MSc Thesis Proposal of Pooja Chakrabarthy:"Exploring the effect of small world properties in Transportation Networks "

 

Date: Friday May 14, 2021 

Time: 10:00 AM – 12:00 PM 

Meeting URL:  https://zoom.us/j/97442781196?from=addon 

Passcode:    If interested in attending the event, contact the Graduate Secretary at csgradinfo@uwindsor.ca

 

Real world networks such as computer networks, biological networks, neural networks, social networks often possess topological properties which cannot simply be explained by networks having a completely regular or random graph structure, rather they lie somewhere between these two extremes and are often known as small world networks. Studying small world networks using graph theory technique is simple, yet powerful, because it helps in capturing real-world network properties. In this thesis, we study the nontrivial topological properties like average clustering, degree distribution, shortest path length in such complex real-world networks and different conditions necessary for these properties to emerge in a graph. These properties plays a crucial role in determining the structure and functions of the network and help as a foundation for understanding the interactions within the networks where different entities are represented as vertices and the relationships between them as links. The specific case of public transport can be modeled as a network with stops as vertices and connections between consecutive stops as links. We conduct an empirical study on road transportation networks, which is of crucial importance in the modern world. We compare and contrast their distinctive structural properties with those of fully regular and random graphs and quantify their efficiency. We conclude this work outlining some possible future research directions. 

 

Keywords: Complex Network, Graphs, Small World Network, Topological Properties, Transportation Networks 

 

Internal Reader: Dr Pooya Moradian Zadeh  

External Reader: Dr Yash Aneja          

Advisor: Dr Asish Mukhopadhyay