52 research outputs found
University of Windsor Graduate Calendar 2023 Spring
https://scholar.uwindsor.ca/universitywindsorgraduatecalendars/1027/thumbnail.jp
University of Windsor Graduate Calendar 2023 Winter
https://scholar.uwindsor.ca/universitywindsorgraduatecalendars/1026/thumbnail.jp
On-premise containerized, light-weight software solutions for Biomedicine
Bioinformatics software systems are critical tools for analysing large-scale biological
data, but their design and implementation can be challenging due to the need for reliability, scalability, and performance. This thesis investigates the impact of several
software approaches on the design and implementation of bioinformatics software
systems. These approaches include software patterns, microservices, distributed
computing, containerisation and container orchestration. The research focuses on
understanding how these techniques affect bioinformatics software systems’ reliability, scalability, performance, and efficiency. Furthermore, this research highlights
the challenges and considerations involved in their implementation. This study also
examines potential solutions for implementing container orchestration in bioinformatics research teams with limited resources and the challenges of using container
orchestration. Additionally, the thesis considers microservices and distributed computing and how these can be optimised in the design and implementation process to
enhance the productivity and performance of bioinformatics software systems. The
research was conducted using a combination of software development, experimentation, and evaluation. The results show that implementing software patterns can
significantly improve the code accessibility and structure of bioinformatics software
systems. Specifically, microservices and containerisation also enhanced system reliability, scalability, and performance. Additionally, the study indicates that adopting
advanced software engineering practices, such as model-driven design and container
orchestration, can facilitate efficient and productive deployment and management of
bioinformatics software systems, even for researchers with limited resources. Overall, we develop a software system integrating all our findings. Our proposed system
demonstrated the ability to address challenges in bioinformatics. The thesis makes
several key contributions in addressing the research questions surrounding the design,
implementation, and optimisation of bioinformatics software systems using software
patterns, microservices, containerisation, and advanced software engineering principles and practices. Our findings suggest that incorporating these technologies can
significantly improve bioinformatics software systems’ reliability, scalability, performance, efficiency, and productivity.Bioinformatische Software-Systeme stellen bedeutende Werkzeuge für die Analyse
umfangreicher biologischer Daten dar. Ihre Entwicklung und Implementierung kann
jedoch aufgrund der erforderlichen Zuverlässigkeit, Skalierbarkeit und Leistungsfähigkeit eine Herausforderung darstellen. Das Ziel dieser Arbeit ist es, die Auswirkungen von Software-Mustern, Microservices, verteilten Systemen, Containerisierung
und Container-Orchestrierung auf die Architektur und Implementierung von bioinformatischen Software-Systemen zu untersuchen. Die Forschung konzentriert sich
darauf, zu verstehen, wie sich diese Techniken auf die Zuverlässigkeit, Skalierbarkeit,
Leistungsfähigkeit und Effizienz von bioinformatischen Software-Systemen auswirken
und welche Herausforderungen mit ihrer Konzeptualisierungen und Implementierung
verbunden sind. Diese Arbeit untersucht auch potenzielle Lösungen zur Implementierung von Container-Orchestrierung in bioinformatischen Forschungsteams mit begrenzten Ressourcen und die Einschränkungen bei deren Verwendung in diesem Kontext. Des Weiteren werden die Schlüsselfaktoren, die den Erfolg von bioinformatischen Software-Systemen mit Containerisierung, Microservices und verteiltem Computing beeinflussen, untersucht und wie diese im Design- und Implementierungsprozess optimiert werden können, um die Produktivität und Leistung bioinformatischer
Software-Systeme zu steigern. Die vorliegende Arbeit wurde mittels einer Kombination aus Software-Entwicklung, Experimenten und Evaluation durchgefĂĽhrt. Die
erzielten Ergebnisse zeigen, dass die Implementierung von Software-Mustern, die Zuverlässigkeit und Skalierbarkeit von bioinformatischen Software-Systemen erheblich
verbessern kann. Der Einsatz von Microservices und Containerisierung trug ebenfalls zur Steigerung der Zuverlässigkeit, Skalierbarkeit und Leistungsfähigkeit des
Systems bei. DarĂĽber hinaus legt die Arbeit dar, dass die Anwendung von SoftwareEngineering-Praktiken, wie modellgesteuertem Design und Container-Orchestrierung,
die effiziente und produktive Bereitstellung und Verwaltung von bioinformatischen
Software-Systemen erleichtern kann. Zudem löst die Implementierung dieses SoftwareSystems, Herausforderungen für Forschungsgruppen mit begrenzten Ressourcen. Insgesamt hat das System gezeigt, dass es in der Lage ist, Herausforderungen im Bereich
der Bioinformatik zu bewältigen und stellt somit ein wertvolles Werkzeug für Forscher in diesem Bereich dar. Die vorliegende Arbeit leistet mehrere wichtige Beiträge
zur Beantwortung von Forschungsfragen im Zusammenhang mit dem Entwurf, der
Implementierung und der Optimierung von Software-Systemen fĂĽr die Bioinformatik unter Verwendung von Prinzipien und Praktiken der Softwaretechnik. Unsere
Ergebnisse deuten darauf hin, dass die Einbindung dieser Technologien die Zuverlässigkeit, Skalierbarkeit, Leistungsfähigkeit, Effizienz und Produktivität bioinformatischer Software-Systeme erheblich verbessern kann
Universal Database System Analysis for Insight and Adaptivity
Database systems are ubiquitous; they serve as the cornerstone of modern
application infrastructure due to their efficient data access and
storage. Database systems are commonly deployed in a wide range of environments,
from transaction processing to analytics.
Unfortunately, this broad support comes with a trade-off in system
complexity. Database systems contain many components and features that
must work together to meet client demand. Administrators responsible
for maintaining database systems face a daunting task: they must
determine the access characteristics of the client workload they are
serving and tailor the system to optimize for
it. Complicating matters, client workloads are known to shift in
access patterns and load. Thus, administrators continuously
perform this optimization task, refining system design and
configuration to meet ever-changing client request patterns.
Researchers have focused on creating next-generation, natively adaptive database systems to
address this administrator burden. Natively adaptive database systems construct
client-request models, determine workload characteristics, and tailor
processing strategies to optimize accordingly. These systems
continuously refine their models, ensuring they are responsive to
workload shifts. While these new systems show promise in adapting system
behaviour to their environment, existing, popularly-used database systems
lack these adaptive capabilities. Porting the ideas in these new
adaptive systems to existing infrastructure requires monumental
engineering effort, slowing their adoption and leaving users stranded
with their existing, non-adaptive database systems.
In this thesis, I present Dendrite, a framework that easily
``bolts on'' to existing database systems to endow them with adaptive
capabilities. Dendrite captures database system behaviour in
a system-agnostic fashion, ensuring that its techniques are
generalizable. It compares captured behaviour to determine
how system behaviour changes over time and with respect to idealized
system performance. These differences are matched against
configurable adaption rules, which deploy user-defined
functions to remedy performance problems. As such, Dendrite can
deploy whatever adaptions are necessary to address a behaviour shift
and tailor the system to the workload at hand. Dendrite
has low tracking overhead, making it practical for intensive database
system deployments
University of Windsor Graduate Calendar 2022 Fall
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University of Windsor Graduate Calendar 2022 Winter
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University of Windsor Graduate Calendar 2022 Spring
https://scholar.uwindsor.ca/universitywindsorgraduatecalendars/1024/thumbnail.jp
Applications and Experiences of Quality Control
The rich palette of topics set out in this book provides a sufficiently broad overview of the developments in the field of quality control. By providing detailed information on various aspects of quality control, this book can serve as a basis for starting interdisciplinary cooperation, which has increasingly become an integral part of scientific and applied research
University of Windsor Graduate Calendar 2021 Fall
https://scholar.uwindsor.ca/universitywindsorgraduatecalendars/1022/thumbnail.jp
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