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Trust Management in Cloud-Integrated Wireless sensor Networks

Trust Management in Cloud-Integrated Wireless Sensor Network...

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international conference on Collaboration Technologies and systems (CTS)

作者： Savas, Onur Jin, Guang Deng, Julia Intelligent Automat Inc Rockville MD 20855 USA

ISBN: (纸本)9781467364041;9781467364034

The untethered nature of Wireless sensor Networks (WSNs) lets them sense information in previously unobtainable situations (e. g., undersea) as well as in various hostile environments (e. g., battlefield). With the proliferation of WSNs, a broad range of ubiquitous computing applications has been enabled in distributed sensing and control areas. Accordingly, the amount of data gathered by contemporary WSNs is becoming larger and larger, and creating unprecedented challenges in terms of computation and storage. Cloud computing, on the other hand, provides a data-intensive processing environment. Integrating cloud computing with WSNs is becoming one growing trend due to its great potential to enhance existing capabilities of WSNs. However, this integrated system brings more security issues, emanating from both WSNs and cloud computing. Ensuring data safety as well as system performance is an essential enabler and one of the major challenges to overcome. In this paper, we first study the architecture of cloud-integrated WSNs, identify security challenges in this architecture, and then discuss how trust management could be effectively used to enhance the security of such a system.

关键词： Trust Management Wireless sensor Networks Cloud computing Algorithms

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Component-Average based distributed Seismic Tomography in sensor Networks

Component-Average based Distributed Seismic Tomography in Se...

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ieee international conference on distributed computing in sensor systems

作者： Goutham Kamath Lei Shi Wen-Zhan Song Department of Computer Science Georgia State University

ISBN: (纸本)9781479902064

Existing volcano instrumentation and monitoring system use centralized approach for data collection and image reconstruction and they lack the capability of obtaining real time information. A new distributed method is required which can obtain a high resolution seismic tomography in real time. In this paper, we present a component-average distributed multi-resolution evolving tomography algorithm for processing data and inverting volcano tomography in the network, while avoiding centralized computation and costly data collection. The new algorithm distributes the computational burden to sensor nodes and performs real time tomographic inversion under constraints of network resources. We implemented and evaluated the algorithm in a customized simulator using synthetic data. The experiment results validate that our proposed algorithm not only balances the computation load but also achieves high data loss tolerance.~1

关键词： distributed computing Seismic Tomography sensor Network seismic tomographies distributed computing sensor networks Data Collection Methods Tomography Web resources Distribute

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Imaging Seismic Tomography in sensor Network

Imaging Seismic Tomography in Sensor Network

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ieee international conference on distributed computing in sensor systems

作者： Lei Shi Wen-Zhan Song Mingsen Xu Qingjun Xiao Goutham Kamath Jonathan M. Lees Guoliang Xing Department of Computer Science Georgia State University Department of Geological Sciences University of North Carolina at Chapel Hill

ISBN: (纸本)9781479902064

Tomography imaging, applied to seismology, requires a new, decentralized approach if high resolution calculations are to be performed in a sensor network configuration. The real-time data retrieval from a network of large-amount wireless seismic nodes to a central server is virtually impossible due to the sheer data amount and resource limitations. In this paper, we present a distributed multi-resolution evolving tomography algorithm for processing data and inverting volcano tomography in the network, while avoiding costly data collections and centralized computations. The new algorithm distributes the computational burden to sensor nodes and performs real-time tomography inversion under the constraints of network resources. We implemented and evaluated the system design in the CORE emulator. The experiment results validate that our proposed algorithm not only balances the computation load, but also achieves low communication cost and high data loss-tolerance.~1

关键词： distributed computing In-network Processing Seismic Tomography sensor Network seismic tomographies distributed computing sensor networks Tomography Data Collection Methods seismology Web resources

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Uncovering the Impact of Minimum-Energy Routing on Lifetime of Wireless sensor Networks

Uncovering the Impact of Minimum-Energy Routing on Lifetime ...

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ieee international conference on distributed computing in sensor systems

作者： Arda Soylev Kemal Bicakci Bulent Tavli KTO Karatay University Computer Engineering Department Konya Turkey TOBB University of Economics and Technology Computer Engineering Department Ankara Turkey TOBB University of Economics and Technology Electrical Engineering Department Ankara Turkey

ISBN: (纸本)9781479902064

It is well-known that in wireless sensor networks using minimum-energy paths to transfer data from sensor nodes to base station is not an energy-balancing option and not the optimal solution if lifetime, defined as the duration till the first node in the network exhausts all its energy, is of concern. However, the net effect of minimum-energy routing on network lifetime has not been studied in detail before. In this study, we present comparative analysis using both simulations and linear programming models to investigate this issue with respect to various system parameters such as energy model, network area and number of nodes. Our results show that network lifetime achieved with minimum-energy routing could be as low as 19.3% of the maximum achievable lifetime depending on the values of other system parameters.

关键词： Wireless sensor network linear programming network lifetime routing energy efficiency Wireless sensor networks Network routing linear programming system parameter Energy efficiency mean life optimal solution Ganglia

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Wireless sensor network based on multilevel femtocells for home monitoring

Wireless sensor network based on multilevel femtocells for h...

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2013 ieee 7th international conference on Intelligent Data Acquisition and Advanced computing systems, IDAACS 2013

作者： Maciuca, Andrei Popescu, Dan Strutu, Mircea Stamatescu, Grigore Politehnica University of Bucharest Splaiul Independentei 313 Romania

ISBN: (纸本)9781479914265

An intelligent femtocell-based sensor network is proposed for home monitoring elderly or people with chronic diseases. The femtocell is considered as a small sensor network which is placed into patient house and consists on both mobile and fixed sensors disposed on three layers. The first layer contains body sensors attached to the patient that monitor different health parameters, patient location, position and possible falls. The second layer is dedicated for ambient sensors and routing inside the cell. The third layer contains emergency ambient sensors that cover burglary events or toxic gas concentration, distributed by necessities. Cell implementation is based on IRIS family of motes. In order to reduce energy consumption and radiation level, adaptive rates of acquisition and communication are used. Experimental results on body sensors and ambient ones are presented in the last section. © 2013 ieee.

关键词： Femtocell

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Iterative sensor Node Deployment with Channel Quality Feedback

Iterative Sensor Node Deployment with Channel Quality Feedba...

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ieee international conference on distributed computing in sensor systems

作者： Rafael Funke Hannes Frey University of Paderborn University of Koblenz-Landau

ISBN: (纸本)9781479902064

A wireless sensor network is of no use if it does not support proper communication among the sensor nodes. It is thus important to deploy sensor nodes such that high quality links are available for any communication path required during sensor network operation. In this work we describe a deployment algorithm which takes the link qualities between neighboring nodes of already deployed nodes into account to decide the right position for the next node to be deployed. We compare our approach with the well known regular triangle tessellation deployment. Simulation results show that when both approaches cover the same area, in our approach sink based and unicast communication works visibly better in terms of bit error rate.

关键词： wireless sensor Feedback Iterative Iterative Channel quality feedback Bit error rate Feedback Telecommunication lines Wireless sensor networks deployment unicast communication Ganglia sensors Line of nodes

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Self-Organizing WSN Protocol for Real-Time Communication Requirements

Self-Organizing WSN Protocol for Real-Time Communication Req...

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ieee international conference on distributed computing in sensor systems

作者： Janos Sallai Péter Horváth Xenofon Koutsoukos Institute for Software Integrated Systems Vanderbilt University USA

ISBN: (纸本)9781479902064

In this paper we propose a distributed, low-power, self-organizing MAC scheme for low-power wireless sensor and control applications. In such applications, nearly periodic traffic needs to be handled so that the communication delays are minimized and the transmission is as predictable as possible. We propose Asynchronous Random Schedules with Collision Forecast (ARS/CF) for this purpose, together with a multichannel extension based on an improved modulation scheme to improve capacity scaling of the basic ARS/CF scheme. We analyze and simulate the basic single-hop ARS/CF implementation with regard to throughput and delay when used both in single- and multi-channel settings. Finally, we consider the implementation of ARS/CF in a multi-hop setting.

关键词： ARS CF WSN Wireless sensor networks WSN gene Action Request System CONTAINMENT FAILURE LOW POWER Throughput Communication Research

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sensor Networks for Railway Monitoring: Detecting Trains from their distributed Vibration Footprints

Sensor Networks for Railway Monitoring: Detecting Trains fro...

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ieee international conference on distributed computing in sensor systems

作者： Eugen Berlin Kristof Van Laerhoven Department of Computer Science Technische Universit?t Darmstadt

ISBN: (纸本)9781479902064

We report in this paper on a wireless sensor network deployment at railway tracks to monitor and analyze the vibration patterns caused by trains passing by. We investigate in particular a system that relies on having a distributed network of sensor nodes that individually contain efficient feature extraction algorithms and classifiers that fit the restricted hardware resources, rather than using few complex and specialized sensors. A feasibility study is described on the raw data obtained from a real-world deployment on one of Europe's busiest railroad sections, which was annotated with the help of video footage and contains vibration patterns of 186 trains. These trains were classified in 6 types by various methods, the best performing at an accuracy of 97%. The trains' length in wagons was estimated with a mean-squared error of 3.98. Visual inspection of the data shows further opportunities in the estimation of train speed and detection of worn-out cargo wheels.

关键词： feature extraction sensor data abstraction event classification railway monitoring wireless sensor networks Wireless sensor networks TRAIN Feature extraction railways Vibration Caravans hardware resource distributed NETWORKS Footprints

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Multiple sensor Skewed Covariance Target Localization

Multiple Sensor Skewed Covariance Target Localization

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ieee international conference on distributed computing in sensor systems

作者： Leonid Naimark Kramian Inc. Brookline MA USA

ISBN: (纸本)9781479902064

A cost-effective approach to improve tracking system accuracy is to employ two or more inexpensive sensors. For example, a radar that exhibits good range, but relatively poor cross-range accuracy may be operated in concert with a camera possessing inverted properties. For each separate sensor, we assume that the target location error is represented by a bivariate Gaussian distribution with an elliptical constant probability contour. The problem posed is that of fusing data from these sensors to produce single-frame location coordinate estimates for a target. One of the methods proposed in the past is covariance intersection which assumes that all sensor measurements are uncorrelated. In this paper, we present a generalized method that provides localization coordinate estimation when sensor estimate distributions are skewed. We show that for a variety of practically important cases, our method offers substantially improved performance over conventional approaches. Based on our results, it is possible to segment the tracking volume into sub-volumes.

关键词： Multi-sensor Tracking Covariance Intersection Multi-static Multi-function sensor systems sensors Covariance Gaussian distribution Targets Coordinates location error

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Non-intrusive Tracking of Patients With Dementia Using a Wireless sensor Network

Non-intrusive Tracking of Patients With Dementia Using a Wir...

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ieee international conference on distributed computing in sensor systems

作者： Arnoldo Díaz-Ramírez Fabian N. Murrieta Jorge A. Atempa Francisco A. Bonino Department of Computer Systems Instituto Tecnol6gico de Mexicali Mexicali B.C. México

ISBN: (纸本)9781479902064

As a consequence of the aging of the world population, society and governments must face major challenges regarding people's health. In recent years, researches have been interested in investigating how the technology can be used to improve the healthcare and assistance of patients with dementia, as the Alzheimer's disease. In this paper, we propose a non-intrusive pervasive model to assist patients with dementia, based on the use of a wireless sensor network. Using high availability and low cost binary sensors, the proposed model is able to determine in real-time the location of a patient, and to emit alerts if one leaves a safe place without supervision.

关键词： Wireless sensor networks ubiquitous computing ambient intelligence healthcare pervasive applications Alzheimer's disease Wireless sensor networks Alzheimer Disease Ambient intelligence Ubiquitous computing Dementia Patients high availability

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