Estimating characteristics of large graphs via sampling is a vital part of the study of complex networks. Current sampling methods such as (independent) random vertex and random w...
It has been observed that the degrees of the topologies of several communication networks follow heavy tailed statistics. What is the impact of such heavy tailed statistics on the...
—In this paper, we study the sensitivity of centrality metrics as a key metric of social networks to support visual reasoning. As centrality represents the prestige or importance...
It appeared recently that the classical random graph model used to represent real-world complex networks does not capture their main properties. Since then, various attempts have ...
A pervasive requirement of distributed systems is to deal with churn — change in the set of participating nodes due to joins, graceful leaves, and failures. A high churn rate ca...