Year: 2024
Type: conference-paper
Abstract: Generating synthetic networks with special properties is an important topic of research in network science.Generative algorithms enable researchers to replicate complex network structures, facilitating in-depth analysis and validate different algorithms.One such important type of networks is a scale-free network.Many real networks, irrespective of their discipline, function or scope follow the scale free property.In a scale-free network the vertex connectivity follows a power-law distribution where the probability of a vertex having degree 𝑘 is proportional to 𝑘 -𝛾 with 2 < 𝛾 < 3. Starting from Albert-Barabasi model, numerous models have been developed to generate scale-free networks.But generative models for scale-free networks of desired graph (network) classes has been a key scope of work.In this paper, we focus on two special graph classes called caterpillars and series-parallel networks.We characterize the value of 𝛾 required for constructing a scale-free caterpillar network and provide an 𝑂 (𝑛) algorithm for generating scale-free caterpillar networks of 𝑛 vertices.We also provide an 𝑂 (𝑚) algorithm for generating scale-free series-parallel networks of 𝑚 edges.
Authors: Mahdee Mushfique Kamal, Sujoy Das, Md. Saidur Rahman
Institution: Bangladesh University of Engineering and Technology
Language: English
Subfield: Statistical and Nonlinear Physics
Field: Physics and Astronomy
Domain: Physical Sciences
Open Access status: bronze
OpenAlex ID: W4411097633