111 research outputs found

    A comprehensive survey of wireless body area networks on PHY, MAC, and network layers solutions

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    Recent advances in microelectronics and integrated circuits, system-on-chip design, wireless communication and intelligent low-power sensors have allowed the realization of a Wireless Body Area Network (WBAN). A WBAN is a collection of low-power, miniaturized, invasive/non-invasive lightweight wireless sensor nodes that monitor the human body functions and the surrounding environment. In addition, it supports a number of innovative and interesting applications such as ubiquitous healthcare, entertainment, interactive gaming, and military applications. In this paper, the fundamental mechanisms of WBAN including architecture and topology, wireless implant communication, low-power Medium Access Control (MAC) and routing protocols are reviewed. A comprehensive study of the proposed technologies for WBAN at Physical (PHY), MAC, and Network layers is presented and many useful solutions are discussed for each layer. Finally, numerous WBAN applications are highlighted

    Experiences from building an Outdoor Testbed for Community Wireless Networks

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    Abstract-Community Wireless Networks are an emerging networking model, offering people the opportunity to build and manage their own network without being dependent on telecom operators. The strength of this type of networks lies in the involvement of the whole community, as each person benefitting from the community wireless network somehow contributes to the design, deployment and maintenance of the network. This model has resulted in large community wireless networks growing all over the world, connecting people in the local communities to each other and the Internet. Because of the rising popularity and demonstrated success, researchers are also becoming more interested in community networks. This paper presents guidelines and experiences from creating an outdoor testbed targeted at community wireless networks, based on experience and feedback from community network members

    Alternative Network Deployments: Taxonomy, Characterization, Technologies, and Architectures

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    This document presents a taxonomy of a set of "Alternative Network Deployments" that emerged in the last decade with the aim of bringing Internet connectivity to people or providing a local communication infrastructure to serve various complementary needs and objectives. They employ architectures and topologies different from those of mainstream networks and rely on alternative governance and business models. The document also surveys the technologies deployed in these networks, and their differing architectural characteristics, including a set of definitions and shared properties. The classification considers models such as Community Networks, Wireless Internet Service Providers (WISPs), networks owned by individuals but leased out to network operators who use them as a low-cost medium to reach the underserved population, networks that provide connectivity by sharing wireless resources of the users, and rural utility cooperatives

    Design of energy efficient topologies for wireless on-body channel

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    Advanced applications in the area of remote health monitoring can be realized by Wireless Body Area Networks (WBANs). This paper investigates the physical propagation channel at 2.45 GHz near real humans and presents an application for cross-layer design in order to optimize the energy consumption of single-hop and multi-hop network topologies. The characterization of the physical layer is an important element in the development of a WBAN. Propagation measurements are performed on real humans in a multipath environment and propagation models are proposed. As a cross-layer application, the proposed path loss models are used to evaluate the energy efficiency of different network topologies. The paper investigates which topology is the most energy efficient in WBANs: single-hop or multi-hop communication

    Advances in wireless community networks with the community-lab testbed

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    Beyond traditional telecom providers, citizens and organizations pool their own resources and coordinate in order to build local network infrastructures to address the digital divide in many parts of the world. These crowdsourced network infrastructures can be self-organized and shared by a community for the collective benefit of its members. Several of these networks have developed open, free, and neutral agreements, and are governed as a common-pool resource: community networks. These are built using a variety of commodity wireless hardware (e.g., Wi-Fi long-range point-to-point links, Wi-Fi and GSM access points, and mesh networks), sometimes optical fiber links, heterogeneous nodes, routing protocols, and applications. A group of researchers, developers, and community networks developed the Community-Lab testbed, and for the last five years have worked together to overcome obstacles, improve the technologies, tools, and operational models being used, as well as model best practices for more effective and sustainable community networks. This article presents the challenges for experimentation, the testbeds built, results, lessons learned, and the impact of that work to place wireless community networks as one sustainable way toward an Internet accessible to all.Peer ReviewedPostprint (author's final draft

    Continuous athlete monitoring in challenging cycling environments using IoT technologiesis

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    Internet of Things (IoT)-based solutions for sport analytics aim to improve performance, coaching, and strategic insights. These factors are especially relevant in cycling, where real-time data should be available anytime, anywhere, even in remote areas where there are no infrastructure-based communication technologies (e.g., LTE and Wi-Fi). In this article, we present an experience report on the use of state-of-the-art IoT technologies in cycling, where a group of cyclists can form a reliable and energy efficient mesh network to collect and process sensor data in real-time, such as heart rate, speed, and location. This data is analyzed in real-time to estimate the performance of each rider and derive instantaneous feedback. Our solution is the first to combine a local body area network to gather the sensor data from the cyclist and a 6TiSCH network to form a multihop long-range wireless sensor network in order to provide each bicycle with connectivity to the sink (e.g., a moving car following the cyclists). In this article, we present a detailed technical description of this solution, describing its requirements, options, and technical challenges. In order to assess such a deployment, we present a large publicly available data-set from different real-world cycling scenarios (mountain road cycle racing and cyclo-cross) which characterizes the performance of the approach, demonstrating its feasibility and evidencing its relevance and promising possibilities in a cycling context for providing low-power communication with reliable performance

    City of things : enabling resource provisioning in smart cities

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    In the last few years, traffic over wireless networks has been increasing exponentially due to the impact of IoT. IoT is transforming a wide range of services in different domains of urban life, such as environmental monitoring, home automation, and public transportation. The so-called smart city applications will introduce a set of stringent requirements, such as low latency and high mobility, since services must be allocated and instantiated on demand, simultaneously, close to multiple devices at different locations. Efficient resource provisioning functionalities are needed to address these demanding constraints introduced by smart city applications while minimizing resource costs and maximizing QoS. In this article, the CoT framework is presented, which provides not only data collection and analysis functionalities but also automated resource provisioning mechanisms for future smart city applications. CoT is deployed as a smart city test-bed in Antwerp, Belgium, which allows researchers and developers to easily set up and validate IoT experiments. A smart city use case of air quality monitoring through the deployment of air quality sensors in moving cars is presented showing the full applicability of the CoT framework for a flexible and scalable resource provisioning in the smart city ecosystem

    Time series analysis to predict link quality of wireless community networks

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    Community networks have emerged under the mottosCommunity networks have emerged under the mottos “break the strings that are limiting you”, “don't buy the network, be the network” or “a free net for everyone is possible”. Such networks create a measurable social impact as they provide to the community the right and opportunity of communication. As any other network that mixes wired and wireless links, the routing protocol must face several challenges that arise from the unreliable nature of the wireless medium. Link quality tracking helps the routing layer to select links that maximize the delivery rate and minimize traffic congestion. Moreover, link quality prediction has proved to be a technique that surpasses link quality tracking by foreseeing which links are more likely to change its quality. In this work, we focus on link quality prediction by means of a time series analysis. We apply this prediction technique in the routing layer of large-scale, distributed, and decentralized networks. We demonstrate that it is possible to accurately predict the link quality in 98% of the instances, both in the short and the long terms. Particularly, we analyse the behaviour of the links globally to identify the best prediction algorithm and metric, the impact of lag windows in the results, the prediction accuracy some time steps ahead into the future, the degradation of prediction over time, and the correlation of prediction with topological features. Moreover, we also analyse the behaviour of links individually to identify the variability of link quality prediction between links, and the variability of link quality prediction over time. Finally, we also present an optimized prediction method that considers the knowledge about the expected link quality values.Peer ReviewedPostprint (author's final draft
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