Matching Items (57)
Description
Video deinterlacing is a key technique in digital video processing, particularly with the widespread usage of LCD and plasma TVs. This thesis proposes a novel spatio-temporal, non-linear video deinterlacing technique that adaptively chooses between the results from one dimensional control grid interpolation (1DCGI), vertical temporal filter (VTF) and temporal line averaging (LA). The proposed method performs better than several popular benchmarking methods in terms of both visual quality and peak signal to noise ratio (PSNR). The algorithm performs better than existing approaches like edge-based line averaging (ELA) and spatio-temporal edge-based median filtering (STELA) on fine moving edges and semi-static regions of videos, which are recognized as particularly challenging deinterlacing cases. The proposed approach also performs better than the state-of-the-art content adaptive vertical temporal filtering (CAVTF) approach. Along with the main approach several spin-off approaches are also proposed each with its own characteristics.
ContributorsVenkatesan, Ragav (Author) / Frakes, David H (Thesis advisor) / Li, Baoxin (Committee member) / Reisslein, Martin (Committee member) / Arizona State University (Publisher)
Created2012
Description
Insertion and deletion errors represent an important category of channel impairments. Despite their importance and much work over the years, channels with such impairments are far from being fully understood as they proved to be difficult to analyze. In this dissertation, a promising coding scheme is investigated over independent and identically distributed (i.i.d.) insertion/deletion channels, i.e., interleaved concatenation of an outer low-density parity-check (LDPC) code with error-correction capabilities and an inner marker code for synchronization purposes. Marker code structures which offer the highest achievable rates are found with standard bit-level synchronization is performed. Then, to exploit the correlations in the likelihoods corresponding to different transmitted bits, a novel symbol-level synchronization algorithm that works on groups of consecutive bits is introduced. Extrinsic information transfer (EXIT) charts are also utilized to analyze the convergence behavior of the receiver, and to design LDPC codes with degree distributions matched to these channels. The next focus is on segmented deletion channels. It is first shown that such channels are information stable, and hence their channel capacity exists. Several upper and lower bounds are then introduced in an attempt to understand the channel capacity behavior. The asymptotic behavior of the channel capacity is also quantified when the average bit deletion rate is small. Further, maximum-a-posteriori (MAP) based synchronization algorithms are developed and specific LDPC codes are designed to match the channel characteristics. Finally, in addition to binary substitution errors, coding schemes and the corresponding detection algorithms are also studied for several other models with synchronization errors, including inter-symbol interference (ISI) channels, channels with multiple transmit/receive elements and multi-user communication systems.
ContributorsWang, Feng (Author) / Duman, Tolga M. (Thesis advisor) / Tepedelenlioğlu, Cihan (Committee member) / Reisslein, Martin (Committee member) / Zhang, Junshan (Committee member) / Arizona State University (Publisher)
Created2012
Description
A new type of Ethernet switch based on the PCI Express switching fabric is being presented. The switch leverages PCI Express peer-to-peer communication protocol to implement high performance Ethernet packet switching. The advantages and challenges of using the PCI Express as the switching fabric are addressed. The PCI Express is a high-speed short-distance communication protocol largely used in motherboard-level interconnects. The total bandwidth of a PCI Express 3.0 link can reach as high as 256 gigabit per second (Gb/s) per 16 lanes. Concerns for PCI Express such as buffer speed, address mapping, Quality of Service and power consumption need to be considered. An overview of the proposed Ethernet switch architecture is presented. The switch consists of a PCI Express switching fabric and multiple adaptor cards. The thesis reviews the peer-to-peer (P2P) communication protocol used in the switching fabric. The thesis also discusses the packet routing procedure in P2P protocol in detail. The Ethernet switch utilizes a portion of the Quality of Service provided with PCI Express to ensure guaranteed transmission. The thesis presents a method of adapting Ethernet packets over the PCI Express transaction layer packets. The adaptor card is divided into the following two parts: receive path and transmit path. The commercial off-the-shelf Media Access Control (MAC) core and PCI Express endpoint core are used in the adaptor. The output address lookup logic block is responsible for converting Ethernet MAC addresses to PCI Express port addresses. Different methods of providing Quality of Service in the adaptor card include classification, flow control, and error detection with the cooperation of the PCI Express switch are discussed. The adaptor logic is implemented in Verilog hardware description language. Functional simulation is conducted in ModelSim. The simulation results show that the Ethernet packets are able to be converted to the corresponding PCI Express transaction layer packets based on their destination MAC addresses. The transaction layer packets are then converted back to Ethernet packets. A functionally correct FPGA logic of the adaptor card is ready for implementation on real FPGA development board.
ContributorsChen, Caiyi (Author) / Hui, Joseph (Thesis advisor) / Reisslein, Martin (Committee member) / Zhang, Yanchao (Committee member) / Arizona State University (Publisher)
Created2012
Description
Fully distributed wireless sensor networks (WSNs) without fusion center have advantages such as scalability in network size and energy efficiency in communications. Each sensor shares its data only with neighbors and then achieves global consensus quantities by in-network processing. This dissertation considers robust distributed parameter estimation methods, seeking global consensus on parameters of adaptive learning algorithms and statistical quantities.
Diffusion adaptation strategy with nonlinear transmission is proposed. The nonlinearity was motivated by the necessity for bounded transmit power, as sensors need to iteratively communicate each other energy-efficiently. Despite the nonlinearity, it is shown that the algorithm performs close to the linear case with the added advantage of power savings. This dissertation also discusses convergence properties of the algorithm in the mean and the mean-square sense.
Often, average is used to measure central tendency of sensed data over a network. When there are outliers in the data, however, average can be highly biased. Alternative choices of robust metrics against outliers are median, mode, and trimmed mean. Quantiles generalize the median, and they also can be used for trimmed mean. Consensus-based distributed quantile estimation algorithm is proposed and applied for finding trimmed-mean, median, maximum or minimum values, and identification of outliers through simulation. It is shown that the estimated quantities are asymptotically unbiased and converges toward the sample quantile in the mean-square sense. Step-size sequences with proper decay rates are also discussed for convergence analysis.
Another measure of central tendency is a mode which represents the most probable value and also be robust to outliers and other contaminations in data. The proposed distributed mode estimation algorithm achieves a global mode by recursively shifting conditional mean of the measurement data until it converges to stationary points of estimated density function. It is also possible to estimate the mode by utilizing grid vector as well as kernel density estimator. The densities are estimated at each grid point, while the points are updated until they converge to a global mode.
Diffusion adaptation strategy with nonlinear transmission is proposed. The nonlinearity was motivated by the necessity for bounded transmit power, as sensors need to iteratively communicate each other energy-efficiently. Despite the nonlinearity, it is shown that the algorithm performs close to the linear case with the added advantage of power savings. This dissertation also discusses convergence properties of the algorithm in the mean and the mean-square sense.
Often, average is used to measure central tendency of sensed data over a network. When there are outliers in the data, however, average can be highly biased. Alternative choices of robust metrics against outliers are median, mode, and trimmed mean. Quantiles generalize the median, and they also can be used for trimmed mean. Consensus-based distributed quantile estimation algorithm is proposed and applied for finding trimmed-mean, median, maximum or minimum values, and identification of outliers through simulation. It is shown that the estimated quantities are asymptotically unbiased and converges toward the sample quantile in the mean-square sense. Step-size sequences with proper decay rates are also discussed for convergence analysis.
Another measure of central tendency is a mode which represents the most probable value and also be robust to outliers and other contaminations in data. The proposed distributed mode estimation algorithm achieves a global mode by recursively shifting conditional mean of the measurement data until it converges to stationary points of estimated density function. It is also possible to estimate the mode by utilizing grid vector as well as kernel density estimator. The densities are estimated at each grid point, while the points are updated until they converge to a global mode.
ContributorsLee, Jongmin (Electrical engineer) (Author) / Tepedelenlioğlu, Cihan (Thesis advisor) / Spanias, Andreas (Thesis advisor) / Tsakalis, Konstantinos (Committee member) / Reisslein, Martin (Committee member) / Arizona State University (Publisher)
Created2017
Description
This thesis investigates three different resource allocation problems, aiming to achieve two common goals: i) adaptivity to a fast-changing environment, ii) distribution of the computation tasks to achieve a favorable solution. The motivation for this work relies on the modern-era proliferation of sensors and devices, in the Data Acquisition Systems (DAS) layer of the Internet of Things (IoT) architecture. To avoid congestion and enable low-latency services, limits have to be imposed on the amount of decisions that can be centralized (i.e. solved in the ``cloud") and/or amount of control information that devices can exchange. This has been the motivation to develop i) a lightweight PHY Layer protocol for time synchronization and scheduling in Wireless Sensor Networks (WSNs), ii) an adaptive receiver that enables Sub-Nyquist sampling, for efficient spectrum sensing at high frequencies, and iii) an SDN-scheme for resource-sharing across different technologies and operators, to harmoniously and holistically respond to fluctuations in demands at the eNodeB' s layer.
The proposed solution for time synchronization and scheduling is a new protocol, called PulseSS, which is completely event-driven and is inspired by biological networks. The results on convergence and accuracy for locally connected networks, presented in this thesis, constitute the theoretical foundation for the protocol in terms of performance guarantee. The derived limits provided guidelines for ad-hoc solutions in the actual implementation of the protocol.
The proposed receiver for Compressive Spectrum Sensing (CSS) aims at tackling the noise folding phenomenon, e.g., the accumulation of noise from different sub-bands that are folded, prior to sampling and baseband processing, when an analog front-end aliasing mixer is utilized.
The sensing phase design has been conducted via a utility maximization approach, thus the scheme derived has been called Cognitive Utility Maximization Multiple Access (CUMMA).
The framework described in the last part of the thesis is inspired by stochastic network optimization tools and dynamics.
While convergence of the proposed approach remains an open problem, the numerical results here presented suggest the capability of the algorithm to handle traffic fluctuations across operators, while respecting different time and economic constraints.
The scheme has been named Decomposition of Infrastructure-based Dynamic Resource Allocation (DIDRA).
The proposed solution for time synchronization and scheduling is a new protocol, called PulseSS, which is completely event-driven and is inspired by biological networks. The results on convergence and accuracy for locally connected networks, presented in this thesis, constitute the theoretical foundation for the protocol in terms of performance guarantee. The derived limits provided guidelines for ad-hoc solutions in the actual implementation of the protocol.
The proposed receiver for Compressive Spectrum Sensing (CSS) aims at tackling the noise folding phenomenon, e.g., the accumulation of noise from different sub-bands that are folded, prior to sampling and baseband processing, when an analog front-end aliasing mixer is utilized.
The sensing phase design has been conducted via a utility maximization approach, thus the scheme derived has been called Cognitive Utility Maximization Multiple Access (CUMMA).
The framework described in the last part of the thesis is inspired by stochastic network optimization tools and dynamics.
While convergence of the proposed approach remains an open problem, the numerical results here presented suggest the capability of the algorithm to handle traffic fluctuations across operators, while respecting different time and economic constraints.
The scheme has been named Decomposition of Infrastructure-based Dynamic Resource Allocation (DIDRA).
ContributorsFerrari, Lorenzo (Author) / Scaglione, Anna (Thesis advisor) / Bliss, Daniel (Committee member) / Ying, Lei (Committee member) / Reisslein, Martin (Committee member) / Arizona State University (Publisher)
Created2017
Description
The Internet of Things (IoT) has become a more pervasive part of everyday life. IoT networks such as wireless sensor networks, depend greatly on the limiting unnecessary power consumption. As such, providing low-power, adaptable software can greatly improve network design. For streaming live video content, Wireless Video Sensor Network Platform compatible Dynamic Adaptive Streaming over HTTP (WVSNP-DASH) aims to revolutionize wireless segmented video streaming by providing a low-power, adaptable framework to compete with modern DASH players such as Moving Picture Experts Group (MPEG-DASH) and Apple’s Hypertext Transfer Protocol (HTTP) Live Streaming (HLS). Each segment is independently playable, and does not depend on a manifest file, resulting in greatly improved power performance. My work was to show that WVSNP-DASH is capable of further power savings at the level of the wireless sensor node itself if a native capture program is implemented at the camera sensor node. I created a native capture program in the C language that fulfills the name-based segmentation requirements of WVSNP-DASH. I present this program with intent to measure its power consumption on a hardware test-bed in future. To my knowledge, this is the first program to generate WVSNP-DASH playable video segments. The results show that our program could be utilized by WVSNP-DASH, but there are issues with the efficiency, so provided are an additional outline for further improvements.
ContributorsKhan, Zarah (Author) / Reisslein, Martin (Thesis advisor) / Seema, Adolph (Committee member) / Papandreou-Suppappola, Antonia (Committee member) / Arizona State University (Publisher)
Created2018
Description
Mobile devices have penetrated into every aspect of modern world. For one thing, they are becoming ubiquitous in daily life. For the other thing, they are storing more and more data, including sensitive data. Therefore, security and privacy of mobile devices are indispensable. This dissertation consists of five parts: two authentication schemes, two attacks, and one countermeasure related to security and privacy of mobile devices.
Specifically, in Chapter 1, I give an overview the challenges and existing solutions in these areas. In Chapter 2, a novel authentication scheme is presented, which is based on a user’s tapping or sliding on the touchscreen of a mobile device. In Chapter 3, I focus on mobile app fingerprinting and propose a method based on analyzing the power profiles of targeted mobile devices. In Chapter 4, I mainly explore a novel liveness detection method for face authentication on mobile devices. In Chapter 5, I investigate a novel keystroke inference attack on mobile devices based on user eye movements. In Chapter 6, a novel authentication scheme is proposed, based on detecting a user’s finger gesture through acoustic sensing. In Chapter 7, I discuss the future work.
Specifically, in Chapter 1, I give an overview the challenges and existing solutions in these areas. In Chapter 2, a novel authentication scheme is presented, which is based on a user’s tapping or sliding on the touchscreen of a mobile device. In Chapter 3, I focus on mobile app fingerprinting and propose a method based on analyzing the power profiles of targeted mobile devices. In Chapter 4, I mainly explore a novel liveness detection method for face authentication on mobile devices. In Chapter 5, I investigate a novel keystroke inference attack on mobile devices based on user eye movements. In Chapter 6, a novel authentication scheme is proposed, based on detecting a user’s finger gesture through acoustic sensing. In Chapter 7, I discuss the future work.
ContributorsChen, Yimin (Author) / Zhang, Yanchao (Thesis advisor) / Zhang, Junshan (Committee member) / Reisslein, Martin (Committee member) / Ying, Lei (Committee member) / Arizona State University (Publisher)
Created2018
Description
The commercial semiconductor industry is gearing up for 5G communications in the 28GHz and higher band. In order to maintain the same relative receiver sensitivity, a larger number of antenna elements are required; the larger number of antenna elements is, in turn, driving semiconductor development. The purpose of this paper is to introduce a new method of dividing wireless communication protocols (such as the 802.11a/b/g
and cellular UMTS MAC protocols) across multiple unreliable communication links using a new link layer communication model in concert with a smart antenna aperture design referred to as Vector Antenna. A vector antenna is a ‘smart’ antenna system and as any smart antenna aperture, the design inherently requires unique microwave component performance as well as Digital Signal Processing (DSP) capabilities. This performance and these capabilities are further enhanced with a patented wireless protocol stack capability.
and cellular UMTS MAC protocols) across multiple unreliable communication links using a new link layer communication model in concert with a smart antenna aperture design referred to as Vector Antenna. A vector antenna is a ‘smart’ antenna system and as any smart antenna aperture, the design inherently requires unique microwave component performance as well as Digital Signal Processing (DSP) capabilities. This performance and these capabilities are further enhanced with a patented wireless protocol stack capability.
ContributorsJames, Frank Lee (Author) / Reisslein, Martin (Thesis advisor) / Seeling, Patrick (Thesis advisor) / McGarry, Michael (Committee member) / Zhang, Yanchao (Committee member) / Arizona State University (Publisher)
Created2019
Description
Emerging modular cable network architectures distribute some cable headend functions to remote nodes that are located close to the broadcast cable links reaching the cable modems (CMs) in the subscriber homes and businesses. In the Remote- PHY (R-PHY) architecture, a Remote PHY Device (RPD) conducts the physical layer processing for the analog cable transmissions, while the headend runs the DOCSIS medium access control (MAC) for the upstream transmissions of the distributed CMs over the shared cable link. In contrast, in the Remote MACPHY (R-MACPHY) ar- chitecture, a Remote MACPHY Device (RMD) conducts both the physical and MAC layer processing. The dissertation objective is to conduct a comprehensive perfor- mance comparison of the R-PHY and R-MACPHY architectures. Also, development of analytical delay models for the polling-based MAC with Gated bandwidth alloca- tion of Poisson traffic in the R-PHY and R-MACPHY architectures and conducting extensive simulations to assess the accuracy of the analytical model and to evaluate the delay-throughput performance of the R-PHY and R-MACPHY architectures for a wide range of deployment and operating scenarios. Performance evaluations ex- tend to the use of Ethernet Passive Optical Network (EPON) as transport network between remote nodes and headend. The results show that for long CIN distances above 100 miles, the R-MACPHY architecture achieves significantly shorter mean up- stream packet delays than the R-PHY architecture, especially for bursty traffic. The extensive comparative R-PHY and R-MACPHY comparative evaluation can serve as a basis for the planning of modular broadcast cable based access networks.
ContributorsAlharbi, Ziyad Ghazai (Author) / Reisslein, Martin (Thesis advisor) / Thyagaturu, Akhilesh (Committee member) / Zhang, Yanchao (Committee member) / McGarry, Michael (Committee member) / Arizona State University (Publisher)
Created2019
Description
The goal of this study was to understand elementary school children’s perceptions of engineering. A total of 949 elementary school students were surveyed, individually or as a whole group, to examine gender and age differences in achievement-related beliefs (i.e., competency, interest, and importance) pertaining to engineering-related skills and activities. The results of this study found that specific skills and activities showed significant gender and age differences for each of the three measures. Significant findings showed that younger students (kindergarten through second grade) found many of the engineering-related skills and activities more interesting than the older students (third through fifth grade); however, the older students rated more of the skills and activities as being important. Gender differences showed that girls typically rated themselves as being more competent, more interested in, and valuing the skills and activities that pertained more to mindset ideas, such as learning from your mistakes and failures or not giving up, whereas boys rated themselves higher in more of the hands-on activities, such as building with things like legos, blocks, and k’nex.
ContributorsHandlos, Jamie Lynn Harte (Author) / Miller, Cindy (Thesis director) / Reisslein, Martin (Committee member) / School of Life Sciences (Contributor) / Chemical Engineering Program (Contributor, Contributor) / Barrett, The Honors College (Contributor)
Created2019-05