Degree Correlation in Scale-Free Graphs

نویسندگان

  • Babak Fotouhi
  • Michael G. Rabbat
چکیده

We obtain closed form expressions for the expected conditional degree distribution and the joint degree distribution of the linear preferential attachment model for network growth in the steady state. We consider the multiple-destination preferential attachment growth model, where incoming nodes at each timestep attach to β existing nodes, selected by degree-proportional probabilities. By the conditional degree distribution p(`|k), we mean the degree distribution of nodes that are connected to a node of degree k. By the joint degree distribution p(k, `), we mean the proportion of links that connect nodes of degrees k and `. In addition to this growth model, we consider the shifted-linear preferential growth and solve for the same quantities, as well as a closed form expression for its steady-state degree distribution.

برای دانلود متن کامل این مقاله و بیش از 32 میلیون مقاله دیگر ابتدا ثبت نام کنید

ثبت نام

اگر عضو سایت هستید لطفا وارد حساب کاربری خود شوید

منابع مشابه

Degree-degree correlations in random graphs with heavy-tailed degrees

We investigate degree-degree correlations for scale-free graph sequences. The main conclusion of this paper is that the assortativity coefficient is not the appropriate way to describe degreedependences in scale-free random graphs. Indeed, we study the infinite volume limit of the assortativity coefficient, and show that this limit is always non-negative when the degrees have finite first but i...

متن کامل

On merging and dividing of Barabási-Albert-graphs

The Barabási-Albert-model is commonly used to generate scale-free graphs, like social networks. To generate dynamics in these networks, methods for altering such graphs are needed. Growing and shrinking is done simply by doing further generation iterations or undo them. In our paper we present four methods to merge two graphs based on the Barabási-Albertmodel, and five strategies to reverse the...

متن کامل

Correlation Analysis between Maximal Clique Size and Centrality Metrics for Random Networks and Scale-Free Networks

The high-level contribution of this paper is a comprehensive analysis of the correlation levels between node centrality (a computationally light-weight metric) and maximal clique size (a computationally hard metric) in random network and scale-free network graphs generated respectively from the well-known Erdos-Renyi (ER) and Barabasi-Albert (BA) models. We use three well-known measures for eva...

متن کامل

epl draft Architectural and functional connectivity in scale-free integrate- and-fire networks

Using integrate-and-fire networks, we study the relationship between the architectural connectivity of a network and its functional connectivity as characterized by the network’s dynamical properties. We show that dynamics on a complex network can be controlled by the topology of the network, in particular, scale-free functional connectivity can arise from scale-free architectural connectivity,...

متن کامل

Recursive graphs with small-world scale-free properties.

We discuss a category of graphs, recursive clique trees, which have small-world and scale-free properties and allow a fine tuning of the clustering and the power-law exponent of their discrete degree distribution. We determine relevant characteristics of those graphs: the diameter, degree distribution, and clustering parameter. The graphs have also an interesting recursive property, and general...

متن کامل

On the Distribution of the Maximal Clique Size for the Vertices in Real-world Network Graphs and Correlation Studies

The high-level contributions of this paper are as follows: We modify an existing branch-andbound based exact algorithm (for maximum clique size of an entire graph) to determine the maximal clique size that the individual vertices in the graph are part of. We then run this algorithm on six real-world network graphs (ranging from random networks to scale-free networks) and analyze the distributio...

متن کامل

ذخیره در منابع من


  با ذخیره ی این منبع در منابع من، دسترسی به آن را برای استفاده های بعدی آسان تر کنید

برای دانلود متن کامل این مقاله و بیش از 32 میلیون مقاله دیگر ابتدا ثبت نام کنید

ثبت نام

اگر عضو سایت هستید لطفا وارد حساب کاربری خود شوید

عنوان ژورنال:
  • CoRR

دوره abs/1308.5169  شماره 

صفحات  -

تاریخ انتشار 2013