Date of Award

Fall 2021

Publication Type

Thesis

Degree Name

M.Sc.

Department

Computer Science

Keywords

Complex networks, Fault tolerance, Network resilience, Network topology, Small world networks, Transportation networks

Supervisor

Y. Aneja

Supervisor

P. Zadeh

Rights

info:eu-repo/semantics/openAccess

Abstract

Complex networks are ubiquitous; consider, for example, road networks, protein-protein interaction networks, metabolic networks, power networks etc. They can be applied to a wide range of areas like mathematics, computer science, social, and biological sciences. Random graphs can aid in observing the topological features in various data sources and give insights on their respective real-world networks. In this thesis, we study the particular case of small-world networks and compare them with random and regular networks. We start by explaining the complexity of networks and how graph theory can be applied to complex networks to understand their topological properties. Using which, we can tell how nodes and edges are arranged in a complex networks. We study some of the network models based on this work, elaborating how we can use these models to explain their topological properties. Finally, we conduct an empirical study on Transportation networks to demonstrate the efficacy of the proposed framework. Due to urbanization, more than half of the world population live in cities currently. To overcome the rapid urbanization in a sustainable manner, transit systems all around the world are likely to grow. By studying transportation networks as a complex network, this thesis identifies the properties and effects of road network designs using a graph theory approach. We observe that our network model follows small world properties and, finally, some future works are proposed in this area of research.

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