Abstract

We consider configuration graphs with N vertices. The degrees of the vertices are independent identically distributed limited random variables. They are equal to the number of vertex semiedges that are numbered in an arbitrary order. The graph is constructed by joining all of the semiedges pairwise equiprobably to form edges. We study the subset of such random graphs under the condition that the sum of vertex degrees is known and it is equal to n. An important characteristic of the topology of a graph is the local clustering coefficient. We obtained the limit distributions of the local clustering coefficient and the number of triangles of each vertex as N and n tend to infinity. We also considered the limit behaviour of their mathematical expectations.

Highlights

  • We consider configuration graphs with N vertices

  • The degrees of the vertices are independent identically distributed limited random variables. They are equal to the number of vertex semiedges that are numbered in an arbitrary order

  • The graph is constructed by joining all of the semiedges pairwise equiprobably to form edges

Read more

Summary

Introduction

We consider configuration graphs with N vertices. The degrees of the vertices are independent identically distributed limited random variables. We consider configuration graphs with N vertices. We study the subset of such random graphs under the condition that the sum of vertex degrees is known and it is equal to n. Равную степени любой вершины графа, и пусть pk = P{ξ = k}, k = 1, 2, . Что сумма степеней вершин любого графа должна быть четной, поэтому в случае необходимости в граф вводится дополнительная вершина единичной степени.

Results
Conclusion
Full Text
Paper version not known

Talk to us

Join us for a 30 min session where you can share your feedback and ask us any queries you have

Schedule a call

Disclaimer: All third-party content on this website/platform is and will remain the property of their respective owners and is provided on "as is" basis without any warranties, express or implied. Use of third-party content does not indicate any affiliation, sponsorship with or endorsement by them. Any references to third-party content is to identify the corresponding services and shall be considered fair use under The CopyrightLaw.