Matching Items (16)

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Estimation Theory on Random Graphs for Offset Detection in Sensor Networks

Description

A distributed sensor network (DSN) is a set of spatially scattered intelligent sensors designed to obtain data across an environment. DSNs are becoming a standard architecture for collecting data over

A distributed sensor network (DSN) is a set of spatially scattered intelligent sensors designed to obtain data across an environment. DSNs are becoming a standard architecture for collecting data over a large area. We need registration of nodal data across the network in order to properly exploit having multiple sensors. One major problem worth investigating is ensuring the integrity of the data received, such as time synchronization. Consider a group of match filter sensors. Each sensor is collecting the same data, and comparing the data collected to a known signal. In an ideal world, each sensor would be able to collect the data without offsets or noise in the system. Two models can be followed from this. First, each sensor could make a decision on its own, and then the decisions could be collected at a ``fusion center'' which could then decide if the signal is present or not. The fusion center can then decide if the signal is present or not based on the number true-or-false decisions that each sensor has made. Alternatively, each sensor could relay the data that it collects to the fusion center, and it could then make a decision based on all of the data that it then receives. Since the fusion center would have more information to base its decision on in the latter case--as opposed to the former case where it only receives a true or false from each sensor--one would expect the latter model to perform better. In fact, this would be the gold standard for detection across a DSN. However, there is random noise in the world that causes corruption of data collection, especially among sensors in a DSN. Each sensor does not collect the data in the exact same way or with the same precision. We classify these imperfections in data collections as offsets, specifically the offset present in the data collected by one sensor with respect to the rest of the sensors in the network. Therefore, reconsider the two models for a DSN described above. We can naively implement either of these models for data collection. Alternatively, we can attempt to estimate the offsets between the sensors and compensate. One could see how it would be expected that estimating the offsets within the DSN would provide better overall results than not finding estimators. This thesis will be structured as follows. First, there will be an extensive investigation into detection theory and the impact that different types of offsets have on sensor networks. Following the theory, an algorithm for estimating the data offsets will be proposed correct for the offsets. Next, we will look at Monte Carlo simulation results to see the impact on sensor performance of data offsets in comparison to a sensor network without offsets present. The algorithm is then implemented, and further experiments will demonstrate sensor performance with offset detection.

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Created

Date Created
  • 2016-05

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Operating Systems for Underwater Wireless Sensor Networks

Description

As the need for data concerning the health of the world's oceans increases, it becomes necessary to develop large, networked communication systems underwater. This research involves the development of an

As the need for data concerning the health of the world's oceans increases, it becomes necessary to develop large, networked communication systems underwater. This research involves the development of an embedded operating system that is suited for optically-linked underwater wireless sensor networks (WSNs). Optical WSNs are unique in that large sums of data may be received relatively infrequently, and so an operating system for each node must be very responsive. Additionally, the volatile nature of the underwater environment means that the operating system must be accurate, while still maintaining a low profile on a relatively small microprocessor core. The first part of this research concerns the actual implementation of the operating system's task scheduler and additional libraries to maintain synchronization, and the second part involves testing the operating system for responsiveness to interrupts and overall performance.

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Created

Date Created
  • 2016-05

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Statistically Based Registration in Sensor Networks

Description

In recent years, networked systems have become prevalent in communications, computing, sensing, and many other areas. In a network composed of spatially distributed agents, network-wide synchronization of information about the

In recent years, networked systems have become prevalent in communications, computing, sensing, and many other areas. In a network composed of spatially distributed agents, network-wide synchronization of information about the physical environment and the network configuration must be maintained using measurements collected locally by the agents. Registration is a process for connecting the coordinate frames of multiple sets of data. This poses numerous challenges, particularly due to availability of direct communication only between neighboring agents in the network. These are exacerbated by uncertainty in the measurements and also by imperfect communication links. This research explored statistically based registration in a sensor network. The approach developed exploits measurements of offsets formed as differences of state values between pairs of agents that share a link in the network graph. It takes into account that the true offsets around any closed cycle in the network graph must sum to zero.

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Created

Date Created
  • 2014-05

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Security and privacy in heterogeneous wireless and mobile networks: challenges and solutions

Description

The rapid advances in wireless communications and networking have given rise to a number of emerging heterogeneous wireless and mobile networks along with novel networking paradigms, including wireless sensor networks,

The rapid advances in wireless communications and networking have given rise to a number of emerging heterogeneous wireless and mobile networks along with novel networking paradigms, including wireless sensor networks, mobile crowdsourcing, and mobile social networking. While offering promising solutions to a wide range of new applications, their widespread adoption and large-scale deployment are often hindered by people's concerns about the security, user privacy, or both. In this dissertation, we aim to address a number of challenging security and privacy issues in heterogeneous wireless and mobile networks in an attempt to foster their widespread adoption. Our contributions are mainly fivefold. First, we introduce a novel secure and loss-resilient code dissemination scheme for wireless sensor networks deployed in hostile and harsh environments. Second, we devise a novel scheme to enable mobile users to detect any inauthentic or unsound location-based top-k query result returned by an untrusted location-based service providers. Third, we develop a novel verifiable privacy-preserving aggregation scheme for people-centric mobile sensing systems. Fourth, we present a suite of privacy-preserving profile matching protocols for proximity-based mobile social networking, which can support a wide range of matching metrics with different privacy levels. Last, we present a secure combination scheme for crowdsourcing-based cooperative spectrum sensing systems that can enable robust primary user detection even when malicious cognitive radio users constitute the majority.

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Created

Date Created
  • 2013

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A cross-layer power analysis and profiling of wireless video sensor node platform applications

Description

Wireless video sensor networks has been examined and evaluated for wide range

of applications comprising of video surveillance, video tracking, computer vision, remote

live video and control. The reason behind importance of

Wireless video sensor networks has been examined and evaluated for wide range

of applications comprising of video surveillance, video tracking, computer vision, remote

live video and control. The reason behind importance of sensor nodes is its ease

of implementation, ability to operate in adverse environments, easy to troubleshoot,

repair and the high performance level. The biggest challenges with the architectural

design of wireless video sensor networks are power consumption, node failure,

throughput, durability and scalability. The whole project here is to create a gateway

node to integrate between "Internet of things" framework and wireless sensor network.

Our Flexi-Wireless Video Sensor Node Platform (WVSNP) is a low cost, low

power and compatible with traditional sensor network where the main focus was on

maximizing throughput or minimizing node deployment. My task here in this project

was to address the challenges of video power consumption for wireless video sensor

nodes. While addressing the challenges, I performed analysis of predicting the nodes

durability when it is battery operated and to choose appropriate design parameters.

I created a small optimized image to boot up Wandboard DUAL/QUAD board, capture

videos in small/big chunks from the board. The power analysis was performed

for only capturing scenarios, playback of reference videos and, live capturing and realtime

playing of videos on WVSNP player. Each sensor node in sensor network are

battery operated and runs without human intervention. Thus to predict nodes durability,

for dierent video size and format, I have collected power consumption results

and based on this I have provided some recommendation of HW/SW architecture.

i

Contributors

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Created

Date Created
  • 2014

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Distributed inference over multiple-access channels with wireless sensor networks

Description

Distributed inference has applications in fields as varied as source localization, evaluation of network quality, and remote monitoring of wildlife habitats. In this dissertation, distributed inference algorithms over multiple-access channels

Distributed inference has applications in fields as varied as source localization, evaluation of network quality, and remote monitoring of wildlife habitats. In this dissertation, distributed inference algorithms over multiple-access channels are considered. The performance of these algorithms and the effects of wireless communication channels on the performance are studied. In a first class of problems, distributed inference over fading Gaussian multiple-access channels with amplify-and-forward is considered. Sensors observe a phenomenon and transmit their observations using the amplify-and-forward scheme to a fusion center (FC). Distributed estimation is considered with a single antenna at the FC, where the performance is evaluated using the asymptotic variance of the estimator. The loss in performance due to varying assumptions on the limited amounts of channel information at the sensors is quantified. With multiple antennas at the FC, a distributed detection problem is also considered, where the error exponent is used to evaluate performance. It is shown that for zero-mean channels between the sensors and the FC when there is no channel information at the sensors, arbitrarily large gains in the error exponent can be obtained with sufficient increase in the number of antennas at the FC. In stark contrast, when there is channel information at the sensors, the gain in error exponent due to having multiple antennas at the FC is shown to be no more than a factor of 8/π for Rayleigh fading channels between the sensors and the FC, independent of the number of antennas at the FC, or correlation among noise samples across sensors. In a second class of problems, sensor observations are transmitted to the FC using constant-modulus phase modulation over Gaussian multiple-access-channels. The phase modulation scheme allows for constant transmit power and estimation of moments other than the mean with a single transmission from the sensors. Estimators are developed for the mean, variance and signal-to-noise ratio (SNR) of the sensor observations. The performance of these estimators is studied for different distributions of the observations. It is proved that the estimator of the mean is asymptotically efficient if and only if the distribution of the sensor observations is Gaussian.

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Created

Date Created
  • 2010

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Self-configuring and self-adaptive environment control systems for buildings

Description

Lighting systems and air-conditioning systems are two of the largest energy consuming end-uses in buildings. Lighting control in smart buildings and homes can be automated by having computer controlled lights

Lighting systems and air-conditioning systems are two of the largest energy consuming end-uses in buildings. Lighting control in smart buildings and homes can be automated by having computer controlled lights and window blinds along with illumination sensors that are distributed in the building, while temperature control can be automated by having computer controlled air-conditioning systems. However, programming actuators in a large-scale environment for buildings and homes can be time consuming and expensive. This dissertation presents an approach that algorithmically sets up the control system that can automate any building without requiring custom programming. This is achieved by imbibing the system self calibrating and self learning abilities.

For lighting control, the dissertation describes how the problem is non-deterministic polynomial-time hard(NP-Hard) but can be resolved by heuristics. The resulting system controls blinds to ensure uniform lighting and also adds artificial illumination to ensure light coverage remains adequate at all times of the day, while adjusting for weather and seasons. In the absence of daylight, the system resorts to artificial lighting.

For temperature control, the dissertation describes how the temperature control problem is modeled using convex quadratic programming. The impact of every air conditioner on each sensor at a particular time is learnt using a linear regression model. The resulting system controls air-conditioning equipments to ensure the maintenance of user comfort and low cost of energy consumptions. The system can be deployed in large scale environments. It can accept multiple target setpoints at a time, which improves the flexibility and efficiency of cooling systems requiring temperature control.

The methods proposed work as generic control algorithms and are not preprogrammed for a particular place or building. The feasibility, adaptivity and scalability features of the system have been validated through various actual and simulated experiments.

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Created

Date Created
  • 2015

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Analysis of wireless video sensor network platforms over AJAX, CGI and WebRTC

Description

Since the inception of Internet of Things (IoT) framework, the amount of interaction between electronic devices has tremendously increased and the ease of implementing software between such devices has bettered.

Since the inception of Internet of Things (IoT) framework, the amount of interaction between electronic devices has tremendously increased and the ease of implementing software between such devices has bettered. Such data exchange between devices, whether between Node to Server or Node to Node, has paved way for creating new business models. Wireless Video Sensor Network Platforms are being used to monitor and understand the surroundings better. Both hardware and software supporting such devices have become much smaller and yet stronger to enable these. Specifically, the invention of better software that enable Wireless data transfer have become more simpler and lightweight technologies such as HTML5 for video rendering, Common Gateway Interface(CGI) scripts enabling interactions between client and server and WebRTC from Google for peer to peer interactions. The role of web browsers in enabling these has been vastly increasing.

Although HTTP is the most reliable and consistent data transfer protocol for such interactions, the most important underlying challenge with such platforms is the performance based on power consumption and latency in data transfer.

In the scope of this thesis, two applications using CGI and WebRTC for data transfer over HTTP will be presented and the power consumption by the peripherals in transmitting the data and the possible implications for those will be discussed.

Contributors

Agent

Created

Date Created
  • 2016

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SmartGateway Framework

Description

Cisco estimates that by 2020, 50 billion devices will be connected to the Internet. But 99% of the things today remain isolated and unconnected. Different connectivity protocols, proprietary access, varied

Cisco estimates that by 2020, 50 billion devices will be connected to the Internet. But 99% of the things today remain isolated and unconnected. Different connectivity protocols, proprietary access, varied device characteristics, security concerns are the main reasons for that isolated state. This project aims at designing and building a prototype gateway that exposes a simple and intuitive HTTP Restful interface to access and manipulate devices and the data that they produce while addressing most of the issues listed above. Along with manipulating devices, the framework exposes sensor data in such a way that it can be used to create applications like rules or events that make the home smarter. It also allows the user to represent high-level knowledge by aggregating the low-level sensor data. This high-level representation can be considered as a property of the environment or object rather than the sensor itself which makes interpreting the values more intuitive and accessible.

Contributors

Agent

Created

Date Created
  • 2015

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An exact optimization approach for relay node location in wireless sensor networks

Description

I study the problem of locating Relay nodes (RN) to improve the connectivity of a set

of already deployed sensor nodes (SN) in a Wireless Sensor Network (WSN). This is

known as

I study the problem of locating Relay nodes (RN) to improve the connectivity of a set

of already deployed sensor nodes (SN) in a Wireless Sensor Network (WSN). This is

known as the Relay Node Placement Problem (RNPP). In this problem, one or more

nodes called Base Stations (BS) serve as the collection point of all the information

captured by SNs. SNs have limited transmission range and hence signals are transmitted

from the SNs to the BS through multi-hop routing. As a result, the WSN

is said to be connected if there exists a path for from each SN to the BS through

which signals can be hopped. The communication range of each node is modeled

with a disk of known radius such that two nodes are said to communicate if their

communication disks overlap. The goal is to locate a given number of RNs anywhere

in the continuous space of the WSN to maximize the number of SNs connected (i.e.,

maximize the network connectivity). To solve this problem, I propose an integer

programming based approach that iteratively approximates the Euclidean distance

needed to enforce sensor communication. This is achieved through a cutting-plane

approach with a polynomial-time separation algorithm that identies distance violations.

I illustrate the use of my algorithm on large-scale instances of up to 75 nodes

which can be solved in less than 60 minutes. The proposed method shows solutions

times many times faster than an alternative nonlinear formulation.

Contributors

Agent

Created

Date Created
  • 2019