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Title: Improving spectrum efficiency in heterogeneous wireless networks
Creator: Liu, Chin-Jung
Date: 2018
Collection: Electronic Theses & Dissertations
Description: Over the past decades, the bandwidth-intensive applications that are previously confined to wired networks are now migrating to wireless networks. This trend has brought unprecedented high demand for wireless bandwidth. The wireless traffic is destined to dominate the Internet traffic in the future, but many of the popular wireless spectrum bands, especially the cellular and ISM bands, are already congested. On the other hand, some other wireless technologies, such as TV bands, often do not...
Show moreOver the past decades, the bandwidth-intensive applications that are previously confined to wired networks are now migrating to wireless networks. This trend has brought unprecedented high demand for wireless bandwidth. The wireless traffic is destined to dominate the Internet traffic in the future, but many of the popular wireless spectrum bands, especially the cellular and ISM bands, are already congested. On the other hand, some other wireless technologies, such as TV bands, often do not fully utilize their spectrum. However, the spectrum allocation is tightly regulated by the authority and adjusting the allocation is extremely difficult. The uneven utilization and the rigid regulation have led to the proposal of heterogeneous wireless networks, including cognitive radio networks (CRN) and heterogeneous cellular networks (HetNet). The CRNs that usually operate on different technologies from the spectrum owner attempt to reuse the idle spectrum (i.e., white space) from the owner, while HetNets attempt to improve spectrum utilization by smallcells. This dissertation addresses some of the challenging problems in these heterogeneous wireless networks.In CRNs, the secondary users (SU) are allowed to access the white spaces opportunistically as long as the SUs do not interfere with the primary users (PU, i.e., the spectrum owner). The CRN provides a promising means to improve spectral efficiency, which also introduces a set of new research challenges. We identify and discuss two problems in CRNs, namely non-contiguous control channel establishment and k-protected routing protocol design. The first problem deals with the need from SUs for a channel to transfer control information. Most existing approaches are channel-hopping (CH) based, which is inapplicable to NC-OFDM. We propose an efficient method for guaranteed NC-OFDM-based control channel establishment by utilizing short pulses on OFDM subcarriers. The results show that the time needed for establishing control channel is lower than that of CH-based approaches. The second problem deals with the interruption to a routing path in a CRN when a PU becomes active again. Existing reactive approaches that try to seek for an alternative route after PU returns suffer from potential long delay and possible interruption if an alternative cannot be found. We propose a k-protected routing protocol that builds routing paths with preassigned backups that are guaranteed to sustain from k returning PUs without being interrupted. Our result shows that the k-protected routing paths are never interrupted even when k PUs return, and have significantly shorter backup activation delays.HetNets formed by smallcells with different sizes of coverage and macrocells have been proposed to satisfy increased bandwidth demand with the limited and crowded wireless spectrum. Since the smallcells and macrocells operate on the same frequency, interference becomes a critical issue. Detecting and mitigating interference are two of the challenges introduced by HetNets. We first study the interference identification problem. Existing interference identification approaches often regard more cells as interferers than necessary. We propose to identify interference by analyzing the received patterns observed by the mobile stations. The result shows that our approach identifies all true interferers and excludes most non-interfering cells. The second research problem in HetNets is to provide effective solutions to mitigate the interference. The interference mitigation approaches in the literature mainly try to avoid interference, such as resource isolation that leads to significantly fewer resources, or power control that sacrifices signal quality and coverage. Instead of conservatively avoiding interference, we propose to mitigate the interference by precanceling the interfering signals from known interferers. With precancellation, the same set of resources can be shared between cells and thus throughput is improved.This dissertation addresses several challenges in heterogeneous wireless networks, including CRNs and HetNets. The proposed non-contiguous control channel protocol and k-protected routing protocol for CRNs can significantly improve the feasibility of CRNs in future wireless network applications. The proposed interference identification and interference precancellation approaches can effectively mitigate the interference and improve the throughput and spectrum utilization in HetNets. This dissertation aims at breaking the barriers for supporting heterogeneous wireless networks to improve the utilization of the precious and limited wireless spectrum.
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Title: Damage progression quantification and data robustness evaluation in self-powered sensors networks
Creator: Hasni, Hassene
Date: 2018
Collection: Electronic Theses & Dissertations
Description: "This research proposes novel damage progression quantification and data robustness evaluation approaches, for structural health monitoring (SHM), using a new class of self-powered piezo-floating-gate (PFG) sensors. This system relies on harvesting the mechanical energy from structures through the direct effect of piezoelectricity. The operating power of the smart sensor and the data used for damage identification is harvested directly from the sensing signal induced by a piezoelectric...
Show more"This research proposes novel damage progression quantification and data robustness evaluation approaches, for structural health monitoring (SHM), using a new class of self-powered piezo-floating-gate (PFG) sensors. This system relies on harvesting the mechanical energy from structures through the direct effect of piezoelectricity. The operating power of the smart sensor and the data used for damage identification is harvested directly from the sensing signal induced by a piezoelectric transducer under dynamic loading. The developed models integrate structural simulations using finite element method (FEM) techniques, experimental studies, and statistical and artificial intelligence (AI) methods. In this work, the performance of the sensing system in identifying damage is investigated for various damage scenarios based on numerical and experimental studies. Both steel and pavement structures are studied. A new surface sensing approach for detecting bottom-up cracks in asphalt concrete (AC) pavement is proposed. Two types of self-powered wireless sensors are investigated in this research. Different data interpretation techniques are developed for each type of sensor. The data are obtained from finite element simulations, or experimental measurement, and are fitted to probability distributions to define initial damage indicators. Sensor fusion models are developed based on the concept of group-effect of sensors, in order to increase the damage detection resolution of individual sensors. Probabilistic neural network (PNN) and support vector machine (SVM) methods are used to improve the accuracy of the proposed damage identification methods for the case of multi-class damage progression. The proposed work is divided into four main parts: (i) Damage identification in steel structures using data from a uniform PFG sensor, (ii) Damage detection in steel and pavement structures using a non-uniform PFG sensor, (iii) Damage detection and localization in steel frame structures using hybrid network of self-powered strain and vibration sensors, and, (iv) a field demonstration of the new technology on the Mackinac Bridge in Michigan. The cases of the U10W gusset plate of the I-35W bridge in Minneapolis, MN, a steel girder, a steel plate under compaction tension mode, and an AC beam under three-point bending configuration are investigated. A surface sensing approach to detect bottom-up cracking in AC pavement under dynamic moving load is also proposed. This approach is based on interpreting the data of a surface-mounted network of sensors. Moreover, a hybrid network of strain and vibration-based sensors is used to detect damage in bolted steel frames. The objective is to establish a local-to-global strategy for damage identification in frames. Data fusion models combined with AI classifiers are developed. Uncertainty analysis is performed to verify the performance of the sensors under different noise levels."--Pages ii-iii.
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Title: Design and deployment of low-cost wireless sensor networks for real-time event detection and monitoring
Creator: Phillips, Dennis Edward
Date: 2018
Collection: Electronic Theses & Dissertations
Description: As sensor network technologies become more mature, they are increasingly being applied to a wide variety of environmental monitoring applications, ranging from agricultural sensing to habitat monitoring, oceanic and volcanic monitoring. In this dissertation two wireless sensor networks (WSNs) are presented. One for monitoring residential power usage and another for producing an image of a volcano's internal structure.The two WSNs presented address several common challenges facing modern...
Show moreAs sensor network technologies become more mature, they are increasingly being applied to a wide variety of environmental monitoring applications, ranging from agricultural sensing to habitat monitoring, oceanic and volcanic monitoring. In this dissertation two wireless sensor networks (WSNs) are presented. One for monitoring residential power usage and another for producing an image of a volcano's internal structure.The two WSNs presented address several common challenges facing modern sensor networks. The first is in-network processing and assigning the processing tasks across a heterogeneous network architecture. By efficiently utilizing in-network processing power consumption can be reduced and operational lifetime of the network can be extended. As nodes are embedded into various environments sensing accuracy is intrinsically affected by physical noise. The second challenge relates to how to deal with this noise in a way which increases sensing accuracy. The third challenge is ease of deployment. As WSNs become more common place they will be installed by non-experts.As a key technology of home area networks in smart grids, fine-grained power usage monitoring may help conserve electricity. Smart homes outfitted with network connected appliances will provide this capability in the future. Until smart appliances have wide adaption there is a serious gap in capabilities. To fill this gap an easy to deploy monitoring system is needed. Several existing systems achieve the goal of fine-grained power monitoring by exploiting appliances' power usage signatures utilizing labor-intensive in situ training processes. Recent work shows that autonomous power usage monitoring can be achieved by supplementing a smart meter with distributed sensors that detect the working states of appliances. However, sensors must be carefully installed for each appliance, resulting in high installation cost. Supero is the first ad hoc sensor system that can monitor appliance power usage without supervised training. By exploiting multi-sensor fusion and unsupervised machine learning algorithms, Supero can classify the appliance events of interest and autonomously associate measured power usage with the respective appliances. Extensive evaluation in five real homes shows that Supero can estimate the energy consumption with errors less than 7.5%. Moreover, non-professional users can quickly deploy Supero with considerable flexibility.There are a number of active volcanos around the world with large population areas located nearby. An eruption poses a significant threat to the adjacent population. During times of increased activity being able to obtain a real-time images of the interior would allow seismologists to better understand volcanic dynamics. Volcano tomography can provide this valuable information concerning the internal structure of a volcano. The second sensor network presented in this dissertation is a seismic monitoring sensor network featuring in-network processing of the seismic signals with the capability to perform volcano tomography in real-time. The design challenges, analysis of processing/network processing times in the information processing pipeline, the system designed to meet these challenges and the results from deploying a prototype network on two volcanoes in Ecuador and Chile are presented. The study shows that it is possible to achieve in-network seismic event detection and real-time tomography using a sensor network that is 2 orders of magnitude less expensive than traditional seismic equipment.
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Title: Towards discrete-pulse-based networking and event detection architectures for resource-constrained applications
Creator: Das, Saptarshi (Graduate of Michigan State University)
Date: 2019
Collection: Electronic Theses & Dissertations
Description: "In this dissertation thesis, we develop a scalable and energy-efficient discrete-pulse-based networking architecture along with a Spiking-Neuron-based low-power detection framework for use in resource-constrained settings. Applications such as Structural Health Monitoring (SHM) using wireless sensor networks powered by ambient energy harvesting are particularly suited for such a framework. The key idea in pulse-based networking is to eschew unnecessary overhead as incurred in traditional...
Show more"In this dissertation thesis, we develop a scalable and energy-efficient discrete-pulse-based networking architecture along with a Spiking-Neuron-based low-power detection framework for use in resource-constrained settings. Applications such as Structural Health Monitoring (SHM) using wireless sensor networks powered by ambient energy harvesting are particularly suited for such a framework. The key idea in pulse-based networking is to eschew unnecessary overhead as incurred in traditional packet-based networking and encode only the essential information using small number of discrete pulses and their positions with respect to a synchronized time frame structure. The baseline pulse networking does not scale well with increase in network size. In order to ameliorate this, we develop a scalable time frame structure for use in applications with large network size while preserving the energy advantages of pulse networking. In addition, we stress the importance of judicious use of erratic energy availability in ambient energy harvesting powered systems. To that effect, we build energy-awareness syntaxes within the pulse networking framework for better utilization of energy resources in such systems. We also demonstrate the feasibility of pulse networking over a through-substrate ultrasonic link layer and the advantages thereof in terms of utilizing existing infrastructure and removing the need for radio retrofits. We explore how the protocol performance varies for an airplane stabilizer monitoring application powered by ambient vibration energy harvesting in different energy availability scenarios. Beyond this, we also develop a Spiking-Neuron-based low-power event pattern detection architecture and illustrate how this can be incorporated within a pulse-networked SHM system. The Spiking Neuron based architecture is evidenced to be simpler in terms of implementation but more efficient in terms of computation and energy usage, thus enabling in-situ detection even at intermediate nodes in the network and robust low-power event pattern detection immune to pulse drifts and errors."--Pages ii-iii.
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Title: Wireless sensors for enhancing food supply chain visibility
Creator: Karuppuswami, Saranraj
Date: 2019
Collection: Electronic Theses & Dissertations
Description: "The demand for providing safe and quality food from the farm to the plate had led to the development of sensor technologies for quality control and real-time end-to-end monitoring of food along the supply chain. These advanced sensors serve as the first line of defense against food-borne outbreaks, economically motivated adulteration, and food contamination preventing illness, deaths, huge economic losses and promotes global health and well-being. The key goal is to ensure that the food...
Show more"The demand for providing safe and quality food from the farm to the plate had led to the development of sensor technologies for quality control and real-time end-to-end monitoring of food along the supply chain. These advanced sensors serve as the first line of defense against food-borne outbreaks, economically motivated adulteration, and food contamination preventing illness, deaths, huge economic losses and promotes global health and well-being. The key goal is to ensure that the food reaching the fork meets the highest safety standards by promoting tamper-free sustainable practices along the food supply chain. Real-time food monitoring also prevents unnecessary wastage due to spoilage or good food being thrown out due to misconception of the labeled expiration date. In this dissertation, a number of RF passive wireless sensing approaches are presented that allows simultaneous tracking and quality monitoring of packaged food products as it moves along the supply chain. The end goal is to develop a low cost, long range, battery-free, and real time sensor tag which can detect multiple parameters of the packaged food simultaneously and at the same time provide the identification information. In order to realize a multi-functional sensor tag, a number of sensing approaches are developed targeting four different types of food related quality control challenges; Adulteration, Contamination, Wastage, and Spoilage. To identify and eliminate food adulteration, magnetoelastic based dielectric and viscosity sensors are developed. These hybrid sensors are shorter range sensors and a number of liquid food items such as milk and oil are characterized. A sensing approach that utilizes 3D printed RF sensors coupled to a microfludic channel for liquid profling by monitoring the dielectric constant is developed for food quality detection. Next, to prevent contamination, capacitance based short range inductor-capacitor (LC) tanks are developed. An interdisciplinary approach which is a confluence of carbohydrate coated nano particles capturing bacteria in liquid food with RF detection is developed. A common method to prevent wastage or spoilage is to detect and profile aroma emitted from food. Adsorption, absorption, and capillary condensation based short range as well as long range sensors that monitor the dielectric constant or the conductivity of the target food are developed. First, a short range capillary condensation based sensor is demonstrated for volatile profiling using a porous substrate and an LC tank. This is followed by demonstrating sensitivity and specificity of different thin-film coated short range sensors that detect vapors that are directly related to the spoilage index of the food. Finally, a long range passive sensor integrated with ID is demonstrated for detecting Ammonia in packaged food. The developed sensor is compatible with existing RFID infrastructure and is capable of digitizing the sensor information along with the identification information for transmission. Overall, the work demonstrates that a passive multi-modal sensor provides additional information about products moving across the supply chain transforming the tracebility-centric supply chain into a value-centric one with increased visibility and empowers the different stake holders with the quality information as the product moves along the supply chain."--Pages ii-iii.
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Title: Transmission timing modulation for information coding in energy-constrained wireless networks
Creator: Feng, Dezhi
Date: 2020
Collection: Electronic Theses & Dissertations
Description: The objective of this thesis is to develop a framework of transmission timing-based modulation framework for improving energy efficiency, security, and information transfer capacity in embedded wireless networks with very thin energy budgets. The key idea is to modulate both intra-PDU (Protocol Data Unit) and inter-PDU timing for addressing energy, security, and information transfer capacity in wireless embedded networks. As for energy efficiency, we developed a novel pulse position-coded PDU...
Show moreThe objective of this thesis is to develop a framework of transmission timing-based modulation framework for improving energy efficiency, security, and information transfer capacity in embedded wireless networks with very thin energy budgets. The key idea is to modulate both intra-PDU (Protocol Data Unit) and inter-PDU timing for addressing energy, security, and information transfer capacity in wireless embedded networks. As for energy efficiency, we developed a novel pulse position-coded PDU (PPCP) paradigm. The core idea is to encode a protocol data unit (PDU) in terms of the silence duration between two sets of delimiter pulses, whose positions are modulated based on the value of the PDU. This PPCP architecture achieves significant energy savings by using a lesser amount of bit/pulse transmissions, and by eliminating long multi-bit preambles and headers, which are normally used in traditional packets. The proposed multi-access pulse-based PDU scheme enables medium sharing among many sensor nodes without requiring per-PDU frame synchronization. As for security, we developed the concept of a novel chaotic pulse position coded protocol data unit (CPPCP) for secure embedded networking. The core idea of CPPCP is to encode a protocol data unit (PDU) with a wideband pulse train with chaotically-varied inter-pulse intervals. The architecture ensures communication security by introducing randomness between data symbols, noise-like frequency spectrum, and significant energy savings by using a smaller number of pulse transmissions compared to existing secure coding schemes such as Bluetooth Low Energy (BLE). Compared with the traditional key-based cryptographic techniques, CPPCP suppresses decipherable information by eliminating symbol periodicity. The mechanism can also be piggy-backed on traditional cryptography solutions to achieve higher levels of security. Finally, for enhancing the information transfer capacity, we developed a data packet position modulation (DPPM) paradigm. Packet transmissions in low duty cycle networks are often scheduled as TDMA slots, whose periodicity is determined based on application sampling requirements and the energy in-flow, often in the form of energy harvesting. The key idea of DPPM is to modulate the inter-packet spacing for coding additional information without incurring additional transmission energy expenditures. We first developed a have a DPPM based networking solution for single-hop transmit-only networks in which a number of low-energy nodes transmit data to an aggregator. The architecture is developed for a two-node point-to-point link, followed by a multipoint-to-point multi-access network. Detailed analytical and simulation models are developed to demonstrate the performance of a symmetric and an asymmetric version of DPPM.
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Title: Gliding robotic fish : design, collaborative estimation, and application to underwater sensing
Creator: Ennasr, Osama Nasr
Date: 2020
Collection: Electronic Theses & Dissertations
Description: Autonomous underwater robots have received significant attention over the past two decades due to the increasing demand for environmental sustainability. Recently, gliding robotic fish has emerged as a promising mobile sensing platform in versatile aquatic environments. Such robots, inspired by underwater gliders and robotic fish, combine buoyancy-driven gliding and fin-actuated swimming to realize both energy-efficient locomotion and high maneuverability. In this dissertation, we first...
Show moreAutonomous underwater robots have received significant attention over the past two decades due to the increasing demand for environmental sustainability. Recently, gliding robotic fish has emerged as a promising mobile sensing platform in versatile aquatic environments. Such robots, inspired by underwater gliders and robotic fish, combine buoyancy-driven gliding and fin-actuated swimming to realize both energy-efficient locomotion and high maneuverability. In this dissertation, we first discuss the design improvements for the second-generation gliding robotic fish "Grace 2". These improvements have transformed the robots to underwater sensing platforms that can be modified to fit the requirements of a specific application with relative ease.We focus on the application of detecting and tracking live fish underwater, which is an important part of fishery research, as it helps scientists understands habitat use, migratory patterns, and spawning behavior of fishes. The gliding robotic fish has demonstrated its ability to detect special acoustic signals emulating tagged fish through a series of trials in Higgins Lake, Michigan. These tests have also validated a gliding-based strategy for navigating to a GPS waypoint, and offered insight into the limitations of the current design. Additional improvements are proposed to allow these robots to glide at larger depths and perform more interesting working patterns underwater.Motivated by the problem of tracking real fish, we consider the case where multiple robots localize and track a moving target without the need for a centralized node. We present theoretical treatment on how a network of robots can infer the location of an emitter (or target), and then track it, through a time-difference-of-arrival (TDOA) localization scheme in a fully distributed manner. In particular, we utilize a networked extended Kalman filter to estimate the target's location in a distributed manner, and establish that successful localization can be achieved under fixed and time-varying undirected communication topologies if every agent is part of a network with a minimum of 4 connected, non-coplanar agents. We further propose a movement control strategy based on the norm of the estimation covariance matrices, with a tuning parameter to balance the trade-off between estimation performance and the total distance traveled by the robots.Finally, motivated by the distributed localization problem, we investigate a more general problem of distributed estimation by a network of sensors. Specifically, we consider the class of consensus-based distributed linear filters (CBDLF) where each sensor updates its estimate in two steps: a consensus step dictated by a weighted and directed communication graph, followed by a local Luenberger filtering step. We show that the sub-optimal filtering gains that minimize an upper bound of a quadratic filtering cost are related to the convergence of a set of coupled Riccati equations. Then we show that the convergence of these coupled Riccati equations depends on the notion of squared detectability for the networked system, and proceed to provide necessary conditions that link the convergence of the coupled Riccati equations to the network topology and consensus weights of the communication graph.
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