129,324 research outputs found

    Cognitive test-bed for wireless sensor networks

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    Cognitive Wireless Sensor Networks are an emerging technology with a vast potential to avoid traditional wireless problems such as reliability, interferences and spectrum scarcity in Wireless Sensor Networks. Cognitive Wireless Sensor Networks test-beds are an important tool for future developments, protocol strategy testing and algorithm optimization in real scenarios. A new cognitive test-bed for Cognitive Wireless Sensor Networks is presented in this paper. This work in progress includes both the design of a cognitive simulator for networks with a high number of nodes and the implementation of a new platform with three wireless interfaces and a cognitive software for extracting real data. Finally, as a future work, a remote programmable system and the planning for the physical deployment of the nodes at the university building is presented

    On the Relevance of Using Open Wireless Sensor Networks in Environment Monitoring

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    This paper revisits the problem of the readiness for field deployments of wireless sensor networks by assessing the relevance of using Open Hardware and Software motes for environment monitoring. We propose a new prototype wireless sensor network that fine-tunes SquidBee motes to improve the life-time and sensing performance of an environment monitoring system that measures temperature, humidity and luminosity. Building upon two outdoor sensing scenarios, we evaluate the performance of the newly proposed energy-aware prototype solution in terms of link quality when expressed by the Received Signal Strength, Packet Loss and the battery lifetime. The experimental results reveal the relevance of using the Open Hardware and Software motes when setting up outdoor wireless sensor networks

    A COMMUNICATION FRAMEWORK FOR MULTIHOP WIRELESS ACCESS AND SENSOR NETWORKS: ANYCAST ROUTING & SIMULATION TOOLS

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    The reliance on wireless networks has grown tremendously within a number of varied application domains, prompting an evolution towards the use of heterogeneous multihop network architectures. We propose and analyze two communication frameworks for such networks. A first framework is designed for communications within multihop wireless access networks. The framework supports dynamic algorithms for locating access points using anycast routing with multiple metrics and balancing network load. The evaluation shows significant performance improvement over traditional solutions. A second framework is designed for communication within sensor networks and includes lightweight versions of our algorithms to fit the limitations of sensor networks. Analysis shows that this stripped down version can work almost equally well if tailored to the needs of a sensor network. We have also developed an extensive simulation environment using NS-2 to test realistic situations for the evaluations of our work. Our tools support analysis of realistic scenarios including the spreading of a forest fire within an area, and can easily be ported to other simulation software. Lastly, we us our algorithms and simulation environment to investigate sink movements optimization within sensor networks. Based on these results, we propose strategies, to be addressed in follow-on work, for building topology maps and finding optimal data collection points. Altogether, the communication framework and realistic simulation tools provide a complete communication and evaluation solution for access and sensor networks

    ShakeNet: A portable wireless sensor network for instrumenting large civil structures

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    We report our findings from a U.S. Geological Survey (USGS) National Earthquake Hazards Reduction Program-funded project to develop and test a wireless, portable, strong-motion network of up to 40 triaxial accelerometers for structural health monitoring. The overall goal of the project was to record ambient vibrations for several days from USGS-instrumented structures. Structural health monitoring has important applications in fields like civil engineering and the study of earthquakes. The emergence of wireless sensor networks provides a promising means to such applications. However, while most wireless sensor networks are still in the experimentation stage, very few take into consideration the realistic earthquake engineering application requirements. To collect comprehensive data for structural health monitoring for civil engineers, high-resolution vibration sensors and sufficient sampling rates should be adopted, which makes it challenging for current wireless sensor network technology in the following ways: processing capabilities, storage limit, and communication bandwidth. The wireless sensor network has to meet expectations set by wired sensor devices prevalent in the structural health monitoring community. For this project, we built and tested an application-realistic, commercially based, portable, wireless sensor network called ShakeNet for instrumentation of large civil structures, especially for buildings, bridges, or dams after earthquakes. Two to three people can deploy ShakeNet sensors within hours after an earthquake to measure the structural response of the building or bridge during aftershocks. ShakeNet involved the development of a new sensing platform (ShakeBox) running a software suite for networking, data collection, and monitoring. Deployments reported here on a tall building and a large dam were real-world tests of ShakeNet operation, and helped to refine both hardware and software

    Supporting Cyber-Physical Systems with Wireless Sensor Networks: An Outlook of Software and Services

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    Sensing, communication, computation and control technologies are the essential building blocks of a cyber-physical system (CPS). Wireless sensor networks (WSNs) are a way to support CPS as they provide fine-grained spatial-temporal sensing, communication and computation at a low premium of cost and power. In this article, we explore the fundamental concepts guiding the design and implementation of WSNs. We report the latest developments in WSN software and services for meeting existing requirements and newer demands; particularly in the areas of: operating system, simulator and emulator, programming abstraction, virtualization, IP-based communication and security, time and location, and network monitoring and management. We also reflect on the ongoing efforts in providing dependable assurances for WSN-driven CPS. Finally, we report on its applicability with a case-study on smart buildings

    Architectures for wireless sensor networks

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    The vision of ubiquitous computing requires the development of devices and technologies that can be pervasive without being intrusive. The basic component of such a smart environment will be a small node with sensing and wireless communications capabilities, able to organize itself flexibly into a network for data collection and delivery. Building such a sensor network presents many significant challenges, especially at the architectural, protocol, and operating system level. Although sensor nodes might be equipped with a power supply or energy scavenging means and an embedded processor that makes them autonomous and self-aware, their functionality and capabilities will be very limited. Therefore, collaboration between nodes is essential to deliver smart services in a ubiquitous setting. New algorithms for networking and distributed collaboration need to be developed. These algorithms will be the key for building self-organizing and collaborative sensor networks that show emergent behavior and can operate in a challenging environment where nodes move, fail, and energy is a scarce resource. The question that rises is how to organize the internal software and hardware components in a manner thatwill allowthem towork properly and be able to adapt dynamically to new environments, requirements, and applications. At the same time the solution should be general enough to be suited for as many applications as possible. Architecture definition also includes, at the higher level, a global view of the whole network. The topology, placement of base stations, beacons, etc. is also of interest. In this chapter, we will present and analyze some of the characteristics of the architectures for wireless sensor networks. Then, we will propose a new dataflow-based architecture that allows, as a new feature, the dynamic reconfiguration of the sensor nodes software at runtime

    Integrated Sensor Fusion Device with an Optimized Mathematical Model to Monitor Civil Engineering Structures

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    Integrated sensor fusion is a new technique in which multiple sensors intelligently combine data to support application or system performance improvement software. With this method, many sensors combine data for accurate position and orientation information to overcome the inadequacy of each sensor. Data consolidation can be described as measuring the state of an entity as a mixture of data or information. This multidisciplinary field has several advantages, including increased confidence, reliability, and reduced ambiguity when measuring company conditions in engineered systems. This paper discusses the various applications of data fusion in civil engineering in recent years, and puts forward some potential advantages of data fusion in civil engineering. Mathematical modeling (MM) is the skill to transform challenges from application to tractable mathematical formulations that provide insight, answers, and instructions in the theoretical and numerical analysis of the original application. This article presented an integer linear programming mathematical model to divide building activities in a project to solve building planning problems. MMCE (Mathematical Modeling Conceptual Evaluation) introduced it to complete an accurate and quick estimation of civil systems such as traffic networks, structural systems, and building projects, becoming more and more achievable through omnipresent sensor networks and communications systems. By assessing the condition of the system, it can make better decisions more rapidly and better. This has enormous value and a variety of impacts. Fusion data is an essential element of system status assessment. Applications and needs for research are underlined for the future

    QFlow lite dataset: A machine-learning approach to the charge states in quantum dot experiments

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    Over the past decade, machine learning techniques have revolutionized how research is done, from designing new materials and predicting their properties to assisting drug discovery to advancing cybersecurity. Recently, we added to this list by showing how a machine learning algorithm (a so-called learner) combined with an optimization routine can assist experimental efforts in the realm of tuning semiconductor quantum dot (QD) devices. Among other applications, semiconductor QDs are a candidate system for building quantum computers. The present-day tuning techniques for bringing the QD devices into a desirable configuration suitable for quantum computing that rely on heuristics do not scale with the increasing size of the quantum dot arrays required for even near-term quantum computing demonstrations. Establishing a reliable protocol for tuning that does not rely on the gross-scale heuristics developed by experimentalists is thus of great importance. To implement the machine learning-based approach, we constructed a dataset of simulated QD device characteristics, such as the conductance and the charge sensor response versus the applied electrostatic gate voltages. Here, we describe the methodology for generating the dataset, as well as its validation in training convolutional neural networks. We show that the learner's accuracy in recognizing the state of a device is ~96.5 % in both current- and charge-sensor-based training. We also introduce a tool that enables other researchers to use this approach for further research: QFlow lite - a Python-based mini-software suite that uses the dataset to train neural networks to recognize the state of a device and differentiate between states in experimental data. This work gives the definitive reference for the new dataset that will help enable researchers to use it in their experiments or to develop new machine learning approaches and concepts.Comment: 18 pages, 6 figures, 3 table

    Reliable routing protocols for dynamic wireless ad hoc and sensor networks

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    The vision of ubiquitous computing requires the development of devices and technologies, which can be pervasive without being intrusive. The basic components of such a smart environment will be small nodes with sensing and wireless communications capabilities, able to organize flexibly into a network for data collection and delivery. The constant improvements in digital circuit technology, has made the deployment of such small, inexpensive, low-power, distributed devices, which are capable of information gathering, processing, and communication in miniature packaging, a reality.\ud Realizing such a network presents very significant challenges, especially at the protocol and software level. Major steps forward are required in the field of communications protocol, data processing, and application support. Although sensor nodes will be equipped with a power supply (battery) and embedded processor that makes them autonomous and self-aware, their functionality and capabilities will be very limited. The resource limitations of Wireless Sensor Networks (WSN), especially in terms of energy, require novel and collaborative approach for the wireless communication. Therefore, collaboration between nodes is essential to deliver smart services in a ubiquitous setting. Current research in this area generally assumes a rather static network, leading to a strong performance degradation in a dynamic environment. In this thesis we investigate new algorithms for routing in dynamic wireless environment and evaluate their feasibility through experimentation. These algorithms will be key for building self-organizing and collaborative sensor networks\ud that show emergent behavior and can operate in a challenging environment where\ud nodes move, fail and energy is a scarce resource.\ud We develop the technology needed for building self-organizing and collabora-\ud tive sensor networks using reconfigurable smart sensor nodes, which are self-aware,self-reconfigurable and autonomous. This technology will enable the creation of a new generation of sensors, which can effectively network together so as to provide a flexible platform for the support of a large variety of mobile sensor network applications. In this thesis, we address the dynamics of sink nodes, sensor nodes and event in the routing of wireless sensor networks, while maintaining high reliability and low energy consumption. The hypothesis is that this requires different routing protocols and approaches. The varying application scenarios of wireless sensor\ud networks require different routing protocols and approaches as well.\ud This thesis has three major contributions to the routing in dynamic wireless\ud sensor networks. Firstly, a combination between a new multipath on-Demand Rout-\ud ing protocol and a data-splitting scheme which results in an e±cient solution for high reliability and low traffic. Secondly, a cross-layered approach with a self-organizing medium access control protocol and a tightly integrated source routing protocol is designed for high mobility sensor networks. Finally, a data-centric approach based on cost estimation is designed to disseminate aggregated data from data source to destination with high efficiency
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