805 resultados para Wireless network


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MoNET e' un emulatore per reti wireless mobili, composto da una suite di software distribuiti. MoNET fornisce a ricercatori e sviluppatori un ambiente virtualizzato controllato per lo sviluppo e il test di applicazioni mobili e protocolli di rete per qualsiasi tipologia di hardware e piattaforma software che possa essere virtualizzata. La natura distribuita di questo emulatore permette di creare scenari di dimensione arbitraria. La rete wireless viene emulata in maniera trasparente, quindi la connettività percepita da ogni nodo virtuale, presenta le stesse caratteristiche di quella fisica emulata.

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Negli ultimi dieci anni si è rinnovata l’esigenza di sviluppare nuove tecnologie legate alla telemedicina, specie a seguito dello sviluppo dei sistemi di telecomunicazione che consentono ad ogni persona di avere a disposizione sistemi portatili, come gli smartphone, sempre connessi e pronti a comunicare. Lo stesso sviluppo si è avuto all’interno dei sistemi sanitari in cui è diventato fondamentale informatizzare le attività ospedaliere per via del contesto demografico a cui si va incontro: invecchiamento della popolazione e aumento del numero di pazienti affetti da malattie croniche. Tutti questi aspetti portano all’attuazione di un cambiamento strategico. Le Body Area Network, fulcro di questo lavoro di tesi, rappresentano la risposta a questa necessità. Si spiegano l'architettura e le tecnologie abilitanti per la realizzazione di queste reti di sensori, gli standard di comunicazione tramite i quali avviene la trasmissione dei dati e come le reti si interfacciano con i pazienti e le strutture sanitarie. Si conclude con una panoramica sui sensori di una BAN e alcuni esempi in commercio.

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With research on Wireless Sensor Networks (WSNs) becoming more and more mature in the past five years, researchers from universities all over the world have set up testbeds of wireless sensor networks, in most cases to test and evaluate the real-world behavior of developed WSN protocol mechanisms. Although these testbeds differ heavily in the employed sensor node types and the general architectural set up, they all have similar requirements with respect to management and scheduling functionalities: as every shared resource, a testbed requires a notion of users, resource reservation features, support for reprogramming and reconfiguration of the nodes, provisions to debug and remotely reset sensor nodes in case of node failures, as well as a solution for collecting and storing experimental data. The TARWIS management architecture presented in this paper targets at providing these functionalities independent from node type and node operating system. TARWIS has been designed as a re-usable management solution for research and/or educational oriented research testbeds of wireless sensor networks, relieving researchers intending to deploy a testbed from the burden to implement their own scheduling and testbed management solutions from scratch.

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We developed UAVNet, a framework for the autonomous deployment of a flying Wireless Mesh Network using small quadrocopter-based Unmanned Aerial Vehicles (UAVs). The flying wireless mesh nodes are automatically interconnected to each other and building an IEEE 802.11s wireless mesh network. The implemented UAVNet prototype is able to autonomously interconnect two end systems by setting up an airborne relay, consisting of one or several flying wireless mesh nodes. The developed software includes basic functionality to control the UAVs and to setup, deploy, manage, and monitor a wireless mesh network. Our evaluations have shown that UAVNet can significantly improve network performance.

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Tracking or target localization is used in a wide range of important tasks from knowing when your flight will arrive to ensuring your mail is received on time. Tracking provides the location of resources enabling solutions to complex logistical problems. Wireless Sensor Networks (WSN) create new opportunities when applied to tracking, such as more flexible deployment and real-time information. When radar is used as the sensing element in a tracking WSN better results can be obtained; because radar has a comparatively larger range both in distance and angle to other sensors commonly used in WSNs. This allows for less nodes deployed covering larger areas, saving money. In this report I implement a tracking WSN platform similar to what was developed by Lim, Wang, and Terzis. This consists of several sensor nodes each with a radar, a sink node connected to a host PC, and a Matlab© program to fuse sensor data. I have re-implemented their experiment with my WSN platform for tracking a non-cooperative target to verify their results and also run simulations to compare. The results of these tests are discussed and some future improvements are proposed.

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This paper studies the energy-efficiency and service characteristics of a recently developed energy-efficient MAC protocol for wireless sensor networks in simulation and on a real sensor hardware testbed. This opportunity is seized to illustrate how simulation models can be verified by cross-comparing simulation results with real-world experiment results. The paper demonstrates that by careful calibration of simulation model parameters, the inevitable gap between simulation models and real-world conditions can be reduced. It concludes with guidelines for a methodology for model calibration and validation of sensor network simulation models.

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Over the past several years the topics of energy consumption and energy harvesting have gained significant importance as a means for improved operation of wireless sensor and mesh networks. Energy-awareness of operation is especially relevant for application scenarios from the domain of environmental monitoring in hard to access areas. In this work we reflect upon our experiences with a real-world deployment of a wireless mesh network. In particular, a comprehensive study on energy measurements collected over several weeks during the summer and the winter period in a network deployment in the Swiss Alps is presented. Energy performance is monitored and analysed for three system components, namely, mesh node, battery and solar panel module. Our findings cover a number of aspects of energy consumption, including the amount of load consumed by a mesh node, the amount of load harvested by a solar panel module, and the dependencies between these two. With our work we aim to shed some light on energy-aware network operation and to help both users and developers in the planning and deployment of a new wireless (mesh) network for environmental research.