Integrative Modeling, Simulation, and Optimization Techniques for Efficient Data-Intensive Applications in Edge Computing Infrastructures

The fourth industrial revolution is blurring the boundaries between the physical and digital worlds. New solutions are becoming increasingly complex and involve expertise in multiple domains. Thus, they can no longer be considered stand-alone solutions but a system of systems comprising devices, users, and other supporting systems. Their conception, design, and deployment require a thorough analysis of the scenario to be successful. Modeling and simulation-based systems engineering (MSBSE) applies advanced Modeling and Simulation (M&S) techniques to ensure a logical, robust, and reliable incremental design, allowing the technical risks of the system to be assessed while lowering the costs of the solution under development. However, these methods still have different shortcomings. This thesis proposes a novel approach that integrates Modeling, Simulation, and Optimization methodologies for developing complex systems. This holistic view emphasizes using formal modeling tools to build more robust and reliable solutions. Simulation is the main tool to verify that the proposed model meets the system requirements. It also incorporates optimization techniques to automate design decisions and improve the system under development performance. We provide an in-depth study of formal modeling, simulation, and optimization approaches to aid the development of more robust solutions throughout the design and development of complex systems. We then propose a new process for integrating these modeling, simulation, and optimization techniques. In addition, we explore techniques for improving simulation performance to accelerate the proposed system development process. Finally, we define an M&S-agnostic optimization framework that integrates different optimization algorithms to improve the performance of any complex system under development. Decoupling the optimization tools from the specific problem allows us to reuse the optimization tools for multiple systems under study. We define a use case of a complex system to elaborate on the proposed methodology. Namely, we focus on federated Edge Computing infrastructures. This use case can benefit significantly from the proposed workflow, as the number of interconnected devices is growing exponentially and the current infrastructures are becoming saturated. Edge Computing stands out as a technology enabler for new services that require intensive, distributed real-time computation.

Name thesis:degree_name

Doctor of Philosophy (Ph.D.)

Level thesis:degree_level

Doctoral

Discipline thesis:degree_discipline

Engineering, Electrical and Computer

Grantor dc:publisher

Carleton University

Year dc:date.issued

2024

Author dc:creator

• Cardenas Rodriguez, Roman

Statement dc:rights

• Copyright © 2023 the author(s). Theses may be used for non-commercial research, educational, or related academic purposes only. Such uses include personal study, distribution to students, research and scholarship. Theses may only be shared by linking to the Carleton University Institutional Repository and no part may be copied without proper attribution to the author; no part may be used for commercial purposes directly or indirectly via a for-profit platform; no adaptation or derivative works are permitted without consent from the copyright owner.

Language dc:language.iso

en

DOI

10.22215/etd/2023-15873

OAI identifier oai:identifier

oai:carleton.scholaris.ca:20.500.14718/41339