750 resultados para Underwater sensor networks
Resumo:
Reliable electronic systems, namely a set of reliable electronic devices connected to each other and working correctly together for the same functionality, represent an essential ingredient for the large-scale commercial implementation of any technological advancement. Microelectronics technologies and new powerful integrated circuits provide noticeable improvements in performance and cost-effectiveness, and allow introducing electronic systems in increasingly diversified contexts. On the other hand, opening of new fields of application leads to new, unexplored reliability issues. The development of semiconductor device and electrical models (such as the well known SPICE models) able to describe the electrical behavior of devices and circuits, is a useful means to simulate and analyze the functionality of new electronic architectures and new technologies. Moreover, it represents an effective way to point out the reliability issues due to the employment of advanced electronic systems in new application contexts. In this thesis modeling and design of both advanced reliable circuits for general-purpose applications and devices for energy efficiency are considered. More in details, the following activities have been carried out: first, reliability issues in terms of security of standard communication protocols in wireless sensor networks are discussed. A new communication protocol is introduced, allows increasing the network security. Second, a novel scheme for the on-die measurement of either clock jitter or process parameter variations is proposed. The developed scheme can be used for an evaluation of both jitter and process parameter variations at low costs. Then, reliability issues in the field of “energy scavenging systems” have been analyzed. An accurate analysis and modeling of the effects of faults affecting circuit for energy harvesting from mechanical vibrations is performed. Finally, the problem of modeling the electrical and thermal behavior of photovoltaic (PV) cells under hot-spot condition is addressed with the development of an electrical and thermal model.
Resumo:
Wireless Sensor Networks (WSNs) offer a new solution for distributed monitoring, processing and communication. First of all, the stringent energy constraints to which sensing nodes are typically subjected. WSNs are often battery powered and placed where it is not possible to recharge or replace batteries. Energy can be harvested from the external environment but it is a limited resource that must be used efficiently. Energy efficiency is a key requirement for a credible WSNs design. From the power source's perspective, aggressive energy management techniques remain the most effective way to prolong the lifetime of a WSN. A new adaptive algorithm will be presented, which minimizes the consumption of wireless sensor nodes in sleep mode, when the power source has to be regulated using DC-DC converters. Another important aspect addressed is the time synchronisation in WSNs. WSNs are used for real-world applications where physical time plays an important role. An innovative low-overhead synchronisation approach will be presented, based on a Temperature Compensation Algorithm (TCA). The last aspect addressed is related to self-powered WSNs with Energy Harvesting (EH) solutions. Wireless sensor nodes with EH require some form of energy storage, which enables systems to continue operating during periods of insufficient environmental energy. However, the size of the energy storage strongly restricts the use of WSNs with EH in real-world applications. A new approach will be presented, which enables computation to be sustained during intermittent power supply. The discussed approaches will be used for real-world WSN applications. The first presented scenario is related to the experience gathered during an European Project (3ENCULT Project), regarding the design and implementation of an innovative network for monitoring heritage buildings. The second scenario is related to the experience with Telecom Italia, regarding the design of smart energy meters for monitoring the usage of household's appliances.
Resumo:
This paper examines the accuracy of software-based on-line energy estimation techniques. It evaluates today’s most widespread energy estimation model in order to investigate whether the current methodology of pure software-based energy estimation running on a sensor node itself can indeed reliably and accurately determine its energy consumption - independent of the particular node instance, the traffic load the node is exposed to, or the MAC protocol the node is running. The paper enhances today’s widely used energy estimation model by integrating radio transceiver switches into the model, and proposes a methodology to find the optimal estimation model parameters. It proves by statistical validation with experimental data that the proposed model enhancement and parameter calibration methodology significantly increases the estimation accuracy.
Resumo:
This paper presents our ongoing work on enterprise IT integration of sensor networks based on the idea of service descriptions and applying linked data principles to them. We argue that using linked service descriptions facilitates a better integration of sensor nodes into enterprise IT systems and allows SOA principles to be used within the enterprise IT and within the sensor network itself.
Resumo:
Linking the physical world to the Internet, also known as the Internet of Things, has increased available information and services in everyday life and in the Enterprise world. In Enterprise IT an increasing number of communication is done between IT backend systems and small IoT devices, for example sensor networks or RFID readers. This introduces some challenges in terms of complexity and integration. We are working on the integration of IoT devices into Enterprise IT by leveraging SOA techniques and Semantic Web technologies. We present a SOA based integration platform for connecting WSNs and large enterprise business processes. For ensuring interoperability our platform is based on Linked Services. These are thoroughly described, machine-readable, machine-reasonable service descriptions.
Resumo:
For smart cities applications, a key requirement is to disseminate data collected from both scalar and multimedia wireless sensor networks to thousands of end-users. Furthermore, the information must be delivered to non-specialist users in a simple, intuitive and transparent manner. In this context, we present Sensor4Cities, a user-friendly tool that enables data dissemination to large audiences, by using using social networks, or/and web pages. The user can request and receive monitored information by using social networks, e.g., Twitter and Facebook, due to their popularity, user-friendly interfaces and easy dissemination. Additionally, the user can collect or share information from smart cities services, by using web pages, which also include a mobile version for smartphones. Finally, the tool could be configured to periodically monitor the environmental conditions, specific behaviors or abnormal events, and notify users in an asynchronous manner. Sensor4Cities improves the data delivery for individuals or groups of users of smart cities applications and encourages the development of new user-friendly services.
Resumo:
This paper considers a framework where data from correlated sources are transmitted with the help of network coding in ad hoc network topologies. The correlated data are encoded independently at sensors and network coding is employed in the intermediate nodes in order to improve the data delivery performance. In such settings, we focus on the problem of reconstructing the sources at decoder when perfect decoding is not possible due to losses or bandwidth variations. We show that the source data similarity can be used at decoder to permit decoding based on a novel and simple approximate decoding scheme. We analyze the influence of the network coding parameters and in particular the size of finite coding fields on the decoding performance. We further determine the optimal field size that maximizes the expected decoding performance as a trade-off between information loss incurred by limiting the resolution of the source data and the error probability in the reconstructed data. Moreover, we show that the performance of the approximate decoding improves when the accuracy of the source model increases even with simple approximate decoding techniques. We provide illustrative examples showing how the proposed algorithm can be deployed in sensor networks and distributed imaging applications.
Resumo:
The Internet of Things (IoT) is attracting considerable attention from the universities, industries, citizens and governments for applications, such as healthcare, environmental monitoring and smart buildings. IoT enables network connectivity between smart devices at all times, everywhere, and about everything. In this context, Wireless Sensor Networks (WSNs) play an important role in increasing the ubiquity of networks with smart devices that are low-cost and easy to deploy. However, sensor nodes are restricted in terms of energy, processing and memory. Additionally, low-power radios are very sensitive to noise, interference and multipath distortions. In this context, this article proposes a routing protocol based on Routing by Energy and Link quality (REL) for IoT applications. To increase reliability and energy-efficiency, REL selects routes on the basis of a proposed end-to-end link quality estimator mechanism, residual energy and hop count. Furthermore, REL proposes an event-driven mechanism to provide load balancing and avoid the premature energy depletion of nodes/networks. Performance evaluations were carried out using simulation and testbed experiments to show the impact and benefits of REL in small and large-scale networks. The results show that REL increases the network lifetime and services availability, as well as the quality of service of IoT applications. It also provides an even distribution of scarce network resources and reduces the packet loss rate, compared with the performance of well-known protocols.
Resumo:
Wireless mobile sensor networks are enlarging the Internet of Things (IoT) portfolio with a huge number of multimedia services for smart cities. Safety and environmental monitoring multimedia applications will be part of the Smart IoT systems, which aim to reduce emergency response time, while also predicting hazardous events. In these mobile and dynamic (possible disaster) scenarios, opportunistic routing allows routing decisions in a completely distributed manner, by using a hop- by-hop route decision based on protocol-specific characteristics, and a predefined end-to-end path is not a reliable solution. This enables the transmission of video flows of a monitored area/object with Quality of Experience (QoE) support to users, headquarters or IoT platforms. However, existing approaches rely on a single metric to make the candidate selection rule, including link quality or geographic information, which causes a high packet loss rate, and reduces the video perception from the human standpoint. This article proposes a cross-layer Link quality and Geographical-aware Opportunistic routing protocol (LinGO), which is designed for video dissemination in mobile multimedia IoT environments. LinGO improves routing decisions using multiple metrics, including link quality, geographic loca- tion, and energy. The simulation results show the benefits of LinGO compared with well-known routing solutions for video transmission with QoE support in mobile scenarios.
Resumo:
The evolution of wireless access technologies and mobile devices, together with the constant demand for video services, has created new Human-Centric Multimedia Networking (HCMN) scenarios. However, HCMN poses several challenges for content creators and network providers to deliver multimedia data with an acceptable quality level based on the user experience. Moreover, human experience and context, as well as network information play an important role in adapting and optimizing video dissemination. In this paper, we discuss trends to provide video dissemination with Quality of Experience (QoE) support by integrating HCMN with cloud computing approaches. We identified five trends coming from such integration, namely Participatory Sensor Networks, Mobile Cloud Computing formation, QoE assessment, QoE management, and video or network adaptation.
Resumo:
Resumen: Las redes de sensores inalámbricos han atraído mucha atención en los últimos años debido a la integración de tecnología inalámbrica, computación y tecnología de sensores. Estas redes consisten en una serie de nodos equipados con capacidades de procesamiento, comunicación y sensado. Utilizan protocolos especiales de radio para transmitir datos en un modo multisalto de operación. En este trabajo se propone utilizar una red de sensores para el monitoreo de las condiciones ambientales de Higiene y Seguridad en entornos industriales. Concretamente se monitorean Temperatura, Humedad, Ruido y Luminosidad. Se propone esta recolección de datos para dar soporte a la inspección anual de un auditor externo, por lo que no se considera esta recolección como crítica dado que no controlan ningún dispositivo. En primera instancia se aborda el problema utilizando una red de sensores con módulos que utilizan el protocolo 802.15 los cuales transmiten a un nodo maestro que sirve como gateway para enviar la información a un servidor que la almacena. La recolección de datos se realiza a través de una plataforma arduino como interface entre el módulo inalámbrico y los sensores. Esta primera propuesta es contrastada con un enfoque de Internet de las Cosas (IoT) utilizando módulos Arduino con WiFi embebido, denominados Wido, que permiten la comunicación de datos directamente al servidor de almacenaje. El trabajo comprende la caracterización del problema, elección del hardware, diseño de la red y la realización de pruebas para evaluar el funcionamiento de ambos enfoques.
Resumo:
The objective of this thesis is the development of cooperative localization and tracking algorithms using nonparametric message passing techniques. In contrast to the most well-known techniques, the goal is to estimate the posterior probability density function (PDF) of the position of each sensor. This problem can be solved using Bayesian approach, but it is intractable in general case. Nevertheless, the particle-based approximation (via nonparametric representation), and an appropriate factorization of the joint PDFs (using message passing methods), make Bayesian approach acceptable for inference in sensor networks. The well-known method for this problem, nonparametric belief propagation (NBP), can lead to inaccurate beliefs and possible non-convergence in loopy networks. Therefore, we propose four novel algorithms which alleviate these problems: nonparametric generalized belief propagation (NGBP) based on junction tree (NGBP-JT), NGBP based on pseudo-junction tree (NGBP-PJT), NBP based on spanning trees (NBP-ST), and uniformly-reweighted NBP (URW-NBP). We also extend NBP for cooperative localization in mobile networks. In contrast to the previous methods, we use an optional smoothing, provide a novel communication protocol, and increase the efficiency of the sampling techniques. Moreover, we propose novel algorithms for distributed tracking, in which the goal is to track the passive object which cannot locate itself. In particular, we develop distributed particle filtering (DPF) based on three asynchronous belief consensus (BC) algorithms: standard belief consensus (SBC), broadcast gossip (BG), and belief propagation (BP). Finally, the last part of this thesis includes the experimental analysis of some of the proposed algorithms, in which we found that the results based on real measurements are very similar with the results based on theoretical models.