All ETDs from UAB

Advisory Committee Chair

Murat M Tanik

Advisory Committee Members

Leon Jololian

Mohammad R Haider

Karthik Lingasubramanian

Buren Earl Wells

Document Type

Dissertation

Date of Award

2022

Degree Name by School

Doctor of Philosophy (PhD) School of Engineering

Abstract

As main characteristics of successful smart cities, the high demand for increased data security and accessibility and citizen engagement mean the role of blockchain technology has begun to increase. Nonetheless, blockchain technology also faces several challenges, which have slowed its adoption. In response, this dissertation introduces a framework for designing blockchain systems in a smart city setting and considers the smart city and blockchain challenges. Researchers have proposed several smart city models that study and analyze the complexity of smart cities to improve city security, functionality, services, and smartness. The proposed information-theoretical modeling approach to generate an innovated blockchain model in a smart city setting. This work relies on the following previous modeling investigations: PArchitect, Conant’s method, and the least action principle (LAP). Utilizing all of these techniques and organizing them within a framework in the best possible way will improve the blockchain systems in smart cities. We utilize the universal information-theoretical modeling approach and other techniques developed by Dr. Murat M. Tanik and his team. They have successfully developed an excellent modeling technique that plays a significant role in modeling complex systems. The framework begins with the PArchitect step, which is followed by a Conant analysis, and concludes with the LAP step. First, we model a real-life system using PArchitect, which is a value-based driven molding technique, then perform analytics with iv Conant’s method. Conant’s method plays a significate role in reducing the complexity level and enabling a profound understanding of the system. This is followed by the LAP step. The role of the framework is to minimize blockchain challenges. The blockchain is continuously in a trade-off with decentralization, security, and scalability, hence, in-depth analysis is required to optimize the trade-off. We propose to utilize LAP to find the best possible distribution of blockchain full nodes (cluster heads) in a blockchain city. Furthermore, LAP plays a major role in clustering the blockchain network. By applying this framework, we minimize the energy and scalability issues in the blockchain and provide capability continuity after modeling that nearly decomposes them, along with a deep understanding of the smart city systems.

Included in

Engineering Commons

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