UWSpace
UWSpace is the University of Waterloo’s institutional repository for the free, secure, and long-term home of research produced by faculty, students, and staff.
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Recent Submissions
Evaluating Container-based and WebAssembly-based Serverless Platforms
(University of Waterloo, 2024-10-04) Monum, Abdul
Serverless computing, often also referred to as Function-as-a-Service (FaaS), allows de- velopers to write scalable event-driven applications while the cloud provider manages the burden of provisioning and maintaining compute resources. Serverless computing is en- abled using virtualized sandboxes like containers or lightweight virtual machines that form the execution units for FaaS applications. However, applications suffer from expensive startup latency (cold starts) due to the compulsory overhead of creating a sandbox and initializing the application code and its dependencies. FaaS platforms keep function ex- ecutors warm in memory to avoid this latency which incurs additional memory overhead on the system. Recently, WebAssembly (Wasm) has emerged as a promising alternative for FaaS applications with its lightweight sandboxing, providing negligible startup delays and reduced memory footprint. However, Wasm applications experience slower execution speeds compared to native execution. This thesis presents a performance evaluation of WebAssembly-based serverless computing in comparison with container-based serverless platforms using analytical performance models and its experimental evaluation. The per- formance model for container-based serverless platforms is used from existing literature, reflecting the behavior of commercial platforms like AWS Lambda, IBM Cloud Functions, and Azure Functions. For WebAssembly-based serverless platforms, this thesis proposes a new performance model based on queueing systems. These models are verified exper- imentally using open-source platforms: Apache OpenWhisk for containers and Spin for WebAssembly. A suite of representative serverless applications is used to validate the models. The comparison of the performance models with experimental results highlights the trade-offs between container-based and WebAssembly-based serverless platforms, pro- viding insights into their respective efficiencies in handling serverless workloads.
This is a test submission
(Springer, 2024) Carmini, Priscilla
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Exploring Tourism Inclusion: Perspectives of Older Adults in St. Jacobs
(University of Waterloo, 2024-10-01) Liang, Jianing
The profit-driven and pro-growth tourism industry, driven by capitalist models, has long exploited resources from communities and caused inequities (Fletcher, 2011; Becken and Kaur, 2022). The COVID-19 pandemic’s interruption of tourism has not only revealed its vulnerability, but also created an opportunity for researchers to reconsider its problematic practices and advocate for a potential shift toward greater sustainability and resilience (Ma et al., 2020; Becken and Kaur, 2022; Bellato et al., 2022). One approach is regenerative tourism, which prioritizes the well-being of destination communities by leveraging tourism resources for regeneration (Pollock, 2019). Acknowledging the unique characteristics of each community, regenerative tourism promotes collaboration among all stakeholders to address diverse community needs inclusively (Becken and Kaur, 2022).
Existing literature on regenerative tourism suffers from a notable gap in the limited attention given to the involvement of older adult residents as community stakeholders in tourism. The ways in which tourism can benefit older adult residents remains relatively unexplored (Chang et al., 2022). Therefore, this proposed research seeks to explore the tourism needs and participation of older adult residents in St. Jacobs Village, aiming to promote inclusive stakeholder engagement for a marginalized group. To achieve this, Arts-Based Research methods, focus group, and individual interview were employed to gain insights from older adult participants and facilitate the sharing of their experiences and perspectives on St. Jacobs Village’s active engagement in tourism.
Non-Stationary Stochastic Modelling of Climate Hazards for Risk and Reliability Assessment
(University of Waterloo, 2024-10-01) Bhadra, Rituraj
This thesis presents methodologies for studying the effects of climate change on natural hazards.
The thesis is structured around three key aspects: first, the stochastic modelling of non-stationary hazards; second, the modelling of concrete degradation in a changing climate; and third, the economic risk evaluation associated with these non-stationary hazards.
The initial focus of this thesis is on applying a non-stationary stochastic process to model the increasing frequency and intensity of climate-driven hazards in Canada. The early chapters provide an overview of the effects of climate change in Canada.
To understand the trends and projections of various climatic variables, such as temperature, precipitation, and wind speed, recent studies and reports from Environment and Climate Change Canada, along with other relevant literature, are examined and analyses were performed on the model outputs of the Couple Model Inter-comparison Project Phase 6 (CMIP6) data. The overview highlights the growing occurrence and severity of climate hazards, including hurricanes, droughts, wildfires, and heatwaves, as supported by other independent studies. In the light of such analyses, this study demonstrates the inadequacy of traditional stationary models for future predictions and risk assessments, thereby advocating for a shift to non-stationary frameworks.
The thesis provides a robust theoretical foundation for non-stationary hazard modelling using stochastic process models. Traditional extreme value analysis (EVA) typically assumes stationarity. However, this assumption is invalidated by gradual changes in the frequency and intensity of climate-driven hazards.
This research proposes methodologies to model climatic hazards using a non-stationary stochastic shock process, specifically the non-homogeneous Poisson process (NHPP), to derive the maximum value distributions over any finite period and not just restricted to annual maxima. These models account for changes in the underlying processes over time, providing a more accurate representation of climate-driven hazards by incorporating time-varying parameters that reflect the dynamic nature of climatic extremes.
By integrating stochasticity and temporal variability, these stochastic process models offer a robust framework for predicting the future occurrence and intensity of climate-driven hazards. The proposed methods are demonstrated through the estimation of maximum value distributions for precipitation events using the Coupled Model Inter-comparison Project (CMIP) phase-6 multi-model ensemble data, with an analysis of inter-model variability.
Furthermore, the thesis presents a case study on modeling heatwaves to illustrate the application of these models to climatic data, particularly for events where the asymptotic assumptions of extreme value theory do not hold.
Climate change will not only influence the loads and hazards on infrastructure, but it will also exacerbate the degradation processes of structures due to harsher climatic conditions such as higher temperatures and increased humidity. To model these effects on the degradation of concrete bridges, simulations were conducted using physico-chemical concrete degradation processes. Based on the simulation results, non-stationary Markov transition probabilities were estimated for several key locations in Canada under various Shared Socioeconomic Pathway (SSP) scenarios.
The final chapter of the thesis addresses the economic aspects of climate-driven hazards. It includes derivations to estimate various statistics of damage costs, such as the mean, variance, moments, and distribution, resulting from a non-stationary hazard process. The analytical results were derived for several cases, such as considering the loss magnitudes to be identically and non-identically distributed, and whether discounting is applied to the losses or not to address the effect of time in evaluating the net present losses or not. This analysis offers valuable information for policy makers, engineers, and scientists involved in climate adaptation and mitigation efforts.
Camera Calibration from Out-of-Focus Images
(University of Waterloo, 2024-10-01) Schmalenberg, Ryan
For many 3D computer vision applications, accurate camera calibration is a necessary pre-requisite task. Generally, the objective is to find a camera’s intrinsic parameters such as focal lengths, or extrinsic parameters such as the camera’s pose in 3D space, or both. Camera calibration using structured calibration targets relies on special patterns which contain features that are used to localize control points with sub-pixel accuracy. The most frequently used patterns are checkerboards and circle grids, and in well constrained environments, these patterns are known to provide accurate feature correspondences for accurate camera calibration results.
One challenging case for camera calibration is in the instance of calibrating a long focal length camera. In this case, the focal plane can be too far away in distance, and the only practical solution is to capture images of the calibration pattern out-of-focus while it is closer to the camera. Due to the radial distribution of out-of-focus blur, and biases created by a lack of distance preservation, as well as changes in spatial blur with perspective, checkerboard patterns have been proven to lose accuracy when they are captured in out-of-focus images, and with increased blur, can fail to provide feature correspondences all together.
To address this, phase-shift circular gradient (PCG) patterns had been proposed as a method to encode control point positions into phase distributions, rather than through pixel intensities. Our work aims to validate previous authors claims of out-of-focus blur invariance and accuracy when using PCG patterns. Using PCG, small circle, and concentric circle grid patterns, we made comparisons using their respective retrieved pixel value focal lengths, and in-focus vs. out-of-focus percentage differences.
Initial comparisons showed that PCGs were largely invariant to blur. However, their accuracy was marginally worse than comparable small circles when real-world noise was introduced. In this real case, a 7-DOF robot arm was used for repeatable calibration target positioning. The recorded set of poses was also used to mirror conditions in a further synthetic experiment. From this work, PCGs initially showed mixed results, but when extended beyond real-world conditions, PCGs were the only pattern that worked under the most severe levels of out-of-focus blur. This validated their improved detectability under extreme blur, and theoretical effectiveness for use with long focal length cameras.
From these results, this study acknowledges the trade-offs in calibration pattern selection for respective use cases. It also highlights the importance of ellipse fitting techniques, as well as acknowledging the role of other learned methods. Finally, this study outlines the benefits that were observed when using robotic target positioning, and our synthetic validation pipeline for experimentation with calibration patterns under various conditions.