Rate-Distortion Classification for Self-Tuning IoT Networks

Many future wireless sensor networks and the Internet of Things are expected to follow a software defined paradigm, where protocol parameters and behaviors will be dynamically tuned as a function of the signal statistics. New protocols will be then injected as a software as certain events occur. For instance, new data compressors could be (re)programmed on-the-fly as the monitored signal type or its statistical properties change. We consider a lossy compression scenario, where the application tolerates some distortion of the gathered signal in return for improved energy efficiency. To reap the full benefits of this paradigm, we discuss an automatic sensor profiling approach where the signal class, and in particular the corresponding rate-distortion curve, is automatically assessed using machine learning tools (namely, support vector machines and neural networks). We show that this curve can be reliably estimated on-the-fly through the computation of a small number (from ten to twenty) of statistical features on time windows of a few hundreds samples

EC-CENTRIC: An Energy- and Context-Centric Perspective on IoT Systems and Protocol Design

The radio transceiver of an IoT device is often where most of the energy is consumed. For this reason, most research so far has focused on low power circuit and energy efficient physical layer designs, with the goal of reducing the average energy per information bit required for communication. While these efforts are valuable per se, their actual effectiveness can be partially neutralized by ill-designed network, processing and resource management solutions, which can become a primary factor of performance degradation, in terms of throughput, responsiveness and energy efficiency. The objective of this paper is to describe an energy-centric and context-aware optimization framework that accounts for the energy impact of the fundamental functionalities of an IoT system and that proceeds along three main technical thrusts: 1) balancing signal-dependent processing techniques (compression and feature extraction) and communication tasks; 2) jointly designing channel access and routing protocols to maximize the network lifetime; 3) providing self-adaptability to different operating conditions through the adoption of suitable learning architectures and of flexible/reconfigurable algorithms and protocols. After discussing this framework, we present some preliminary results that validate the effectiveness of our proposed line of action, and show how the use of adaptive signal processing and channel access techniques allows an IoT network to dynamically tune lifetime for signal distortion, according to the requirements dictated by the application

Wireless sensor networks with QoS for e-health and e-emergency applications

http://www.informatik.uni-trier.de/%7Eley/db/conf/icsoft/ehst2008.htmlMost body sensor networks (BSN) only offer best-effort service delivery, which may compromise the successful operation of emergency healthcare (e-emergency) applications. Due to its real-time nature, e-emergency systems must provide quality of service (QoS) support, in order to provide a pervasive, valuable and fully reliable assistance to patients with risk abnormalities. But what is the real meaning of QoS support within the e-emergency context? What benefits can QoS mechanisms bring to e-emergency systems, and how are they being deployed? In order to answer these questions, this paper firstly discusses the need of QoS in personal wireless healthcare systems, and then presents an overview of such systems with QoS. A case-study requiring QoS support, intended to be deployed in a healthcare unit, is presented, as well as an asynchronous medium access TDMA-based model

Development of a Personal Area Network for biomedical measurements for Internet of Things (IoT)

Internet of Things is a set of ever growing technologies and specialized devices that are increasingly influential in our everyday lives. IoT is all about connecting the physical and the digital worlds in one enabling the collection of real world data and the automation of processes. IoT turns your typical device into an smart, programmable one, more capable of interacting with humans and thus enabling users to better understand their surroundings through the data collected. This data collected by the IoT devices can then be used on all kinds of contemporary services and applications. This project aims to implement an IoT application for biomedical measurements, consisting of a WSN(Wireless Sensor Network), where three sensor nodes will collect physical world measurements. This collected information will be transmitted to a routing device, that further send the information to the internet, where the user will be able to access the data in real time through a web browser and schedule some events. In order to carry out the described scenario, a Raspberry Pi and four Zolertia Z1, three working as sensor nodes and one working as a routing node were used. The Z1 mote is powered by a low power MSP430 class microcontroller. Contiki was the operating system chosen to run the sensor nodes. In this scenario, Raspberry Pi plays the role of a router, enabling the connection of the WSN network and the internet. To send the information from the nodes, a high-speed program was developed, aiming to beat the default restrictions that Contiki OS imposes on high-speed networks. The transport protocol chosen is UDP. On the receiving end, an UDP server and a python script were developed with the intent to send the collected data to our ASP.NET web server and mySQL database. Finally connectivity tests and network speed tests of the deployed system are presented

Wearable and Implantable Wireless Sensor Network Solutions for Healthcare Monitoring

Wireless sensor network (WSN) technologies are considered one of the key research areas in computer science and the healthcare application industries for improving the quality of life. The purpose of this paper is to provide a snapshot of current developments and future direction of research on wearable and implantable body area network systems for continuous monitoring of patients. This paper explains the important role of body sensor networks in medicine to minimize the need for caregivers and help the chronically ill and elderly people live an independent life, besides providing people with quality care. The paper provides several examples of state of the art technology together with the design considerations like unobtrusiveness, scalability, energy efficiency, security and also provides a comprehensive analysis of the various benefits and drawbacks of these systems. Although offering significant benefits, the field of wearable and implantable body sensor networks still faces major challenges and open research problems which are investigated and covered, along with some proposed solutions, in this paper

A Survey on FPGA-Based Sensor Systems: Towards Intelligent and Reconfigurable Low-Power Sensors for Computer Vision, Control and Signal Processing

The current trend in the evolution of sensor systems seeks ways to provide more accuracy and resolution, while at the same time decreasing the size and power consumption. The use of Field Programmable Gate Arrays (FPGAs) provides specific reprogrammable hardware technology that can be properly exploited to obtain a reconfigurable sensor system. This adaptation capability enables the implementation of complex applications using the partial reconfigurability at a very low-power consumption. For highly demanding tasks FPGAs have been favored due to the high efficiency provided by their architectural flexibility (parallelism, on-chip memory, etc.), reconfigurability and superb performance in the development of algorithms. FPGAs have improved the performance of sensor systems and have triggered a clear increase in their use in new fields of application. A new generation of smarter, reconfigurable and lower power consumption sensors is being developed in Spain based on FPGAs. In this paper, a review of these developments is presented, describing as well the FPGA technologies employed by the different research groups and providing an overview of future research within this field.The research leading to these results has received funding from the Spanish Government and European FEDER funds (DPI2012-32390), the Valencia Regional Government (PROMETEO/2013/085) and the University of Alicante (GRE12-17)

Intelligent Sensor Networks

In the last decade, wireless or wired sensor networks have attracted much attention. However, most designs target general sensor network issues including protocol stack (routing, MAC, etc.) and security issues. This book focuses on the close integration of sensing, networking, and smart signal processing via machine learning. Based on their world-class research, the authors present the fundamentals of intelligent sensor networks. They cover sensing and sampling, distributed signal processing, and intelligent signal learning. In addition, they present cutting-edge research results from leading experts

Wireless Sensor Networks

The aim of this book is to present few important issues of WSNs, from the application, design and technology points of view. The book highlights power efficient design issues related to wireless sensor networks, the existing WSN applications, and discusses the research efforts being undertaken in this field which put the reader in good pace to be able to understand more advanced research and make a contribution in this field for themselves. It is believed that this book serves as a comprehensive reference for graduate and undergraduate senior students who seek to learn latest development in wireless sensor networks

Runtime Hardware Reconfiguration in Wireless Sensor Networks for Condition Monitoring

The integration of miniaturized heterogeneous electronic components has enabled the deployment of tiny sensing platforms empowered by wireless connectivity known as wireless sensor networks. Thanks to an optimized duty-cycled activity, the energy consumption of these battery-powered devices can be reduced to a level where several years of operation is possible. However, the processing capability of currently available wireless sensor nodes does not scale well with the observation of phenomena requiring a high sampling resolution. The large amount of data generated by the sensors cannot be handled efficiently by low-power wireless communication protocols without a preliminary filtering of the information relevant for the application. For this purpose, energy-efficient, flexible, fast and accurate processing units are required to extract important features from the sensor data and relieve the operating system from computationally demanding tasks. Reconfigurable hardware is identified as a suitable technology to fulfill these requirements, balancing implementation flexibility with performance and energy-efficiency. While both static and dynamic power consumption of field programmable gate arrays has often been pointed out as prohibitive for very-low-power applications, recent programmable logic chips based on non-volatile memory appear as a potential solution overcoming this constraint. This thesis first verifies this assumption with the help of a modular sensor node built around a field programmable gate array based on Flash technology. Short and autonomous duty-cycled operation combined with hardware acceleration efficiently drop the energy consumption of the device in the considered context. However, Flash-based devices suffer from restrictions such as long configuration times and limited resources, which reduce their suitability for complex processing tasks. A template of a dynamically reconfigurable architecture built around coarse-grained reconfigurable function units is proposed in a second part of this work to overcome these issues. The module is conceived as an overlay of the sensor node FPGA increasing the implementation flexibility and introducing a standardized programming model. Mechanisms for virtual reconfiguration tailored for resource-constrained systems are introduced to minimize the overhead induced by this genericity. The definition of this template architecture leaves room for design space exploration and application- specific customization. Nevertheless, this aspect must be supported by appropriate design tools which facilitate and automate the generation of low-level design files. For this purpose, a software tool is introduced to graphically configure the architecture and operation of the hardware accelerator. A middleware service is further integrated into the wireless sensor network operating system to bridge the gap between the hardware and the design tools, enabling remote reprogramming and scheduling of the hardware functionality at runtime. At last, this hardware and software toolchain is applied to real-world wireless sensor network deployments in the domain of condition monitoring. This category of applications often require the complex analysis of signals in the considered range of sampling frequencies such as vibrations or electrical currents, making the proposed system ideally suited for the implementation. The flexibility of the approach is demonstrated by taking examples with heterogeneous algorithmic specifications. Different data processing tasks executed by the sensor node hardware accelerator are modified at runtime according to application requests

A Review on Provisioning Quality of Service of Wireless Telemedicine for E-Health Services

In general, on-line medical consultation reduces time required for medical consultation induces improvement in the quality and efficiency of healthcare services. All major types of current e-health applications such as ECG, X-ray, video, diagnosis images and other common applications have been included in the scope of the study. In addition, the provision of Quality of Service (QoS) for the application of specific healthcare services in e-health, the scheme of priority for e-health services and the support of QoS in wireless networks and techniques or methods for IEEE 802.11 to guarantee the provision of QoS has also been assessed. In e-health, medical services in remote locations such as rural healthcare centers, ambulances, ships as well as home healthcare services can be supported through the applications of e-health services such as medical databases, electronic health records and the routing of text, audio, video and images. Given this, an adaptive resource allocation for a wireless network with multiple service types and multiple priorities have been proposed. For the provision of an acceptable QoS level to users of e-health services, prioritization is an important criterion in a multi-traffic network. The requirement for QoS provisioning in wireless broadband medical networks have paved the pathway for bandwidth requirements and the real-time or live transmission of medical applications. From the study, good performance of the proposed scheme has been validated by the results obtained. The proposed wireless network is capable of handling medical applications for both normal and life-threatening conditions as characterized by the level of emergencies. In addition, the bandwidth allocation and admission control algorithm for IEEE 802.16- based design specifically for wireless telemedicine/e-health services have also been presented in the study. It has been concluded that under busy traffic conditions, the proposed architecture can used as a feasible and reliable infrastructure network for telemedicine