Rural Wireless Mesh Network: A Design Methodology

Wireless Mesh Network is presented as an appealing solution for bridging the digital divide between developed and under-developed regions. But the planning and deployment of these networks are not just a technical matter, since the success depends on many other factors tied to the related region. Although we observe some deployments, to ensure usefulness and sustainability, there is still a need of concrete design process model and proper network planning approach for rural regions, especially in Sub-Saharan Africa. This paper presents a design methodology to provide network connectivity from a landline node in a rural region at very low cost. We propose a methodology composed of ten steps, starting by a deep analysis of the region in order to identify relevant constraints and useful applications to sustain local activities and communication. Approach for planning the physical architecture of the network is based on an indoor-outdoor deployment for reducing the overall cost of the network.Comment: 9 pages, 2 figures, 3 table

Dynamic and heterogeneous wireless sensor network for virtual instrumentation services

En el presente Trabajo Fin de Master se ha llevado a cabo el desarrollo de un sistema orientado a la adquisición de información sensorial, a través del uso de redes de sensores inalámbricas (WSN, del inglés Wireless Sensor Networks), de un sistema dinámico cuyo comportamiento se desea caracterizar. Para la gestión de la información de los sensores heterogéneos presentes en la red se han aplicado los conceptos de SOA (Service Oriented Architecture) a dicha red inalámbrica, de manera que cada uno de los sensores presentes en la red se trata como un servicio de medida. La arquitectura propuesta incorpora un mecanismo de "Plug & Play" para la reconfiguración dinámica de la red así como un proceso de composición de servicios que permite la creación de los denominados instrumentos virtuales a través de la asociación de diferentes sensores. Estos instrumentos virtuales agrupan las capacidades de varios sensores heterogeneos de forma que pueden ofrecer al usuario final información de alto nivel complementada con indicios de calidad de dicha información. Para la obtención de este sistema, las tareas que se han llevado a cabo en este trabajo han sido: se han realizado estudios previos de la utilizacion actual de las redes de sensores inalámbricas y de las arquitecturas SOA aplicadas a WSN. Se ha diseñado la arquitectura de la WSN más adecuada para esta sistema así como el mecanismo "Plug & Play" necesario para el descubrimiento de dispositivos y servicios. Se han estudiado y evaluado los criterios más adecuados para la agrupación de sensores para formar el instrumento virtual de forma automática y transparente. Por último, se ha evaluado la validez de la arquitectura propuesta por medio de su aplicación en un caso concreto en el campo de la logística, en particular, en la supervisión de artículos perecederos. Para ello, ha sido necesario diseñar y definir previamente los módulos de sofware necesarios para la implementación del sistema

Wi-Fi Sensing Algorithms Utilizing Zigbee RF Receiver for Use in Emergency Communications Mesh

This thesis examines a low-power Wi-Fi sensing wake-up controller for an emergency communications mesh network; the goal of the research study is to progressively develop a prototype system that could be used in a live environment. Wireless network protocols are reviewed, in addition to a limited view of cluster analysis, in order to introduce relevant receiver concepts crucial to understanding this study. Algorithms for system implementation are developed, and pseudocode, designed to be configurable and platform-independent, is given for each. The system’s design goals are identified, followed by a discussion on approaches and optimizations in order to maximize the system’s usefulness. An example hardware configuration is given, in conjunction with an analysis of benefits and a discussion of drawbacks for several design options. Finally, the prototype is tested according to design goals in order to establish its feasibility. The results demonstrate that the prototype meets the proposed design goals. The implications of these findings include low power optimization for wireless technologies and machine learning techniques for wireless detection

Survey and Evaluation of Advanced Mobility Management Schemes in the Host Identity Layer

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Automated linear regression tools improve RSSI WSN localization in multipath indoor environment

Received signal strength indication (RSSI)-based localization is emerging in wireless sensor networks (WSNs). Localization algorithms need to include the physical and hardware limitations of RSSI measurements in order to give more accurate results in dynamic real-life indoor environments. In this study, we use the Interdisciplinary Institute for Broadband Technology real-life test bed and present an automated method to optimize and calibrate the experimental data before offering them to a positioning engine. In a preprocessing localization step, we introduce a new method to provide bounds for the range, thereby further improving the accuracy of our simple and fast 2D localization algorithm based on corrected distance circles. A maximum likelihood algorithm with a mean square error cost function has a higher position error median than our algorithm. Our experiments further show that the complete proposed algorithm eliminates outliers and avoids any manual calibration procedure

Efficient and Secure Key Distribution Protocol for Wireless Sensor Networks

Modern wireless sensor networks have adopted the IEEE 802.15.4 standard. This standard defines the first two layers, the physical and medium access control layers; determines the radio wave used for communication; and defines the 128-bit advanced encryption standard (AES-128) for encrypting and validating the transmitted data. However, the standard does not specify how to manage, store, or distribute the encryption keys. Many solutions have been proposed to address this problem, but the majority are impractical in resource-constrained devices such as wireless sensor nodes or cause degradation of other metrics. Therefore, we propose an efficient and secure key distribution protocol that is simple, practical, and feasible to implement on resource-constrained wireless sensor nodes. We conduct simulations and hardware implementations to analyze our work and compare it to existing solutions based on different metrics such as energy consumption, storage overhead, key connectivity, replay attack, man-in-the-middle attack, and resiliency to node capture attack. Our findings show that the proposed protocol is secure and more efficient than other solutions.http://dx.doi.org/10.3390/s1810356

Crowdsensing in Smart Cities: Overview, Platforms, and Environment Sensing Issues

[EN] Evidence shows that Smart Cities are starting to materialise in our lives through the gradual introduction of the Internet of Things (IoT) paradigm. In this scope, crowdsensing emerges as a powerful solution to address environmental monitoring, allowing to control air pollution levels in crowded urban areas in a distributed, collaborative, inexpensive and accurate manner. However, even though technology is already available, such environmental sensing devices have not yet reached consumers. In this paper, we present an analysis of candidate technologies for crowdsensing architectures, along with the requirements for empowering users with air monitoring capabilities. Specifically, we start by providing an overview of the most relevant IoT architectures and protocols. Then, we present the general design of an off-the-shelf mobile environmental sensor able to cope with air quality monitoring requirements; we explore different hardware options to develop the desired sensing unit using readily available devices, discussing the main technical issues associated with each option, thereby opening new opportunities in terms of environmental monitoring programs.This work was partially supported by the Ministerio de Economia y Competitividad, Programa Estatal de Investigacion, Desarrollo e Innovacion Orientada a los Retos de la Sociedad, Proyectos I+D+I 2014, Spain, under Grant TEC2014-52690-R, the Generalitat Valenciana, Spain, the Secretaria Nacional de Educacion Superior, Ciencia, Tecnologia e Innovacion del Ecuador (SENESCYT), and the Universidad de Cuenca.Alvear-Alvear, Ó.; Tavares De Araujo Cesariny Calafate, CM.; Cano, J.; Manzoni, P. (2018). Crowdsensing in Smart Cities: Overview, Platforms, and Environment Sensing Issues. Sensors. 18(2):1-28. https://doi.org/10.3390/s18020460S12818

Fog computing for sustainable smart cities: a survey

The Internet of Things (IoT) aims to connect billions of smart objects to the Internet, which can bring a promising future to smart cities. These objects are expected to generate large amounts of data and send the data to the cloud for further processing, specially for knowledge discovery, in order that appropriate actions can be taken. However, in reality sensing all possible data items captured by a smart object and then sending the complete captured data to the cloud is less useful. Further, such an approach would also lead to resource wastage (e.g. network, storage, etc.). The Fog (Edge) computing paradigm has been proposed to counterpart the weakness by pushing processes of knowledge discovery using data analytics to the edges. However, edge devices have limited computational capabilities. Due to inherited strengths and weaknesses, neither Cloud computing nor Fog computing paradigm addresses these challenges alone. Therefore, both paradigms need to work together in order to build an sustainable IoT infrastructure for smart cities. In this paper, we review existing approaches that have been proposed to tackle the challenges in the Fog computing domain. Specifically, we describe several inspiring use case scenarios of Fog computing, identify ten key characteristics and common features of Fog computing, and compare more than 30 existing research efforts in this domain. Based on our review, we further identify several major functionalities that ideal Fog computing platforms should support and a number of open challenges towards implementing them, so as to shed light on future research directions on realizing Fog computing for building sustainable smart cities