Matching Items (4)
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- All Subjects: Sensor Networks
- Creators: Reisslein, Martin
Description
Distributed inference has applications in a wide range of fields such as source localization, target detection, environment monitoring, and healthcare. In this dissertation, distributed inference schemes which use bounded transmit power are considered. The performance of the proposed schemes are studied for a variety of inference problems. In the first part of the dissertation, a distributed detection scheme where the sensors transmit with constant modulus signals over a Gaussian multiple access channel is considered. The deflection coefficient of the proposed scheme is shown to depend on the characteristic function of the sensing noise, and the error exponent for the system is derived using large deviation theory. Optimization of the deflection coefficient and error exponent are considered with respect to a transmission phase parameter for a variety of sensing noise distributions including impulsive ones. The proposed scheme is also favorably compared with existing amplify-and-forward (AF) and detect-and-forward (DF) schemes. The effect of fading is shown to be detrimental to the detection performance and simulations are provided to corroborate the analytical results. The second part of the dissertation studies a distributed inference scheme which uses bounded transmission functions over a Gaussian multiple access channel. The conditions on the transmission functions under which consistent estimation and reliable detection are possible is characterized. For the distributed estimation problem, an estimation scheme that uses bounded transmission functions is proved to be strongly consistent provided that the variance of the noise samples are bounded and that the transmission function is one-to-one. The proposed estimation scheme is compared with the amplify and forward technique and its robustness to impulsive sensing noise distributions is highlighted. It is also shown that bounded transmissions suffer from inconsistent estimates if the sensing noise variance goes to infinity. For the distributed detection problem, similar results are obtained by studying the deflection coefficient. Simulations corroborate our analytical results. In the third part of this dissertation, the problem of estimating the average of samples distributed at the nodes of a sensor network is considered. A distributed average consensus algorithm in which every sensor transmits with bounded peak power is proposed. In the presence of communication noise, it is shown that the nodes reach consensus asymptotically to a finite random variable whose expectation is the desired sample average of the initial observations with a variance that depends on the step size of the algorithm and the variance of the communication noise. The asymptotic performance is characterized by deriving the asymptotic covariance matrix using results from stochastic approximation theory. It is shown that using bounded transmissions results in slower convergence compared to the linear consensus algorithm based on the Laplacian heuristic. Simulations corroborate our analytical findings. Finally, a robust distributed average consensus algorithm in which every sensor performs a nonlinear processing at the receiver is proposed. It is shown that non-linearity at the receiver nodes makes the algorithm robust to a wide range of channel noise distributions including the impulsive ones. It is shown that the nodes reach consensus asymptotically and similar results are obtained as in the case of transmit non-linearity. Simulations corroborate our analytical findings and highlight the robustness of the proposed algorithm.
ContributorsDasarathan, Sivaraman (Author) / Tepedelenlioğlu, Cihan (Thesis advisor) / Papandreou-Suppappola, Antonia (Committee member) / Reisslein, Martin (Committee member) / Goryll, Michael (Committee member) / Arizona State University (Publisher)
Created2013
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 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
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
ContributorsShah, Tejas (Author) / Reisslein, Martin (Thesis advisor) / Kitchen, Jennifer (Committee member) / McGarry, Michael (Committee member) / Arizona State University (Publisher)
Created2014
Description
Modern measurement schemes for linear dynamical systems are typically designed so that different sensors can be scheduled to be used at each time step. To determine which sensors to use, various metrics have been suggested. One possible such metric is the observability of the system. Observability is a binary condition determining whether a finite number of measurements suffice to recover the initial state. However to employ observability for sensor scheduling, the binary definition needs to be expanded so that one can measure how observable a system is with a particular measurement scheme, i.e. one needs a metric of observability. Most methods utilizing an observability metric are about sensor selection and not for sensor scheduling. In this dissertation we present a new approach to utilize the observability for sensor scheduling by employing the condition number of the observability matrix as the metric and using column subset selection to create an algorithm to choose which sensors to use at each time step. To this end we use a rank revealing QR factorization algorithm to select sensors. Several numerical experiments are used to demonstrate the performance of the proposed scheme.
ContributorsIlkturk, Utku (Author) / Gelb, Anne (Thesis advisor) / Platte, Rodrigo (Thesis advisor) / Cochran, Douglas (Committee member) / Renaut, Rosemary (Committee member) / Armbruster, Dieter (Committee member) / Arizona State University (Publisher)
Created2015
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. 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.
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.
ContributorsRentala, Sri Harsha (Author) / Reisslein, Martin (Thesis advisor) / Kitchen, Jennifer (Committee member) / McGarry, Michael (Committee member) / Arizona State University (Publisher)
Created2016