CS60078: Complex Network Theory

CS60078
Course name	Complex Network Theory
Offered by	Computer Science & Engineering
Credits	3
L-T-P	3-0-0
Previous Year Grade Distribution
1 1 1 2 EX A B C D P F
Semester	Spring

Syllabus

Syllabus mentioned in ERP

Objectivesâ¢Study of the models and behaviors of networked systems.â¢Empirical studies of social, biological, technological and information networks.â¢Exploring the concepts of small world effect, degree distribution, clustering, network correlations, random graphs, models of network growth, and preferential attachment and dynamical processes taking place on networks.ContentTypes of network: Social networks, Information networks, Technological networks, Biological networks.Properties of network: Small world effect, transitivity and clustering, degree distribution, scale free networks, maximum degree; network resilience; mixing patterns; degree correlations; community structures; network navigation.Random Graphs: Poisson random graphs, generalized random graphs, the configuration model, power-law degree distribution, directed graph, bipartite graph, degree correlations.Models of network growth: Prices model, Barabasi and Alberts model, other growth models, vertex copying models.Processes taking place on networks: Percolation theory and network resilience, Epidemiological processes.Applications: Search on networks, exhaustive network search, guided network search, network navigation; network visualization.References1.S. N. Dorogovtsev and J. F. F. Mendes, Evolution of Networks, Oxford University Press.2.Narsingh Deo, Graph Theory, Prentice Hall of India.3.Current Literature.