representing the physical phenomena accurately and optimize the network performance. Therefore, we jointly model accuracy, reliability and timeliness, and then derive the optimal combination of sampling and information transport. We provide an optimized model to choose the right representative sensor nodes to describe the phenomena and highlight the tunable co-design of sampling and information transport by avoiding over or under provision of information. Our simulation and experimental results show that the proposed tunable co-design supports evolving user requirements, copes with dynamic network properties and outperforms the state of the art solutions

Recent Advances in Wireless Communications and Networks

This book focuses on the current hottest issues from the lowest layers to the upper layers of wireless communication networks and provides "real-time" research progress on these issues. The authors have made every effort to systematically organize the information on these topics to make it easily accessible to readers of any level. This book also maintains the balance between current research results and their theoretical support. In this book, a variety of novel techniques in wireless communications and networks are investigated. The authors attempt to present these topics in detail. Insightful and reader-friendly descriptions are presented to nourish readers of any level, from practicing and knowledgeable communication engineers to beginning or professional researchers. All interested readers can easily find noteworthy materials in much greater detail than in previous publications and in the references cited in these chapters

Hybrid intelligent decision support system for distributed detection based on ad hoc integrated WSN & RFID

This thesis was submitted for the award of Doctor of Philosophy and was awarded by Brunel University LondonThe real time monitoring of environment context aware activities, based on distributed detection, is becoming a standard in public safety and service delivery in a wide range of domains (child and elderly care and supervision, logistics, circulation, and other). The safety of people, goods and premises depends on the prompt immediate reaction to potential hazards identified in real time, at an early stage to engage appropriate control actions. Effective emergency response can be supported only by available and acquired expertise or elaborate collaborative knowledge in the domain of distributed detection that include indoor sensing, tracking and localizing. This research proposes a hybrid conceptual multi-agent framework for the acquisition of collaborative knowledge in dynamic complex context aware environments for distributed detection. This framework has been applied for the design and development of a hybrid intelligent multi-agent decision system (HIDSS) that supports a decentralized active sensing, tracking and localizing strategy, and the deployment and configuration of smart detection devices associated to active sensor nodes wirelessly connected in a network topology to configure, deploy and control ad hoc wireless sensor networks (WSNs). This system, which is based on the interactive use of data, models and knowledge base, has been implemented to support fire detection and control access fusion functions aimed at elaborating: An integrated data model, grouping the building information data and WSN-RFID database, composed of the network configuration and captured data, A virtual layout configuration of the controlled premises, based on using a building information model, A knowledge-based support for the design of generic detection devices, A multi-criteria decision making model for generic detection devices distribution, ad hoc WSNs configuration, clustering and deployment, and Predictive data models for evacuation planning, and fire and evacuation simulation. An evaluation of the system prototype has been carried out to enrich information and knowledge fusion requirements and show the scope of the concepts used in data and process modelling. It has shown the practicability of hybrid solutions grouping generic homogeneous smart detection devices enhanced by heterogeneous support devices in their deployment, forming ad hoc networks that integrate WSNs and radio frequency identification (RFID) technology. The novelty in this work is the web-based support system architecture proposed in this framework that is based on the use of intelligent agent modelling and multi-agent systems, and the decoupling of the processes supporting the multi-sensor data fusion from those supporting different context applications. Although this decoupling is essential to appropriately distribute the different fusion functions, the integration of several dimensions of policy settings for the modelling of knowledge processes, and intelligent and pro-active decision making activities, requires the organisation of interactive fusion functions deployed upstream to a safety and emergency response.Saudi government, represented by the Ministry of Interior and General Directorate of Civil Defenc

Service architecting and dynamic composition in pervasive smart ecosystems for the Internet of things based on sensor network technology

Why pervasive awareness and Ambient Intelligence are perceived by a great part of the academia and industry as a massive revolution in the short-term? In our best knowledge, a cornerstone of this thought is based on the fact that the ultimate nature of the smart environment paradigm is not in the technology itself, but on a people-centered approach. Perhaps, is in this apparently simple conception where precisely lies the boldness of this promising vision, which has been consolidated in recent years with the emerging proliferation of mobile, personal, portable, wearable and sensory computing: to reach everyone and everywhere. On the one hand, it touches our daily lives in a close manner, minimizing the required attention from the users, anticipating to their needs with the main intention of redefining our idea of Quality of Experience. On the other hand, this new wave impacts everywhere at both global and personal scales allowing expanded connectivity between devices and smart objects, in a dynamic and ubiquitous manner, as a natural extension of the physical world around us. According to the above, this doctoral dissertation focuses on contributing to the integration of software and networking engineering advances in the field of pervasive smart spaces and environment using sensor networks. This is founded on the convergence of some information technology and computer science paradigms, such as service and agent orientation, semantic technologies and knowledge management in the framework of pervasive computing and the Internet of Things. To this end, the nSOM (nano Service-Oriented Middleware) and nSOL (nano Semantics-Oriented Language) approaches are presented. Firstly, the nSOM proposal defines a service-oriented platform for the implementation, deployment and exposure of agent-based in-network services to the Internet cloud on heterogeneous sensor devices. Secondly, the nSOL solution enables an abstraction for supporting ubiquitous service composition based on semantic knowledge management. The integration of both contributions leads to the formal modelling and practical development of adaptive virtual sensor services for pervasive Ambient Intelligence ecosystems. This work includes also the related performance characterization of the resulting prototype according to several metrics such as code size, volatile memory footprint, CPU overhead, service time delay and battery lifetime. Main foundations and outcomes presented in this essay are contextualized in the following European Research Projects: μSWN (FP6 code: IST-034642), DiYSE (ITEA2 code: 08005) and LifeWear (ITEA2 code: 09026). --------------------¿Por qué la sensibilidad ubicua y la inteligencia ambiental son percibidas por una gran parte de las comunidades académica e industrial como una revolución masiva en el corto plazo? En nuestra opinión, una piedra angular de este pensamiento es el hecho de que la naturaleza última del paradigma de entornos inteligentes no reside en la tecnología en sí misma, sino en una aproximación centrada en las personas. Y es quizá en esta aparente simple concepción donde se halla precisamente el atrevimiento de esta prometedora visión, consolidada en los últimos años con la emergente proliferación de la computación móvil, personal, portable, llevable y sensorial: llegar a todos y a todas partes. Por un lado, esta alcanza nuestras vidas de una manera cercana, minimizando la atención requerida por los usuarios, anticipándose a sus necesidades con el objetivo de redefinir nuestra idea de calidad de experiencia. Por otro lado, esta impacta en todas partes tanto a escala global como personal, con una conectividad expandida entre dispositivos y objetos inteligentes, de un modo ubicuo y dinámico, como una extensión natural del mundo que nos rodea. Conforme a lo anterior, esta tesis doctoral se centra en contribuir en la integración de los avances de ingeniería de redes y software en el ámbito de los espacios y entornos inteligentes ubicuos basados en redes de sensores. Esto se fundamenta en la convergencia de diversos paradigmas de las tecnologías de la información y ciencia de la computación, tales como orientación a servicios y agentes, tecnologías semánticas y de gestión del conocimiento en el contento de la computación ubicua en la Internet de las Cosas. Para este fin, se presentan las aproximaciones nSOM (nano Service-Oriented Middleware) y nSOL (nano Semantics-Oriented Language). En primer lugar, nSOM define una plataforma orientada a servicios para la implementación, despliegue y exposición a la nube de servicios basados en agentes e implementados en red sobre dispositivos heterogéneos de sensores. En segundo lugar, nSOL habilita una abstracción para proporcionar composición ubicua de servicios basada en gestión semántica del conocimiento. La integración de ambas contribuciones conduce a un modelado formal y de implementación práctica de servicios de sensor virtual adaptativos para ecosistemas de inteligencia ambiental. Este trabajo incluye la caracterización del rendimiento del prototipo resultante, basándonos para ello en métricas tales como tamaño de código, tamaño de memoria volátil, sobrecarga de procesamiento, retardo en tiempo de servicio y autonomía de baterías. Los principales fundamentos y resultados discutidos en este ensayo están contextualizados en los siguientes Proyectos de Investigación Europeos: μSWN (FP6 código: IST-034642), DiYSE (ITEA2 código: 08005) y LifeWear (ITEA2 código: 09026).Presidente: Juan Ramón Velasco Pérez; Vocal: Juan Carlos Dueñas; Secretario: Mario Muñoz Organer

A Survey of Limitations and Enhancements of the IPv6 Routing Protocol for Low-power and Lossy Networks: A Focus on Core Operations

Driven by the special requirements of the Low-power and Lossy Networks (LLNs), the IPv6 Routing Protocol for LLNs (RPL) was standardized by the IETF some six years ago to tackle the routing issue in such networks. Since its introduction, however, numerous studies have pointed out that, in its current form, RPL suffers from issues that limit its efficiency and domain of applicability. Thus, several solutions have been proposed in the literature in an attempt to overcome these identified limitations. In this survey, we aim mainly to provide a comprehensive review of these research proposals assessing whether such proposals have succeeded in overcoming the standard reported limitations related to its core operations. Although some of RPL’s weaknesses have been addressed successfully, the study found that the proposed solutions remain deficient in overcoming several others. Hence, the study investigates where such proposals still fall short, the challenges and pitfalls to avoid, thus would help researchers formulate a clear foundation for the development of further successful extensions in future allowing the protocol to be applied more widely

Feature Papers of Drones - Volume I

[EN] The present book is divided into two volumes (Volume I: articles 1–23, and Volume II: articles 24–54) which compile the articles and communications submitted to the Topical Collection ”Feature Papers of Drones” during the years 2020 to 2022 describing novel or new cutting-edge designs, developments, and/or applications of unmanned vehicles (drones). Articles 1–8 are devoted to the developments of drone design, where new concepts and modeling strategies as well as effective designs that improve drone stability and autonomy are introduced. Articles 9–16 focus on the communication aspects of drones as effective strategies for smooth deployment and efficient functioning are required. Therefore, several developments that aim to optimize performance and security are presented. In this regard, one of the most directly related topics is drone swarms, not only in terms of communication but also human-swarm interaction and their applications for science missions, surveillance, and disaster rescue operations. To conclude with the volume I related to drone improvements, articles 17–23 discusses the advancements associated with autonomous navigation, obstacle avoidance, and enhanced flight plannin

Design for energy-efficient and reliable fog-assisted healthcare IoT systems

Cardiovascular disease and diabetes are two of the most dangerous diseases as they are the leading causes of death in all ages. Unfortunately, they cannot be completely cured with the current knowledge and existing technologies. However, they can be effectively managed by applying methods of continuous health monitoring. Nonetheless, it is difficult to achieve a high quality of healthcare with the current health monitoring systems which often have several limitations such as non-mobility support, energy inefficiency, and an insufficiency of advanced services. Therefore, this thesis presents a Fog computing approach focusing on four main tracks, and proposes it as a solution to the existing limitations. In the first track, the main goal is to introduce Fog computing and Fog services into remote health monitoring systems in order to enhance the quality of healthcare. In the second track, a Fog approach providing mobility support in a real-time health monitoring IoT system is proposed. The handover mechanism run by Fog-assisted smart gateways helps to maintain the connection between sensor nodes and the gateways with a minimized latency. Results show that the handover latency of the proposed Fog approach is 10%-50% less than other state-of-the-art mobility support approaches. In the third track, the designs of four energy-efficient health monitoring IoT systems are discussed and developed. Each energy-efficient system and its sensor nodes are designed to serve a specific purpose such as glucose monitoring, ECG monitoring, or fall detection; with the exception of the fourth system which is an advanced and combined system for simultaneously monitoring many diseases such as diabetes and cardiovascular disease. Results show that these sensor nodes can continuously work, depending on the application, up to 70-155 hours when using a 1000 mAh lithium battery. The fourth track mentioned above, provides a Fog-assisted remote health monitoring IoT system for diabetic patients with cardiovascular disease. Via several proposed algorithms such as QT interval extraction, activity status categorization, and fall detection algorithms, the system can process data and detect abnormalities in real-time. Results show that the proposed system using Fog services is a promising approach for improving the treatment of diabetic patients with cardiovascular disease

Power Optimization for Sensor Hubs in Biomedical Applications

The design and development of wearable inertial sensor systems for health monitoring has garnered a huge attention in the scientific community and the industry during the last years. Such platforms have a typical architecture and common building blocks to enable data collection, data processing and feedback restitution. In this thesis we analyze power optimization techniques that can be applied to such systems. When reducing power consumption in a wearable system, different trade-offs have to be inevitably faced. We thus propose software techniques that span from well known duty cycling, frequency scaling, data compression to new paradigm such as radio triggering, heterogeneous multi-core and context aware power management

On Maximizing the Efficiency of Multipurpose WSNs Through Avoidance of Over- or Under-Provisioning of Information

A wireless sensor network (WSN) is a distributed collection of sensor nodes, which are resource constrained and capable of operating with minimal user attendance. The core function of a WSN is to sample physical phenomena and their environment and transport the information of interest, such as current status or events, as required by the application. Furthermore, the operating conditions and/or user requirements of WSNs are often desired to be evolvable, either driven by changes of the monitored phenomena or by the properties of the WSN itself. Consequently, a key objective for setting up/configuring WSNs is to provide the desired information subject to user defined quality requirements (accuracy, reliability, timeliness etc.), while considering their evolvability at the same time. The current state of the art only addresses the functional blocks of sampling and information transport in isolation. The approaches indeed assume the respective other block to be perfect in maintaining the highest possible information contribution. In addition, some of the approaches just concentrate on a few information attributes such as accuracy and ignore other attributes (e.g., reliability, timeliness, etc.). The existing research targeting these blocks usually tries to enhance the information quality requirements (accuracy, reliability, timeliness etc.), regardless of user requirements and use more resources, leading to faster energy depletion. However, we argue that it is not always necessary to provide the highest possible information quality. In fact, it is essential to avoid under or over provision of information in order to save valuable resources such as energy while just satisfying user evolvable requirements. More precisely, we show the interdependence of the different user requirements and how to co-design them in order to tune the level of provisioning. To discern the fundamental issues dictating the tunable co-design in WSNs, this thesis models and co-designs the sampling accuracy, information transport reliability and timeliness, and compares existing techniques. We highlight the key problems of existing techniques and provide solutions to achieve desired application requirements without under or over provisioning of information. Our first research direction is to provide tunable information transport. We show that it is possible to drastically improve efficiency, while satisfying the user evolvable requirements on reliability and timeliness. In this regard, we provide a novel timeliness model and show the tradeoff between the reliability and timeliness. In addition, we show that the reliability and timeliness can work in composition for maximizing efficiency in information transport. Second, we consider the sampling and information transport co-design by just considering the attributes spatial accuracy and transport reliability. We provide a mathematical model in this regard and then show the optimization of sampling and information transport co-design. The approach is based on optimally choosing the number of samples in order to minimize the number of retransmission in the information transport while maintaining the required reliability. Third, we consider representing the physical phenomena accurately and optimize the network performance. Therefore, we jointly model accuracy, reliability and timeliness, and then derive the optimal combination of sampling and information transport. We provide an optimized model to choose the right representative sensor nodes to describe the phenomena and highlight the tunable co-design of sampling and information transport by avoiding over or under provision of information. Our simulation and experimental results show that the proposed tunable co-design supports evolving user requirements, copes with dynamic network properties and outperforms the state of the art solutions